diff --git a/.circleci/config.yml b/.circleci/config.yml
index 55fa9410845..dfc539fb80e 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -112,10 +112,10 @@ commands:
             node --version
             npm --version
   install_rust:
-    description: "Install pinned rustup (1.28.2) and Rust toolchain (1.97.1) with checksum verification. Adds ~/.cargo/bin to PATH. Run this before any `uv sync` or `uv build` of the workspace: the root package builds litellm-rust through maturin, and on an image without cargo maturin fetches an unpinned rustup and a floating toolchain by itself."
+    description: "Install pinned rustup (1.28.2) and Rust toolchain (1.98.0) with checksum verification. Adds ~/.cargo/bin to PATH. Run this before any `uv sync` or `uv build` of the workspace: the root package builds litellm-rust through maturin, and on an image without cargo maturin fetches an unpinned rustup and a floating toolchain by itself."
     steps:
       - run:
-          name: Install Rust (rustup 1.28.2, toolchain 1.97.1)
+          name: Install Rust (rustup 1.28.2, toolchain 1.98.0)
           command: |
             case "$(uname -m)" in
               x86_64)
@@ -135,7 +135,7 @@ commands:
               "https://static.rust-lang.org/rustup/archive/1.28.2/${RUSTUP_TRIPLE}/rustup-init"
             echo "${RUSTUP_SHA256}  /tmp/rustup-init" | sha256sum -c -
             chmod +x /tmp/rustup-init
-            /tmp/rustup-init -y --no-modify-path --profile minimal --default-toolchain 1.97.1
+            /tmp/rustup-init -y --no-modify-path --profile minimal --default-toolchain 1.98.0
             rm -f /tmp/rustup-init
             echo 'export PATH="$HOME/.cargo/bin:$PATH"' >> "$BASH_ENV"
             export PATH="$HOME/.cargo/bin:$PATH"
@@ -300,7 +300,7 @@ jobs:
             if ($rustupActual -ne $rustupExpected) {
               throw "rustup installer hash mismatch: expected $rustupExpected got $rustupActual"
             }
-            & $rustupInit -y --profile minimal --default-toolchain stable
+            & $rustupInit -y --profile minimal --default-toolchain 1.98.0
             if ($LASTEXITCODE -ne 0) {
               exit $LASTEXITCODE
             }
diff --git a/.github/scripts/smoke_test_native_wheel.py b/.github/scripts/smoke_test_native_wheel.py
new file mode 100644
index 00000000000..577bb32fcf0
--- /dev/null
+++ b/.github/scripts/smoke_test_native_wheel.py
@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+import subprocess
+import sys
+import tempfile
+import zipfile
+from pathlib import Path
+from typing import Final
+
+CHILD_SCRIPT: Final = """
+from importlib.util import module_from_spec, spec_from_file_location
+from pathlib import Path
+import sys
+
+native_path = Path(sys.argv[1])
+spec = spec_from_file_location("litellm.rust_bridge._native", native_path)
+if spec is None or spec.loader is None:
+    raise RuntimeError("cannot create native extension import specification")
+module = module_from_spec(spec)
+spec.loader.exec_module(module)
+
+before = module.gil_stats()
+if not isinstance(before.get("releases"), int):
+    raise AssertionError(f"unexpected gil_stats result: {before!r}")
+
+try:
+    module._panic_for_test()
+except BaseException as error:
+    if type(error).__name__ != "PanicException":
+        raise AssertionError(f"expected PanicException, got {type(error).__name__}") from error
+else:
+    raise AssertionError("Rust panic returned without raising")
+
+after = module.gil_stats()
+if not isinstance(after.get("releases"), int):
+    raise AssertionError(f"native module unusable after panic: {after!r}")
+"""
+
+
+def main() -> int:
+    if len(sys.argv) != 2:
+        sys.stderr.write(f"usage: {Path(sys.argv[0]).name} WHEEL\n")
+        return 2
+
+    wheel: Final = Path(sys.argv[1])
+    with tempfile.TemporaryDirectory() as temporary_directory, zipfile.ZipFile(wheel) as archive:
+        native_members: Final = tuple(
+            member
+            for member in archive.infolist()
+            if member.filename.startswith("litellm/rust_bridge/_native.") and member.filename.endswith(".so")
+        )
+        if len(native_members) != 1:
+            sys.stderr.write(f"expected one native extension, found {len(native_members)}\n")
+            return 1
+
+        native_path: Final = Path(temporary_directory) / Path(native_members[0].filename).name
+        native_path.write_bytes(archive.read(native_members[0]))
+        result: Final = subprocess.run((sys.executable, "-c", CHILD_SCRIPT, str(native_path)), check=False)
+
+    if result.returncode != 0:
+        sys.stderr.write(f"native wheel smoke test exited with status {result.returncode}\n")
+        return 1
+
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/.github/scripts/verify_linux_native_wheel.py b/.github/scripts/verify_linux_native_wheel.py
new file mode 100644
index 00000000000..899e2a211c0
--- /dev/null
+++ b/.github/scripts/verify_linux_native_wheel.py
@@ -0,0 +1,282 @@
+from __future__ import annotations
+
+import importlib.util
+import os
+import re
+import subprocess
+import sys
+import zipfile
+from collections.abc import Callable, Mapping, Sequence
+from itertools import product
+from pathlib import Path, PurePosixPath
+from types import MappingProxyType, ModuleType
+from typing import Final, Protocol
+
+EXPECTED_PYTHON_TAG: Final = "cp310"
+EXPECTED_ABI_TAG: Final = "abi3"
+EXPECTED_PLATFORM_TAG: Final = "linux_x86_64"
+
+
+class CommandRunner(Protocol):
+    def __call__(
+        self,
+        command: tuple[str, ...],
+        *,
+        check: bool,
+        capture_output: bool,
+        text: bool,
+    ) -> subprocess.CompletedProcess[str]: ...
+
+
+def _run_command(
+    command: tuple[str, ...],
+    *,
+    check: bool,
+    capture_output: bool,
+    text: bool,
+) -> subprocess.CompletedProcess[str]:
+    return subprocess.run(command, check=check, capture_output=capture_output, text=text)
+
+
+def _dist_info_directory(member: zipfile.ZipInfo) -> str | None:
+    parts: Final = PurePosixPath(member.filename).parts
+    if not parts or not parts[0].endswith(".dist-info"):
+        return None
+    return parts[0]
+
+
+def _wheel_metadata_tags(archive: zipfile.ZipFile, members: tuple[zipfile.ZipInfo, ...]) -> tuple[str, ...]:
+    if len(members) != 1:
+        return ()
+    lines: Final = archive.read(members[0]).splitlines()
+    return tuple(line.removeprefix(b"Tag:").strip().decode("ascii") for line in lines if line.startswith(b"Tag:"))
+
+
+def _load_native_module(native_path: Path) -> ModuleType | None:
+    module_spec: Final = importlib.util.spec_from_file_location("litellm.rust_bridge._native", native_path)
+    if module_spec is None or module_spec.loader is None:
+        return None
+    try:
+        native_module: Final = importlib.util.module_from_spec(module_spec)
+        module_spec.loader.exec_module(native_module)
+    except Exception as error:  # noqa: BLE001  # native module initialization can raise arbitrary exceptions
+        sys.stderr.write(f"native module load failed: {error}\n")
+        return None
+    return native_module
+
+
+def main(
+    argv: Sequence[str] | None = None,
+    environment: Mapping[str, str] | None = None,
+    load_native_module: Callable[[Path], ModuleType | None] = _load_native_module,
+    run_command: CommandRunner = _run_command,
+) -> int:
+    arguments: Final = tuple(sys.argv if argv is None else argv)
+    resolved_environment: Final = os.environ if environment is None else environment
+    if len(arguments) != 2:
+        sys.stderr.write(f"usage: {Path(arguments[0]).name} WHEEL\n")
+        return 2
+
+    wheel: Final = Path(arguments[1])
+    wheel_tags: Final = wheel.stem.rsplit("-", maxsplit=3)
+    if len(wheel_tags) != 4:
+        sys.stderr.write(f"cannot parse wheel tags from {wheel.name}\n")
+        return 1
+
+    wheel_identity: Final = wheel_tags[0].split("-")
+    if len(wheel_identity) != 2 or wheel_identity[0] != "litellm" or not wheel_identity[1]:
+        sys.stderr.write(f"unexpected wheel identity: {wheel_tags[0]}\n")
+        return 1
+
+    expected_dist_info_directory: Final = f"{wheel_tags[0]}.dist-info"
+    expected_dist_info_directories: Final = frozenset((expected_dist_info_directory,))
+    python_tag: Final = wheel_tags[1]
+    abi_tag: Final = wheel_tags[2]
+    platform_tag: Final = wheel_tags[3]
+    expanded_filename_tags: Final = frozenset(
+        "-".join(tag) for tag in product(python_tag.split("."), abi_tag.split("."), platform_tag.split("."))
+    )
+
+    with zipfile.ZipFile(wheel) as archive:
+        wheel_members: Final = archive.infolist()
+        dist_info_directories: Final = frozenset(
+            directory for member in wheel_members if (directory := _dist_info_directory(member)) is not None
+        )
+        required_dist_info_files: Final = ("METADATA", "RECORD", "WHEEL")
+        dist_info_file_counts: Final = MappingProxyType(
+            {
+                filename: sum(
+                    member.filename == f"{expected_dist_info_directory}/{filename}" for member in wheel_members
+                )
+                for filename in required_dist_info_files
+            }
+        )
+        wheel_metadata_members: Final = tuple(
+            member for member in wheel_members if member.filename == f"{expected_dist_info_directory}/WHEEL"
+        )
+        wheel_metadata_tags: Final = _wheel_metadata_tags(archive, wheel_metadata_members)
+        native_members: Final = tuple(
+            member
+            for member in wheel_members
+            if member.filename.startswith("litellm/rust_bridge/_native.") and member.filename.endswith(".so")
+        )
+        if len(native_members) != 1:
+            sys.stderr.write(f"expected one native extension, found {len(native_members)}\n")
+            return 1
+
+        unexpected_members: Final = tuple(
+            member.filename
+            for member in wheel_members
+            if member.filename.endswith((".pdb", ".dwp", ".rlib", ".rmeta", "Cargo.toml", "Cargo.lock"))
+            or any(part.endswith(".dSYM") for part in PurePosixPath(member.filename).parts)
+        )
+        native_member: Final = native_members[0]
+        uncompressed_wheel_size: Final = sum(member.file_size for member in wheel_members)
+        native_path: Final = wheel.parent / "native" / Path(native_member.filename).name
+        native_path.parent.mkdir(parents=True, exist_ok=True)
+        native_path.write_bytes(archive.read(native_member))
+
+    wheel_metadata_tags_match: Final = (
+        len(wheel_metadata_tags) == len(expanded_filename_tags)
+        and frozenset(wheel_metadata_tags) == expanded_filename_tags
+    )
+    commit_sha: Final = resolved_environment.get(
+        "RELEASE_WHEEL_COMMIT_SHA", resolved_environment.get("GITHUB_SHA", "unknown")
+    )
+    rustc_version: Final = run_command(
+        ("rustc", "--version"),
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    pyproject: Final = (Path(__file__).parents[2] / "pyproject.toml").read_text()
+    maturin_match: Final = re.search(r'"maturin==([^";]+)', pyproject)
+    if maturin_match is None:
+        sys.stderr.write("build-system does not pin an exact Maturin version\n")
+        return 1
+
+    maturin_version: Final = maturin_match.group(1)
+    native_percentage: Final = native_member.file_size / uncompressed_wheel_size * 100
+    size_report: Final = "\n".join(
+        (
+            "## Native wheel build report",
+            "",
+            "| Build | Value |",
+            "| --- | --- |",
+            f"| Commit | `{commit_sha}` |",
+            f"| Platform | `{platform_tag}` |",
+            f"| Python ABI | `{python_tag}-{abi_tag}` |",
+            f"| Rust compiler | `{rustc_version}` |",
+            f"| Maturin | `{maturin_version}` |",
+            "| Cargo profile | `release` |",
+            "",
+            "| Artifact | Size |",
+            "| --- | ---: |",
+            f"| Compressed wheel | {wheel.stat().st_size / 1_000_000:.2f} MB |",
+            f"| Uncompressed wheel | {uncompressed_wheel_size / 1_000_000:.2f} MB |",
+            f"| Native extension | {native_member.file_size / 1_000_000:.2f} MB |",
+            f"| Native share | {native_percentage:.2f}% |",
+            "",
+        )
+    )
+    summary_path: Final = resolved_environment.get("GITHUB_STEP_SUMMARY")
+    if summary_path is None:
+        sys.stdout.write(size_report)
+    else:
+        Path(summary_path).write_text(size_report)
+
+    sections: Final = run_command(
+        ("readelf", "--sections", "--wide", str(native_path)),
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout
+    debug_sections: Final = tuple(section for section in (".debug_", ".zdebug_") if section in sections)
+    debug_sections_absent: Final = not debug_sections
+    static_symbol_table_absent: Final = ".symtab" not in sections
+
+    dynamic_symbols: Final = run_command(
+        ("readelf", "--dyn-syms", "--wide", str(native_path)),
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout
+    extension_entry_point_present: Final = "PyInit__native" in dynamic_symbols
+    native_module: Final = load_native_module(native_path)
+    native_module_loads: Final = native_module is not None
+    panic_test_hook_absent: Final = native_module is not None and not hasattr(native_module, "_panic_for_test")
+    native_size_limit: Final = 20_000_000
+    native_size_within_limit: Final = native_member.file_size <= native_size_limit
+    validations: Final = (
+        (f"Python tag is {EXPECTED_PYTHON_TAG}", python_tag == EXPECTED_PYTHON_TAG),
+        (f"ABI tag is {EXPECTED_ABI_TAG}", abi_tag == EXPECTED_ABI_TAG),
+        (f"Platform tag is {EXPECTED_PLATFORM_TAG}", platform_tag == EXPECTED_PLATFORM_TAG),
+        ("Wheel dist-info directory matches the filename", dist_info_directories == expected_dist_info_directories),
+        (
+            "Required dist-info files are present exactly once",
+            all(count == 1 for count in dist_info_file_counts.values()),
+        ),
+        ("Wheel metadata tags match the filename", wheel_metadata_tags_match),
+        ("Debug sections are absent", debug_sections_absent),
+        ("Static symbol table is absent", static_symbol_table_absent),
+        ("Python extension entry point is present", extension_entry_point_present),
+        ("Native module loads", native_module_loads),
+        ("Production module omits the panic test hook", panic_test_hook_absent),
+        ("Native extension does not exceed 20 MB", native_size_within_limit),
+        ("Wheel contents are valid", not unexpected_members),
+    )
+
+    verified_report: Final = size_report + "\n".join(
+        ("", "| Validation | Expected | Result |", "| --- | --- | :---: |")
+        + tuple(f"| {label} | Yes | {'O' if passed else 'X'} |" for label, passed in validations)
+        + ("",)
+    )
+    if summary_path is not None:
+        Path(summary_path).write_text(verified_report)
+
+    invalid_dist_info_files: Final = any(count != 1 for count in dist_info_file_counts.values())
+    validation_errors: Final = tuple(
+        message
+        for failed, message in (
+            (bool(debug_sections), f"{native_member.filename} contains debug sections: {', '.join(debug_sections)}"),
+            (not static_symbol_table_absent, f"{native_member.filename} contains a static symbol table"),
+            (not extension_entry_point_present, "native extension does not export PyInit__native"),
+            (
+                python_tag != EXPECTED_PYTHON_TAG,
+                f"unexpected Python tag: expected {EXPECTED_PYTHON_TAG}, found {python_tag}",
+            ),
+            (abi_tag != EXPECTED_ABI_TAG, f"unexpected ABI tag: expected {EXPECTED_ABI_TAG}, found {abi_tag}"),
+            (
+                platform_tag != EXPECTED_PLATFORM_TAG,
+                f"unexpected platform tag: expected {EXPECTED_PLATFORM_TAG}, found {platform_tag}",
+            ),
+            (
+                dist_info_directories != expected_dist_info_directories,
+                f"unexpected dist-info directories: expected {expected_dist_info_directory}, "
+                f"found {', '.join(sorted(dist_info_directories))}",
+            ),
+            (invalid_dist_info_files, f"required dist-info file counts are invalid: {dist_info_file_counts}"),
+            (
+                not invalid_dist_info_files and not wheel_metadata_tags_match,
+                f"WHEEL tags do not match filename: expected {', '.join(sorted(expanded_filename_tags))}, "
+                f"found {', '.join(sorted(wheel_metadata_tags))}",
+            ),
+            (
+                native_module is not None and not panic_test_hook_absent,
+                "production native module exposes _panic_for_test",
+            ),
+            (
+                not native_size_within_limit,
+                f"native extension exceeds 20 MB: {native_member.file_size / 1_000_000:.2f} MB",
+            ),
+            (bool(unexpected_members), f"wheel contains unexpected build artifacts: {', '.join(unexpected_members)}"),
+        )
+        if failed
+    )
+    sys.stderr.write("".join(f"{message}\n" for message in validation_errors))
+
+    return 0 if all(passed for _, passed in validations) else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/.github/workflows/image-scan.yml b/.github/workflows/image-scan.yml
index bb04563c1a8..206bb809e0c 100644
--- a/.github/workflows/image-scan.yml
+++ b/.github/workflows/image-scan.yml
@@ -80,7 +80,7 @@ jobs:
           LITELLM_IMAGE: litellm-image-scan:${{ github.sha }}
         run: |
           python -m pip install "pytest==9.0.3"
-          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py -v
+          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py -v
 
       # Scans the whole shipped artifact: OS/apk plus every language package
       # baked into the image, including ones no lockfile declares (e.g. prisma's
@@ -124,7 +124,7 @@ jobs:
           LITELLM_IMAGE: litellm-runtime-scan:${{ github.sha }}
         run: |
           python -m pip install "pytest==9.0.3"
-          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py -v
+          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py -v
 
   migrations-image:
     name: migrations-image
@@ -185,7 +185,7 @@ jobs:
           LITELLM_COMPONENT_PORT: "4000"
         run: |
           python -m pip install "pytest==9.0.3"
-          python -m pytest tests/proxy_migration_tests/test_component_image_serves_offline.py -v
+          python -m pytest tests/proxy_migration_tests/test_component_image_serves_offline.py tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py -v
 
   ui-image:
     name: ui-image
diff --git a/.github/workflows/report-rust-release-wheel.yml b/.github/workflows/report-rust-release-wheel.yml
new file mode 100644
index 00000000000..1d93b56f77f
--- /dev/null
+++ b/.github/workflows/report-rust-release-wheel.yml
@@ -0,0 +1,130 @@
+name: Report LiteLLM Rust release wheel
+
+on: # zizmor: ignore[dangerous-triggers] reporter executes no PR code and consumes no PR artifacts or outputs
+  workflow_run:
+    workflows:
+      - LiteLLM Rust
+    types:
+      - completed
+
+permissions: {}
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.workflow_run.pull_requests[0].number || github.event.workflow_run.id }}
+  cancel-in-progress: false
+
+jobs:
+  report-release-wheel:
+    name: report release wheel
+    if: >-
+      github.event.workflow_run.event == 'pull_request' &&
+      github.event.workflow_run.path == '.github/workflows/test-rust.yml' &&
+      github.event.workflow_run.head_repository.full_name == github.repository &&
+      github.event.workflow_run.pull_requests[0].number != null
+    runs-on: ubuntu-latest
+    timeout-minutes: 5
+    permissions:
+      issues: write # PR comments use the issues API
+      pull-requests: read # Current-head validation rejects stale workflow runs
+
+    steps:
+      - name: Link release wheel report on PR
+        uses: actions/github-script@f28e40c7f34bde8b3046d885e986cb6290c5673b # v7.1.0
+        env:
+          COMMENT_MARKER: "<!-- litellm-release-wheel-size -->"
+        with:
+          script: |
+            const marker = process.env.COMMENT_MARKER;
+            const workflowRun = context.payload.workflow_run;
+            const allowedConclusions = new Set([
+              "action_required",
+              "cancelled",
+              "failure",
+              "neutral",
+              "skipped",
+              "stale",
+              "startup_failure",
+              "success",
+              "timed_out",
+            ]);
+            if (
+              !allowedConclusions.has(workflowRun.conclusion) ||
+              workflowRun.event !== "pull_request" ||
+              workflowRun.path !== ".github/workflows/test-rust.yml" ||
+              workflowRun.head_repository?.full_name !==
+                `${context.repo.owner}/${context.repo.repo}` ||
+              workflowRun.pull_requests?.length !== 1
+            ) {
+              throw new Error("unexpected source workflow");
+            }
+            const pullRequest = workflowRun.pull_requests[0];
+            const pullRequestNumber = pullRequest.number;
+            const headSha = workflowRun.head_sha;
+            const runId = workflowRun.id;
+            if (
+              !Number.isSafeInteger(pullRequestNumber) ||
+              pullRequestNumber <= 0 ||
+              !Number.isSafeInteger(runId) ||
+              runId <= 0 ||
+              !/^[0-9a-f]{40}$/.test(headSha) ||
+              pullRequest.head?.sha !== headSha
+            ) {
+              throw new Error("invalid source workflow metadata");
+            }
+            const runUrl =
+              `${context.serverUrl}/${context.repo.owner}/${context.repo.repo}` +
+              `/actions/runs/${runId}`;
+            const result =
+              workflowRun.conclusion === "success"
+                ? "successfully"
+                : `with \`${workflowRun.conclusion}\``;
+            const body = [
+              marker,
+              "## LiteLLM Rust workflow",
+              "",
+              `Workflow completed ${result} for \`${headSha}\``,
+              "",
+              `[View workflow run](${runUrl})`,
+            ].join("\n");
+            const comments = await github.paginate(github.rest.issues.listComments, {
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: pullRequestNumber,
+              per_page: 100,
+            });
+            const existing = comments.find(
+              (comment) =>
+                comment.user?.login === "github-actions[bot]" &&
+                comment.body?.startsWith(marker),
+            );
+            const currentPullRequest = (
+              await github.rest.pulls.get({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                pull_number: pullRequestNumber,
+              })
+            ).data;
+            if (
+              currentPullRequest.state !== "open" ||
+              currentPullRequest.head.repo?.full_name !==
+                `${context.repo.owner}/${context.repo.repo}` ||
+              currentPullRequest.head.sha !== headSha
+            ) {
+              core.info("source workflow no longer matches the current pull request head");
+              return;
+            }
+            if (existing) {
+              await github.rest.issues.updateComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                comment_id: existing.id,
+                body,
+              });
+            } else {
+              await github.rest.issues.createComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: pullRequestNumber,
+                body,
+              });
+            }
diff --git a/.github/workflows/test-rust.yml b/.github/workflows/test-rust.yml
index 21e1bcb90c6..aada0fcf239 100644
--- a/.github/workflows/test-rust.yml
+++ b/.github/workflows/test-rust.yml
@@ -4,6 +4,11 @@ on:
   push:
     paths:
       - "litellm-rust/**"
+      - ".cargo/**"
+      - "pyproject.toml"
+      - "rust-toolchain.toml"
+      - ".github/scripts/smoke_test_native_wheel.py"
+      - ".github/scripts/verify_linux_native_wheel.py"
       - ".github/workflows/test-rust.yml"
   pull_request:
     branches:
@@ -13,6 +18,11 @@ on:
       - "litellm_**"
     paths:
       - "litellm-rust/**"
+      - ".cargo/**"
+      - "pyproject.toml"
+      - "rust-toolchain.toml"
+      - ".github/scripts/smoke_test_native_wheel.py"
+      - ".github/scripts/verify_linux_native_wheel.py"
       - ".github/workflows/test-rust.yml"
 
 permissions:
@@ -40,9 +50,7 @@ jobs:
           persist-credentials: false
 
       - name: Set up Rust
-        run: |
-          rustup toolchain install stable --profile minimal --component clippy,rustfmt
-          rustup default stable
+        run: rustup toolchain install
 
       - name: Cache Cargo registry and target
         uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
@@ -51,7 +59,7 @@ jobs:
             ~/.cargo/registry
             ~/.cargo/git
             litellm-rust/target
-          key: ${{ runner.os }}-cargo-${{ hashFiles('litellm-rust/Cargo.lock') }}
+          key: ${{ runner.os }}-cargo-${{ hashFiles('rust-toolchain.toml', 'litellm-rust/Cargo.lock') }}
           restore-keys: |
             ${{ runner.os }}-cargo-
 
@@ -69,3 +77,47 @@ jobs:
 
       - name: Run core tests with Bedrock auth
         run: cargo test -p litellm-core --features bedrock-auth --locked
+
+  release-wheel:
+    name: release wheel
+    runs-on: ubuntu-latest
+    timeout-minutes: 20
+    permissions:
+      contents: read
+    env:
+      CARGO_TERM_COLOR: always
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
+        with:
+          persist-credentials: false
+
+      - name: Set up Python
+        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
+        with:
+          python-version: "3.12"
+
+      - name: Set up uv
+        uses: ./.github/actions/setup-uv-with-retries
+        with:
+          version: "0.10.9"
+
+      - name: Set up Rust
+        run: rustup toolchain install
+
+      - name: Build release wheel
+        run: uv build --wheel --out-dir dist
+
+      - name: Build panic contract wheel
+        run: >-
+          uv build --wheel --out-dir panic-dist
+          --config-setting "maturin.build-args=--features panic-test,extension-module"
+
+      - name: Smoke-test native panic unwinding
+        run: python .github/scripts/smoke_test_native_wheel.py panic-dist/*.whl
+
+      - name: Verify stripped native extension
+        env:
+          RELEASE_WHEEL_COMMIT_SHA: ${{ github.event.pull_request.head.sha || github.sha }}
+        run: python .github/scripts/verify_linux_native_wheel.py dist/*.whl
diff --git a/Dockerfile b/Dockerfile
index 29a085a4ef9..0a92aa9a68c 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -66,6 +66,7 @@ RUN uv sync --frozen --no-install-project --no-install-workspace --no-default-gr
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 # Copy full source tree
@@ -87,6 +88,7 @@ RUN uv sync --frozen --no-default-groups --no-editable \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
diff --git a/backend/Dockerfile b/backend/Dockerfile
index aa01b9fba8b..622fedcd70d 100644
--- a/backend/Dockerfile
+++ b/backend/Dockerfile
@@ -46,6 +46,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
         --extra proxy-runtime \
         --extra extra_proxy \
         --extra semantic-router \
+        --extra saml \
         --python python3.13
 
 # Stage 2 — copy source and install the project + workspace members.
@@ -57,6 +58,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
         --extra proxy-runtime \
         --extra extra_proxy \
         --extra semantic-router \
+        --extra saml \
         --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json
index df52069e71f..da788bf1ce3 100644
--- a/basedpyright-code-budget.json
+++ b/basedpyright-code-budget.json
@@ -117,7 +117,7 @@
     "limit": 111
   },
   "reportUnnecessaryComparison": {
-    "limit": 695
+    "limit": 692
   },
   "reportUnnecessaryContains": {
     "limit": 5
diff --git a/docker/Dockerfile.database b/docker/Dockerfile.database
index c1348f68231..e9ad2849bb2 100644
--- a/docker/Dockerfile.database
+++ b/docker/Dockerfile.database
@@ -64,6 +64,7 @@ RUN uv sync --frozen --no-install-project --no-install-workspace --no-default-gr
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 # Copy full source tree
@@ -85,6 +86,7 @@ RUN uv sync --frozen --no-default-groups --no-editable \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
diff --git a/docker/Dockerfile.non_root b/docker/Dockerfile.non_root
index 2221435a83a..edf20e8bbff 100644
--- a/docker/Dockerfile.non_root
+++ b/docker/Dockerfile.non_root
@@ -70,6 +70,7 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 # Copy full source tree
@@ -97,6 +98,7 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
         --extra extra_proxy \
         --extra semantic-router \
         --extra saml \
+        --extra bedrock-realtime \
         --python python3.13 \
         --no-sources-package litellm-proxy-extras; \
     else \
@@ -106,6 +108,7 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
         --extra extra_proxy \
         --extra semantic-router \
         --extra saml \
+        --extra bedrock-realtime \
         --python python3.13; \
     fi
 
diff --git a/helm/litellm-helm/Chart.yaml b/helm/litellm-helm/Chart.yaml
index 3959d85edf3..a3cb388ffc6 100644
--- a/helm/litellm-helm/Chart.yaml
+++ b/helm/litellm-helm/Chart.yaml
@@ -18,7 +18,7 @@ type: application
 # This is the chart version. This version number should be incremented each time you make changes
 # to the chart and its templates, including the app version.
 # Versions are expected to follow Semantic Versioning (https://semver.org/)
-version: 1.1.2
+version: 1.1.3
 
 # This is the version number of the application being deployed. This version number should be
 # incremented each time you make changes to the application. Versions are not expected to
diff --git a/helm/litellm-helm/README.md b/helm/litellm-helm/README.md
index b242373de5d..bf4089404db 100644
--- a/helm/litellm-helm/README.md
+++ b/helm/litellm-helm/README.md
@@ -26,7 +26,7 @@ If `db.useStackgresOperator` is used (not yet implemented):
 | `replicaCount`              | The number of LiteLLM Proxy pods to be deployed                                                                                                                                                                                               | `1`                       |
 | `masterkeySecretName`       | The name of the Kubernetes Secret that contains the Master API Key for LiteLLM. If not specified, use the generated secret name.                                                                                                              | N/A                       |
 | `masterkeySecretKey`        | The key within the Kubernetes Secret that contains the Master API Key for LiteLLM. If not specified, use `masterkey` as the key.                                                                                                              | N/A                       |
-| `masterkey`                 | The Master API Key for LiteLLM. If not specified, a random key in the `sk-...` format is generated.                                                                                                                                           | N/A                       |
+| `masterkey`                 | The Master API Key for LiteLLM. If not specified, a random key in the `sk-...` format is generated on first install and reused on upgrades. | N/A                       |
 | `environmentSecrets`        | An optional array of Secret object names. The keys and values in these secrets will be presented to the LiteLLM proxy pod as environment variables. See below for an example Secret object.                                                   | `[]`                      |
 | `environmentConfigMaps`     | An optional array of ConfigMap object names. The keys and values in these configmaps will be presented to the LiteLLM proxy pod as environment variables. See below for an example Secret object.                                             | `[]`                      |
 | `image.repository`          | LiteLLM Proxy image repository                                                                                                                                                                                                                | `ghcr.io/berriai/litellm` |
@@ -212,6 +212,8 @@ service, the **Proxy Endpoint** should be set to `http://<RELEASE>-litellm:4000`
 The **Proxy Key** is the value specified for `masterkey` or, if a `masterkey`
 was not provided to the helm command line, the `masterkey` is a randomly
 generated string in the `sk-...` format stored in the `<RELEASE>-litellm-masterkey` Kubernetes Secret.
+The key is generated once on the first install; later `helm upgrade` runs reuse the
+value already in that Secret, so upgrading never rotates the master key.
 
 ```bash
 kubectl -n litellm get secret <RELEASE>-litellm-masterkey -o jsonpath="{.data.masterkey}"
diff --git a/helm/litellm-helm/templates/secret-masterkey.yaml b/helm/litellm-helm/templates/secret-masterkey.yaml
index 7c8560cc2cc..60ab4e74c6b 100644
--- a/helm/litellm-helm/templates/secret-masterkey.yaml
+++ b/helm/litellm-helm/templates/secret-masterkey.yaml
@@ -1,9 +1,11 @@
 {{- if not .Values.masterkeySecretName }}
-{{ $masterkey := (.Values.masterkey | default (printf "sk-%s" (randAlphaNum 18))) }}
+{{- $secretName := printf "%s-masterkey" (include "litellm.fullname" .) }}
+{{- $existing := lookup "v1" "Secret" .Release.Namespace $secretName }}
+{{- $masterkey := .Values.masterkey | default (dig "data" "masterkey" "" $existing | b64dec) | default (printf "sk-%s" (randAlphaNum 18)) }}
 apiVersion: v1
 kind: Secret
 metadata:
-  name: {{ include "litellm.fullname" . }}-masterkey
+  name: {{ $secretName }}
 data:
   masterkey: {{ $masterkey | b64enc }}
 type: Opaque
diff --git a/helm/litellm-helm/tests/hpa_tests.yaml b/helm/litellm-helm/tests/hpa_tests.yaml
index ec18c3591d3..cd062dd5971 100644
--- a/helm/litellm-helm/tests/hpa_tests.yaml
+++ b/helm/litellm-helm/tests/hpa_tests.yaml
@@ -1,4 +1,4 @@
-suite: "hpa with behavior"
+suite: "hpa"
 templates:
   - hpa.yaml
 tests:
@@ -23,14 +23,44 @@ tests:
       - equal: { path: spec.behavior.scaleUp.stabilizationWindowSeconds, value: 60 }
       - equal: { path: spec.behavior.scaleDown.stabilizationWindowSeconds, value: 90 }
 
----
-suite: "hpa without behavior"
-templates:
-  - hpa.yaml
-tests:
   - it: "does not render behavior when not set"
     set:
       autoscaling.enabled: true
     asserts:
       - isKind: { of: HorizontalPodAutoscaler }
       - isNull: { path: spec.behavior }
+
+  - it: "scales on cpu at the documented 60 percent by default"
+    set:
+      autoscaling.enabled: true
+    asserts:
+      - isKind: { of: HorizontalPodAutoscaler }
+      - equal: { path: "spec.metrics[0].resource.name", value: cpu }
+      - equal: { path: "spec.metrics[0].resource.target.type", value: Utilization }
+      - equal: { path: "spec.metrics[0].resource.target.averageUtilization", value: 60 }
+
+  - it: "does not scale on memory by default"
+    set:
+      autoscaling.enabled: true
+    asserts:
+      - lengthEqual: { path: spec.metrics, count: 1 }
+
+  - it: "honours an explicit cpu target override"
+    set:
+      autoscaling.enabled: true
+      autoscaling.targetCPUUtilizationPercentage: 75
+    asserts:
+      - equal: { path: "spec.metrics[0].resource.target.averageUtilization", value: 75 }
+
+  - it: "renders a memory metric only when a memory target is set"
+    set:
+      autoscaling.enabled: true
+      autoscaling.targetMemoryUtilizationPercentage: 80
+    asserts:
+      - lengthEqual: { path: spec.metrics, count: 2 }
+      - equal: { path: "spec.metrics[1].resource.name", value: memory }
+      - equal: { path: "spec.metrics[1].resource.target.averageUtilization", value: 80 }
+
+  - it: "renders no hpa when autoscaling is disabled"
+    asserts:
+      - hasDocuments: { count: 0 }
diff --git a/helm/litellm-helm/tests/masterkey-secret_tests.yaml b/helm/litellm-helm/tests/masterkey-secret_tests.yaml
index bbbade9d802..296f26755b8 100644
--- a/helm/litellm-helm/tests/masterkey-secret_tests.yaml
+++ b/helm/litellm-helm/tests/masterkey-secret_tests.yaml
@@ -15,6 +15,53 @@ tests:
           # Note: The masterkey is generated as "sk-<18-random-chars>" in plain text,
           # but stored as base64 encoded in Kubernetes secret (requirement).
           # "sk-" base64 encodes to "c2st", so we check for "^c2st" pattern.
+  - it: should reuse the master key already stored in the cluster instead of generating a new one on upgrade
+    template: secret-masterkey.yaml
+    set:
+      masterkeySecretName: ""
+    kubernetesProvider:
+      scheme:
+        "v1/Secret":
+          gvr:
+            version: "v1"
+            resource: "secrets"
+          namespaced: true
+      objects:
+        - kind: Secret
+          apiVersion: v1
+          metadata:
+            name: RELEASE-NAME-litellm-masterkey
+            namespace: NAMESPACE
+          data:
+            masterkey: c2stZXhpc3Rpbmcta2V5
+    asserts:
+      - equal:
+          path: data.masterkey
+          value: c2stZXhpc3Rpbmcta2V5
+  - it: should let an explicit masterkey value override the one already stored in the cluster
+    template: secret-masterkey.yaml
+    set:
+      masterkeySecretName: ""
+      masterkey: sk-explicit
+    kubernetesProvider:
+      scheme:
+        "v1/Secret":
+          gvr:
+            version: "v1"
+            resource: "secrets"
+          namespaced: true
+      objects:
+        - kind: Secret
+          apiVersion: v1
+          metadata:
+            name: RELEASE-NAME-litellm-masterkey
+            namespace: NAMESPACE
+          data:
+            masterkey: c2stZXhpc3Rpbmcta2V5
+    asserts:
+      - equal:
+          path: data.masterkey
+          value: c2stZXhwbGljaXQ=
   - it: should not create a secret if masterkeySecretName is set
     template: secret-masterkey.yaml
     set:
diff --git a/helm/litellm-helm/values.yaml b/helm/litellm-helm/values.yaml
index f8df98de102..637be2322e3 100644
--- a/helm/litellm-helm/values.yaml
+++ b/helm/litellm-helm/values.yaml
@@ -200,7 +200,16 @@ autoscaling:
   enabled: false
   minReplicas: 1
   maxReplicas: 100
-  targetCPUUtilizationPercentage: 80
+  # 60 is the documented recommendation. See "Recommended Machine Specifications"
+  # in https://docs.litellm.ai/docs/proxy/prod. A new replica clears the startupProbe
+  # above only after up to failureThreshold x periodSeconds = 300 seconds, so a target
+  # high enough to trip near saturation adds capacity minutes after it was needed.
+  targetCPUUtilizationPercentage: 60
+  # Deliberately left unset rather than given a value. The prisma query engine's
+  # resident memory is a high-water mark that ratchets to the pod's worst-ever write
+  # and is never returned, so a memory target reads the largest write a pod ever did
+  # rather than what it is doing now, and replicas ratchet up without scaling back in.
+  # Memory is a floor to provision under 'resources', not a signal to scale on.
   # targetMemoryUtilizationPercentage: 80
   # behavior: {}
 
diff --git a/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py b/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py
index f3b55fd4d96..2283814ab35 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py
+++ b/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py
@@ -14,9 +14,22 @@ then fails on a Node binary that was never written. Deleting a cache directory
 that exists without a Node binary is what turns a killed bootstrap back into a
 recoverable one.
 
-Both budgets are overridable so an operator can widen them without a release:
-``LITELLM_PRISMA_BOOTSTRAP_TIMEOUT`` for the toolchain install and
-``LITELLM_PRISMA_COMMAND_TIMEOUT`` for every individual Prisma command.
+``prisma migrate deploy`` is the other command whose runtime is not a
+constant: it grows with the number of pending migrations, so a fresh database
+that has to replay every migration this package ships overruns a per-command
+budget sized for the short bookkeeping commands, on a laptop as much as on a
+slow CI runner. The Python ``prisma`` wrapper spawns Node and the schema engine
+as separate children, so killing the wrapper on timeout leaves them running:
+the retry then contends with that orphan for Prisma's advisory lock and cannot
+finish any sooner. Migrate deploy therefore runs under its own budget.
+
+All three budgets are overridable so an operator can widen them without a
+release: ``LITELLM_PRISMA_BOOTSTRAP_TIMEOUT`` for the toolchain install,
+``LITELLM_PRISMA_MIGRATE_DEPLOY_TIMEOUT`` for ``prisma migrate deploy`` and
+``LITELLM_PRISMA_COMMAND_TIMEOUT`` for every other Prisma command. The
+per-command budget used to bound migrate deploy as well, so a deployment that
+raised it above the deploy default keeps that larger budget for deploy unless
+the deploy override says otherwise.
 """
 
 import math
@@ -36,10 +49,12 @@ except ImportError:
 
 PRISMA_COMMAND_TIMEOUT_ENV_VAR = "LITELLM_PRISMA_COMMAND_TIMEOUT"
 PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR = "LITELLM_PRISMA_BOOTSTRAP_TIMEOUT"
+PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR = "LITELLM_PRISMA_MIGRATE_DEPLOY_TIMEOUT"
 NODEENV_CACHE_DIR_ENV_VAR = "PRISMA_NODEENV_CACHE_DIR"
 
 DEFAULT_PRISMA_COMMAND_TIMEOUT = 60.0
 DEFAULT_PRISMA_BOOTSTRAP_TIMEOUT = 600.0
+DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT = 600.0
 
 BOOTSTRAP_ARG = "--version"
 
@@ -88,6 +103,15 @@ def prisma_bootstrap_timeout() -> float:
     )
 
 
+def prisma_migrate_deploy_timeout() -> float:
+    """Seconds one ``prisma migrate deploy`` may run for, however many migrations are pending."""
+    if os.getenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR) is not None:
+        return _timeout_from_env(
+            PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT
+        )
+    return max(DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT, prisma_command_timeout())
+
+
 def nodeenv_cache_dir() -> Optional[Path]:
     """Where Prisma installs its private Node runtime, or None if unknowable."""
     override = os.getenv(NODEENV_CACHE_DIR_ENV_VAR)
diff --git a/litellm-proxy-extras/litellm_proxy_extras/utils.py b/litellm-proxy-extras/litellm_proxy_extras/utils.py
index b8032dd0d28..f6647268624 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/utils.py
+++ b/litellm-proxy-extras/litellm_proxy_extras/utils.py
@@ -15,8 +15,11 @@ from litellm_proxy_extras.replica_identity import (
     apply_replica_identity_full,
 )
 from litellm_proxy_extras.prisma_toolchain import (
+    PRISMA_COMMAND_TIMEOUT_ENV_VAR,
+    PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR,
     ensure_prisma_toolchain,
     prisma_command_timeout,
+    prisma_migrate_deploy_timeout,
 )
 
 
@@ -698,12 +701,13 @@ class ProxyExtrasDBManager:
 
         original_dir = os.getcwd()
         os.chdir(migrations_dir)
+        deploy_timeout = prisma_migrate_deploy_timeout()
         try:
             for attempt in range(4):
                 try:
                     result = subprocess.run(
                         [_get_prisma_command(), "migrate", "deploy"],
-                        timeout=prisma_command_timeout(),
+                        timeout=deploy_timeout,
                         check=True,
                         capture_output=True,
                         text=True,
@@ -713,8 +717,12 @@ class ProxyExtrasDBManager:
                     return True
 
                 except subprocess.TimeoutExpired:
-                    logger.info(
-                        f"prisma migrate deploy attempt {attempt + 1} timed out, retrying"
+                    logger.warning(
+                        "prisma migrate deploy attempt %s timed out after %ss, retrying. "
+                        "Raise %s if this database needs longer to apply its pending migrations.",
+                        attempt + 1,
+                        deploy_timeout,
+                        PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR,
                     )
                     time.sleep(random.randrange(5, 15))
                     continue
@@ -823,7 +831,8 @@ class ProxyExtrasDBManager:
                 "Database migration failed after 4 attempts (retry loop "
                 "exhausted by timeouts or repeated idempotent-recovery "
                 "continues). Check database connectivity, load, and "
-                "_prisma_migrations ledger state."
+                "_prisma_migrations ledger state, and raise "
+                f"{PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR} if the attempts timed out."
             )
         finally:
             os.chdir(original_dir)
@@ -908,7 +917,7 @@ class ProxyExtrasDBManager:
                         # Set migrations directory for Prisma
                         result = subprocess.run(
                             [_get_prisma_command(), "migrate", "deploy"],
-                            timeout=prisma_command_timeout(),
+                            timeout=prisma_migrate_deploy_timeout(),
                             check=True,
                             capture_output=True,
                             text=True,
@@ -1126,7 +1135,11 @@ class ProxyExtrasDBManager:
                     )
                     return True
             except subprocess.TimeoutExpired:
-                logger.info(f"Attempt {attempt + 1} timed out")
+                logger.warning(
+                    "Attempt %s timed out. Raise %s if this database needs longer to apply its schema.",
+                    attempt + 1,
+                    PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR if use_migrate else PRISMA_COMMAND_TIMEOUT_ENV_VAR,
+                )
                 time.sleep(random.randrange(5, 15))
             except subprocess.CalledProcessError as e:
                 attempts_left = 3 - attempt
diff --git a/litellm-rust/AGENTS.md b/litellm-rust/AGENTS.md
index 36a5ad5a8f4..b8b6291283d 100644
--- a/litellm-rust/AGENTS.md
+++ b/litellm-rust/AGENTS.md
@@ -1,6 +1,6 @@
 # AGENTS.md
 
-litellm-rust has exactly THREE crates. A crate is a LAYER, not a route. Routes (ocr, realtime, chat) and providers (mistral, openai) are MODULES inside the layers.
+litellm-rust has four crates. A crate is a layer or shared foundation, not a route. Routes (ocr, realtime, chat) and providers (mistral, openai) are modules inside the layers.
 
 ## Crates
 
@@ -8,9 +8,10 @@ litellm-rust has exactly THREE crates. A crate is a LAYER, not a route. Routes (
 |-------|------|
 | litellm-core | The LiteLLM SDK in Rust. One public entrypoint per top-level call (`messages::messages()`), owning types, transforms, provider resolution, auth, and the provider HTTP call. Call it, get a typed response. |
 | litellm-ai-gateway | The axum server (behind the `server` feature) plus the WebSocket hosts. Translates HTTP/WS to core entrypoints; owns no provider logic and no handlers. |
-| litellm-python-bridge | PyO3 cdylib exposing Rust to the litellm Python SDK — marshals Python objects and calls core entrypoints. |
+| litellm-python-interop | Domain-neutral PyO3 foundation for GIL handling and typed Python/Serde conversion. |
+| litellm-python-bridge | PyO3 cdylib exposing LiteLLM Rust APIs to the Python SDK. Owns API registration, domain wiring, and Python exception mapping. |
 
-Dependency direction (acyclic): litellm-core ← litellm-ai-gateway ← litellm-python-bridge.
+Dependency direction is acyclic: `litellm-python-bridge` depends on the domain layers and `litellm-python-interop`; the interop foundation depends on no LiteLLM domain crate.
 
 ## Where a route lives
 
@@ -28,7 +29,7 @@ core/src/messages/
 
 Handlers never live in `ai-gateway`. `ocr`, `audio_transcription`, and `realtime` are still hosted there from before this rule; they move to `core` as they are touched.
 
-Adding a crate: default to a MODULE. New crate ONLY on a real trigger — separate artifact (binary/cdylib), proc-macro, shared foundation, or publishable standalone. A new provider or route is none of these.
+Adding a crate: default to a module. A new crate requires a real trigger: separate artifact (binary/cdylib), proc-macro, shared foundation, or publishable standalone. A new provider or route is none of these.
 
 Adding a crate fails crates/core/tests/workspace_crate_allowlist.rs until you update its allowlist and this file — intentional.
 
diff --git a/litellm-rust/CLAUDE.md b/litellm-rust/CLAUDE.md
index fe6ceedbb86..3dcf1853efc 100644
--- a/litellm-rust/CLAUDE.md
+++ b/litellm-rust/CLAUDE.md
@@ -21,12 +21,13 @@ variants of it. The test for a good abstraction is that adding the next provider
 is a few declarative lines, not a new file of duplicated flow. Only diverge from
 the base when behavior is genuinely different, and say so explicitly in the PR.
 
-## Crates (exactly three — see AGENTS.md)
+## Crates (see AGENTS.md)
 
 `litellm-core` **is** the LiteLLM SDK in Rust: it makes the LLM call.
 `litellm-ai-gateway` is an HTTP/WebSocket server in front of it, and
-`litellm-python-bridge` exposes it to the Python SDK. A crate is a **layer**, not
-a route — add modules, not crates.
+`litellm-python-bridge` exposes it to the Python SDK. `litellm-python-interop`
+holds domain-neutral PyO3 primitives shared by Python-facing Rust code. A crate
+is a layer or shared foundation, not a route; add modules, not crates.
 
 ## Core Boundary
 
@@ -175,7 +176,7 @@ cd litellm-rust
 cargo fmt --check
 # the ai-gateway binary + server code is behind the `server` feature
 cargo clippy -p litellm-ai-gateway --all-targets --features server -- -D warnings
-cargo clippy -p litellm-core -p litellm-python-bridge --all-targets -- -D warnings
+cargo clippy -p litellm-core -p litellm-python-interop -p litellm-python-bridge --all-targets -- -D warnings
 cargo test --workspace
 ```
 
diff --git a/litellm-rust/Cargo.lock b/litellm-rust/Cargo.lock
index 4388e561026..dd41cf0e84b 100644
--- a/litellm-rust/Cargo.lock
+++ b/litellm-rust/Cargo.lock
@@ -919,6 +919,12 @@ version = "0.3.33"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b231ed28831efb4a61a08580c4bc233ec56bc009f4cd8f52da2c3cb97df0c109"
 
+[[package]]
+name = "futures-timer"
+version = "3.0.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "af43fadb8a98512d547e37b4e92e0ced13e205c061b87b4623eff01d918d6968"
+
 [[package]]
 name = "futures-util"
 version = "0.3.33"
@@ -972,6 +978,12 @@ dependencies = [
  "wasm-bindgen",
 ]
 
+[[package]]
+name = "glob"
+version = "0.3.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e4eba85ea1d0a966a983acd07deee566e67395d2d96b6fb39e62b5a833f1eb0b"
+
 [[package]]
 name = "h2"
 version = "0.3.27"
@@ -1432,14 +1444,24 @@ dependencies = [
  "criterion",
  "litellm-ai-gateway",
  "litellm-core",
+ "litellm-python-interop",
  "pyo3",
  "pyo3-async-runtimes",
- "pythonize",
- "serde",
  "serde_json",
  "tokio",
 ]
 
+[[package]]
+name = "litellm-python-interop"
+version = "0.1.0"
+dependencies = [
+ "pyo3",
+ "pythonize",
+ "rstest",
+ "serde",
+ "serde_json",
+]
+
 [[package]]
 name = "litemap"
 version = "0.8.2"
@@ -1627,6 +1649,15 @@ dependencies = [
  "zerocopy",
 ]
 
+[[package]]
+name = "proc-macro-crate"
+version = "3.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e67ba7e9b2b56446f1d419b1d807906278ffa1a658a8a5d8a39dcb1f5a78614f"
+dependencies = [
+ "toml_edit",
+]
+
 [[package]]
 name = "proc-macro2"
 version = "1.0.107"
@@ -1899,6 +1930,12 @@ version = "0.8.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d6f6ff9a378485b298a5286656da665ba74413d36db0979633275d2e708145d4"
 
+[[package]]
+name = "relative-path"
+version = "1.9.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ba39f3699c378cd8970968dcbff9c43159ea4cfbd88d43c00b22f2ef10a435d2"
+
 [[package]]
 name = "reqwest"
 version = "0.12.28"
@@ -1956,6 +1993,35 @@ dependencies = [
  "windows-sys 0.52.0",
 ]
 
+[[package]]
+name = "rstest"
+version = "0.26.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f5a3193c063baaa2a95a33f03035c8a72b83d97a54916055ba22d35ed3839d49"
+dependencies = [
+ "futures-timer",
+ "futures-util",
+ "rstest_macros",
+]
+
+[[package]]
+name = "rstest_macros"
+version = "0.26.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9c845311f0ff7951c5506121a9ad75aec44d083c31583b2ea5a30bcb0b0abba0"
+dependencies = [
+ "cfg-if",
+ "glob",
+ "proc-macro-crate",
+ "proc-macro2",
+ "quote",
+ "regex",
+ "relative-path",
+ "rustc_version",
+ "syn 2.0.119",
+ "unicode-ident",
+]
+
 [[package]]
 name = "rustc-hash"
 version = "2.1.3"
@@ -2488,6 +2554,36 @@ dependencies = [
  "tokio",
 ]
 
+[[package]]
+name = "toml_datetime"
+version = "1.1.1+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3165f65f62e28e0115a00b2ebdd37eb6f3b641855f9d636d3cd4103767159ad7"
+dependencies = [
+ "serde_core",
+]
+
+[[package]]
+name = "toml_edit"
+version = "0.25.13+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6975367e4d2ef766d86af01ffad14b622fecc8d4357a998fbc4deb6e9bacaf9b"
+dependencies = [
+ "indexmap",
+ "toml_datetime",
+ "toml_parser",
+ "winnow",
+]
+
+[[package]]
+name = "toml_parser"
+version = "1.1.3+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "1d38ac1cf9b95face32296c0a3ede1fdc270627c9d9c02a7274dd6d960dc4d56"
+dependencies = [
+ "winnow",
+]
+
 [[package]]
 name = "tower"
 version = "0.5.3"
@@ -2903,6 +2999,15 @@ version = "0.52.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"
 
+[[package]]
+name = "winnow"
+version = "1.0.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "23b97319f7b8343df12cc98938e5c3eb436064524c8d2b4e30a1d3a36eecdf81"
+dependencies = [
+ "memchr",
+]
+
 [[package]]
 name = "writeable"
 version = "0.6.3"
diff --git a/litellm-rust/Cargo.toml b/litellm-rust/Cargo.toml
index c17a0605fc7..c447d915abe 100644
--- a/litellm-rust/Cargo.toml
+++ b/litellm-rust/Cargo.toml
@@ -2,6 +2,7 @@
 members = [
     "crates/core",
     "crates/ai-gateway",
+    "crates/python-interop",
     "crates/python-bridge",
 ]
 resolver = "2"
@@ -15,12 +16,14 @@ repository = "https://github.com/BerriAI/litellm"
 [workspace.dependencies]
 litellm-core = { path = "crates/core" }
 litellm-ai-gateway = { path = "crates/ai-gateway", default-features = false }
+litellm-python-interop = { path = "crates/python-interop" }
 axum = "0.7"
 pyo3 = "0.29.0"
 pyo3-async-runtimes = { version = "0.29.0", features = ["tokio-runtime"] }
 pythonize = "0.29.0"
 rand = "0.8"
 reqwest = { version = "0.12", default-features = false, features = ["blocking", "json", "rustls-tls", "http2", "stream"] }
+rstest = "0.26.1"
 serde = { version = "1.0", features = ["derive"] }
 serde_json = "1.0"
 sha2 = "0.10"
diff --git a/litellm-rust/README.md b/litellm-rust/README.md
index bcccf93300b..a0d79c6f0a5 100644
--- a/litellm-rust/README.md
+++ b/litellm-rust/README.md
@@ -26,9 +26,10 @@ coverage and production evidence.
 |-------|------|
 | litellm-core | The SDK. Per-route entrypoints (`messages::messages()`), types, provider transforms (modules under `providers/`), provider resolution, auth, the provider HTTP call, and the router. |
 | litellm-ai-gateway | The axum server (behind the `server` feature) and WebSocket hosts. Translates HTTP/WS to core entrypoints; no provider handlers. |
-| litellm-python-bridge | PyO3 cdylib exposing Rust to the litellm Python SDK — marshals Python objects and calls core entrypoints. |
+| litellm-python-interop | Domain-neutral PyO3 foundation for GIL handling and typed Python/Serde conversion. |
+| litellm-python-bridge | PyO3 cdylib exposing LiteLLM Rust APIs to the Python SDK. Owns API registration, domain wiring, and Python exception mapping. |
 
-Dependency direction (acyclic): litellm-core ← litellm-ai-gateway ← litellm-python-bridge.
+Dependency direction is acyclic: `litellm-python-bridge` depends on the domain layers and `litellm-python-interop`; the interop foundation depends on no LiteLLM domain crate.
 
 ## Layout
 
@@ -38,7 +39,8 @@ crates/
     src/messages/   mod.rs (entrypoint), types, transformation, prepare, handler, client
     src/providers/anthropic/messages/transformation.rs
   ai-gateway/     Axum server + WebSocket hosts; calls core entrypoints.
-  python-bridge/  PyO3 bridge for Python LiteLLM.
+  python-interop/ Domain-neutral PyO3 conversion and GIL primitives.
+  python-bridge/  PyO3 API adapter for Python LiteLLM.
 ```
 
 The folder shape follows the Python provider tree:
diff --git a/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md b/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md
index a1860d8a9c9..4a689cb9579 100644
--- a/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md
+++ b/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md
@@ -54,6 +54,6 @@ Rules for adding or changing an LLM provider/route in `litellm-rust`. `messages`
     cd litellm-rust
     cargo fmt --check
     cargo clippy -p litellm-ai-gateway --all-targets --features server -- -D warnings
-    cargo clippy -p litellm-core -p litellm-python-bridge --all-targets -- -D warnings
+    cargo clippy -p litellm-core -p litellm-python-interop -p litellm-python-bridge --all-targets -- -D warnings
     cargo test --workspace
     ```
diff --git a/litellm-rust/crates/ai-gateway/README.md b/litellm-rust/crates/ai-gateway/README.md
index 7a6c620ee84..5cbb47220be 100644
--- a/litellm-rust/crates/ai-gateway/README.md
+++ b/litellm-rust/crates/ai-gateway/README.md
@@ -6,15 +6,16 @@ dials OpenAI upstream, and splices the two sockets frame-by-frame.
 
 ## Crates
 
-`litellm-rust` is exactly three crates (a crate is a **layer**, not a route):
+`litellm-rust` has four crates. A crate is a layer or shared foundation, not a route:
 
 | Crate | Role |
 |-------|------|
 | litellm-core | The LiteLLM SDK in Rust — per-route entrypoints (`messages::messages()`) that resolve the provider, transform, and make the call; plus types, provider transforms, and the router. |
 | litellm-ai-gateway | The Axum server (behind the `server` feature) and WebSocket hosts. Translates HTTP/WS to core entrypoints; no provider handlers. |
-| litellm-python-bridge | PyO3 cdylib exposing Rust to the litellm Python SDK — marshals Python objects and calls core entrypoints. |
+| litellm-python-interop | Domain-neutral PyO3 foundation for GIL handling and typed Python/Serde conversion. |
+| litellm-python-bridge | PyO3 cdylib exposing LiteLLM Rust APIs to the Python SDK. |
 
-Dependency direction (acyclic): litellm-core ← litellm-ai-gateway ← litellm-python-bridge.
+Dependency direction is acyclic: `litellm-python-bridge` depends on the domain layers and `litellm-python-interop`; the interop foundation depends on no LiteLLM domain crate.
 
 - **Client endpoint:** `wss://<host>/v1/realtime?model=<model>` (WebSocket)
 - **Auth:** `Authorization: Bearer $LITELLM_MASTER_KEY` (fails closed if unset)
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/common_utils.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/common_utils.rs
index 270d5c2d97a..140bc8aeea8 100644
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/common_utils.rs
+++ b/litellm-rust/crates/ai-gateway/src/audio_transcription/common_utils.rs
@@ -1,10 +1,8 @@
-use std::collections::BTreeMap;
-
-use litellm_core::CoreResult;
 use litellm_core::audio_transcription::transformation::AudioTranscriptionProviderConfig;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::providers::bedrock::audio_transcription::BEDROCK_AUDIO_TRANSCRIPTION_CONFIG;
 use serde_json::{Map, Value};
+use std::collections::BTreeMap;
 
 pub(super) fn audio_transcription_provider_config(
     provider: &str,
@@ -17,7 +15,7 @@ pub(super) fn audio_transcription_provider_config(
 
 pub(super) fn string_headers(
     headers: Option<Map<String, Value>>,
-) -> CoreResult<BTreeMap<String, String>> {
+) -> Result<BTreeMap<String, String>, Error> {
     headers
         .unwrap_or_default()
         .into_iter()
@@ -26,7 +24,7 @@ pub(super) fn string_headers(
                 .as_str()
                 .map(|value| (key.clone(), value.to_string()))
                 .ok_or_else(|| {
-                    CoreError::InvalidRequest(format!(
+                    Error::InvalidRequest(format!(
                         "audio transcription extra_headers.{key} must be a string"
                     ))
                 })
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/handler.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/handler.rs
index 33c13550f58..1bdd4ae72a2 100644
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/handler.rs
+++ b/litellm-rust/crates/ai-gateway/src/audio_transcription/handler.rs
@@ -1,11 +1,9 @@
-use std::time::SystemTime;
-
-use litellm_core::CoreResult;
 use litellm_core::audio_transcription::transformation::AudioTranscriptionAuth;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::providers::bedrock::audio_transcription::aws_auth_config;
 use litellm_core::providers::bedrock::aws_base::{resolve_credentials, sign_bedrock_post};
 use serde_json::Value;
+use std::time::SystemTime;
 
 use super::common_utils::truncate_error_body;
 use super::types::ProviderAudioTranscriptionRequest;
@@ -13,10 +11,9 @@ use crate::client::http_client;
 
 pub(crate) async fn execute_audio_transcription_provider_call(
     request: ProviderAudioTranscriptionRequest,
-) -> CoreResult<Value> {
-    let body = serde_json::to_vec(&request.body).map_err(|error| {
-        CoreError::InvalidRequest(format!("invalid audio request body: {error}"))
-    })?;
+) -> Result<Value, Error> {
+    let body = serde_json::to_vec(&request.body)
+        .map_err(|error| Error::InvalidRequest(format!("invalid audio request body: {error}")))?;
     let mut request_builder = http_client().post(&request.url).body(body.clone());
     for (key, value) in &request.upstream_headers {
         request_builder = request_builder.header(key, value);
@@ -27,21 +24,20 @@ pub(crate) async fn execute_audio_transcription_provider_call(
     let response = request_builder
         .send()
         .await
-        .map_err(|error| CoreError::Network(error.to_string()))?;
+        .map_err(|error| Error::Network(error.to_string()))?;
     let status = response.status();
     let text = response
         .text()
         .await
-        .map_err(|error| CoreError::Network(error.to_string()))?;
+        .map_err(|error| Error::Network(error.to_string()))?;
     if !status.is_success() {
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
     }
-    let response_json: Value = serde_json::from_str(&text).map_err(|error| {
-        CoreError::InvalidResponse(format!("invalid audio response JSON: {error}"))
-    })?;
+    let response_json: Value = serde_json::from_str(&text)
+        .map_err(|error| Error::InvalidResponse(format!("invalid audio response JSON: {error}")))?;
     Ok(request
         .config
         .transform_transcription_response(&request.model, response_json)?
@@ -51,14 +47,13 @@ pub(crate) async fn execute_audio_transcription_provider_call(
 pub(crate) async fn sign_request(
     request: &ProviderAudioTranscriptionRequest,
     optional_params: &serde_json::Map<String, Value>,
-) -> CoreResult<ProviderAudioTranscriptionRequest> {
+) -> Result<ProviderAudioTranscriptionRequest, Error> {
     let env_lookup = environment_lookup;
     let auth = request
         .config
         .auth_strategy(&request.model, optional_params, &env_lookup)?;
-    let body = serde_json::to_vec(&request.body).map_err(|error| {
-        CoreError::InvalidRequest(format!("invalid audio request body: {error}"))
-    })?;
+    let body = serde_json::to_vec(&request.body)
+        .map_err(|error| Error::InvalidRequest(format!("invalid audio request body: {error}")))?;
     let mut headers = super::common_utils::string_headers(None)?;
     headers.insert("Content-Type".to_string(), "application/json".to_string());
     headers.extend(request.upstream_headers.iter().cloned());
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs
index 0c9faeda6e7..5e1240de759 100644
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs
+++ b/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs
@@ -1,11 +1,9 @@
-use std::future::Future;
-use std::pin::Pin;
-
-use litellm_core::CoreResult;
 use litellm_core::audio_transcription::transformation::AudioTranscriptionAuth;
 use litellm_core::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use serde_json::{Map, Value, json};
+use std::future::Future;
+use std::pin::Pin;
 
 use super::common_utils::{audio_transcription_provider_config, has_header, string_headers};
 use super::handler::sign_request;
@@ -26,7 +24,7 @@ pub(crate) struct AudioTranscriptionLifecycleHooks {
     request_metadata: RequestMetadata,
 }
 
-type AudioFuture<'a, T> = Pin<Box<dyn Future<Output = CoreResult<T>> + Send + 'a>>;
+type AudioFuture<'a, T> = Pin<Box<dyn Future<Output = Result<T, Error>> + Send + 'a>>;
 type AudioLogFuture<'a> = Pin<Box<dyn Future<Output = ()> + Send + 'a>>;
 
 impl AudioTranscriptionLifecycleHooks {
@@ -45,7 +43,7 @@ impl AudioTranscriptionLifecycleHooks {
     async fn run_pre_call_guardrails(
         &self,
         request: PreparedAudioTranscriptionRequest,
-    ) -> CoreResult<PreparedAudioTranscriptionRequest> {
+    ) -> Result<PreparedAudioTranscriptionRequest, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(request);
         }
@@ -63,17 +61,17 @@ impl AudioTranscriptionLifecycleHooks {
             .await
             .map_err(guardrail_error_to_core_error)?;
         let Value::Object(mut data) = guardrail_request.data else {
-            return Err(CoreError::InvalidRequest(
+            return Err(Error::InvalidRequest(
                 "audio transcription pre_call guardrail must return an object".to_string(),
             ));
         };
         let audio = data.remove("audio").ok_or_else(|| {
-            CoreError::InvalidRequest("audio transcription guardrail removed audio".to_string())
+            Error::InvalidRequest("audio transcription guardrail removed audio".to_string())
         })?;
         let optional_params = match data.remove("optional_params") {
             Some(Value::Object(value)) => value,
             Some(_) => {
-                return Err(CoreError::InvalidRequest(
+                return Err(Error::InvalidRequest(
                     "audio transcription optional_params must be an object".to_string(),
                 ));
             }
@@ -89,9 +87,9 @@ impl AudioTranscriptionLifecycleHooks {
     async fn prepare_provider_request(
         &self,
         request: PreparedAudioTranscriptionRequest,
-    ) -> CoreResult<ProviderAudioTranscriptionRequest> {
+    ) -> Result<ProviderAudioTranscriptionRequest, Error> {
         let config = audio_transcription_provider_config(&request.custom_llm_provider)
-            .ok_or_else(|| CoreError::InvalidProvider(request.custom_llm_provider.clone()))?;
+            .ok_or_else(|| Error::InvalidProvider(request.custom_llm_provider.clone()))?;
         let env_lookup = super::handler::environment_lookup;
         let headers = string_headers(request.extra_headers)?;
         let url = config.complete_url(
@@ -135,7 +133,7 @@ impl AudioTranscriptionLifecycleHooks {
     async fn run_during_call_guardrails(
         &self,
         request: ProviderAudioTranscriptionRequest,
-    ) -> CoreResult<ProviderAudioTranscriptionRequest> {
+    ) -> Result<ProviderAudioTranscriptionRequest, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(request);
         }
@@ -153,12 +151,12 @@ impl AudioTranscriptionLifecycleHooks {
             .await
             .map_err(guardrail_error_to_core_error)?;
         let Value::Object(mut data) = guardrail_request.data else {
-            return Err(CoreError::InvalidRequest(
+            return Err(Error::InvalidRequest(
                 "audio transcription during_call guardrail must return an object".to_string(),
             ));
         };
         let body = data.remove("body").ok_or_else(|| {
-            CoreError::InvalidRequest("audio transcription guardrail removed body".to_string())
+            Error::InvalidRequest("audio transcription guardrail removed body".to_string())
         })?;
         Ok(ProviderAudioTranscriptionRequest { body, ..request })
     }
@@ -241,7 +239,7 @@ impl CallLifecycleHooks<PreparedAudioTranscriptionRequest, ProviderAudioTranscri
     fn async_log_failure_event<'a>(
         &'a self,
         context: &'a CallLifecycleContext,
-        error: &'a CoreError,
+        error: &'a Error,
         timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a> {
         Box::pin(async move {
@@ -281,22 +279,22 @@ fn guardrail_context(metadata: &RequestMetadata) -> GuardrailContext {
     }
 }
 
-fn guardrail_error_to_core_error(error: GuardrailError) -> CoreError {
-    CoreError::InvalidRequest(format!("{}: {}", error.kind, error.message))
+fn guardrail_error_to_core_error(error: GuardrailError) -> Error {
+    Error::InvalidRequest(format!("{}: {}", error.kind, error.message))
 }
 
-fn core_error_kind(error: &CoreError) -> &'static str {
+fn core_error_kind(error: &Error) -> &'static str {
     match error {
-        CoreError::Auth(_) => "AuthError",
-        CoreError::InvalidProvider(_) => "InvalidProvider",
-        CoreError::InvalidRequest(_) => "InvalidRequest",
-        CoreError::InvalidType { .. } => "InvalidType",
-        CoreError::MissingField(_) => "MissingField",
-        CoreError::Http { .. } => "HttpError",
-        CoreError::InvalidResponse(_) => "InvalidResponse",
-        CoreError::Network(_) => "NetworkError",
-        CoreError::Connect(_) => "ConnectError",
-        CoreError::Routing(_) => "RoutingError",
-        CoreError::Unsupported(_) => "UnsupportedRequest",
+        Error::Auth(_) => "AuthError",
+        Error::InvalidProvider(_) => "InvalidProvider",
+        Error::InvalidRequest(_) => "InvalidRequest",
+        Error::InvalidType { .. } => "InvalidType",
+        Error::MissingField(_) => "MissingField",
+        Error::Http { .. } => "HttpError",
+        Error::InvalidResponse(_) => "InvalidResponse",
+        Error::Network(_) => "NetworkError",
+        Error::Connect(_) => "ConnectError",
+        Error::Routing(_) => "RoutingError",
+        Error::Unsupported(_) => "UnsupportedRequest",
     }
 }
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs
index 5d33d912c40..3983846d7b6 100644
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs
+++ b/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs
@@ -1,4 +1,4 @@
-use litellm_core::CoreResult;
+use litellm_core::Error;
 use litellm_core::call_lifecycle::CallLifecycle;
 use serde_json::Value;
 
@@ -13,7 +13,7 @@ pub use types::AudioTranscriptionRequest;
 use handler::execute_audio_transcription_provider_call;
 use prepare::{PreparedAudioTranscriptionCall, prepare_audio_transcription_call};
 
-pub async fn audio_transcription(request: AudioTranscriptionRequest<'_>) -> CoreResult<Value> {
+pub async fn audio_transcription(request: AudioTranscriptionRequest<'_>) -> Result<Value, Error> {
     let PreparedAudioTranscriptionCall { request, hooks } =
         prepare_audio_transcription_call(request);
     CallLifecycle::default()
diff --git a/litellm-rust/crates/ai-gateway/src/io/realtime.rs b/litellm-rust/crates/ai-gateway/src/io/realtime.rs
index 845e7bf9527..662f7328982 100644
--- a/litellm-rust/crates/ai-gateway/src/io/realtime.rs
+++ b/litellm-rust/crates/ai-gateway/src/io/realtime.rs
@@ -15,8 +15,7 @@ use std::time::Duration;
 
 use futures_util::stream::{SplitSink, SplitStream};
 use futures_util::{Sink, SinkExt, Stream, StreamExt};
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::realtime::transformation::RealtimeProviderConfig;
 use litellm_core::realtime::types::RealtimeEvent;
 use tokio::net::TcpStream;
@@ -48,7 +47,7 @@ pub(crate) type UpstreamRx = SplitStream<UpstreamWs>;
 /// Resolve the OpenAI API key from the explicit param or the environment.
 ///
 /// Blank/whitespace values are treated as absent (guard at resolution time).
-pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
+pub(crate) fn resolve_api_key(api_key: Option<&str>) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|key| !key.is_empty())
@@ -58,7 +57,7 @@ pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
                 .ok()
                 .filter(|key| !key.trim().is_empty())
         })
-        .ok_or_else(|| CoreError::Auth(MISSING_KEY_MESSAGE.to_string()))
+        .ok_or_else(|| Error::Auth(MISSING_KEY_MESSAGE.to_string()))
 }
 
 /// Open the upstream WebSocket to OpenAI for `(model, api_key, api_base)`.
@@ -70,24 +69,24 @@ pub(crate) async fn dial_upstream(
     model: &str,
     api_key: &str,
     api_base: Option<&str>,
-) -> CoreResult<UpstreamWs> {
+) -> Result<UpstreamWs, Error> {
     let url = OPENAI_REALTIME_CONFIG.complete_url(api_base, model);
 
     let mut request = url
         .as_str()
         .into_client_request()
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     // GA realtime: only Authorization. The legacy OpenAI-Beta header triggers
     // beta_api_shape_disabled, so we do not send it.
     request.headers_mut().insert(
         AUTHORIZATION,
         HeaderValue::from_str(&format!("Bearer {api_key}"))
-            .map_err(|err| CoreError::Auth(err.to_string()))?,
+            .map_err(|err| Error::Auth(err.to_string()))?,
     );
 
     let (upstream, _response) = connect_async(request)
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     Ok(upstream)
 }
 
@@ -96,22 +95,22 @@ pub(crate) async fn dial_upstream(
 /// Used by the pool to pre-read OpenAI's unprompted `session.created`. Returns an
 /// error on a non-text frame, a closed socket, or undecodable JSON so the pool can
 /// discard a misbehaving socket rather than warm it.
-pub(crate) async fn read_event(upstream_rx: &mut UpstreamRx) -> CoreResult<RealtimeEvent> {
+pub(crate) async fn read_event(upstream_rx: &mut UpstreamRx) -> Result<RealtimeEvent, Error> {
     loop {
         let message = upstream_rx
             .next()
             .await
-            .ok_or_else(|| CoreError::Network("upstream closed before first event".to_string()))?
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .ok_or_else(|| Error::Network("upstream closed before first event".to_string()))?
+            .map_err(|err| Error::Network(err.to_string()))?;
         match message {
             Message::Text(text) => {
                 return serde_json::from_str(&text)
-                    .map_err(|err| CoreError::InvalidResponse(err.to_string()));
+                    .map_err(|err| Error::InvalidResponse(err.to_string()));
             }
             // Ignore protocol frames (ping/pong) while waiting for the first event.
             Message::Ping(_) | Message::Pong(_) => continue,
             Message::Close(_) => {
-                return Err(CoreError::Network(
+                return Err(Error::Network(
                     "upstream closed before first event".to_string(),
                 ));
             }
@@ -139,7 +138,7 @@ pub(crate) async fn splice<In, Out>(
     mut observe: impl FnMut(&RealtimeEvent) + Send,
     mut client_in: In,
     mut client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
@@ -154,7 +153,7 @@ where
             client_out
                 .send(outbound)
                 .await
-                .map_err(|err| CoreError::Network(err.to_string()))?;
+                .map_err(|err| Error::Network(err.to_string()))?;
         }
     }
 
@@ -175,26 +174,26 @@ where
                 // inflate its own spend log. Logging observes upstream events only.
                 for outbound in config.transform_realtime_request(&event, model)?.events {
                     let payload = serde_json::to_string(&outbound)
-                        .map_err(|err| CoreError::InvalidResponse(err.to_string()))?;
+                        .map_err(|err| Error::InvalidResponse(err.to_string()))?;
                     upstream_tx
                         .send(Message::Text(payload))
                         .await
-                        .map_err(|err| CoreError::Network(err.to_string()))?;
+                        .map_err(|err| Error::Network(err.to_string()))?;
                 }
             }
             // upstream -> client
             upstream_message = upstream_rx.next() => {
                 let Some(message) = upstream_message else { break }; // upstream closed
-                match message.map_err(|err| CoreError::Network(err.to_string()))? {
+                match message.map_err(|err| Error::Network(err.to_string()))? {
                     Message::Text(text) => {
                         let event: RealtimeEvent = serde_json::from_str(&text)
-                            .map_err(|err| CoreError::InvalidResponse(err.to_string()))?;
+                            .map_err(|err| Error::InvalidResponse(err.to_string()))?;
                         observe(&event);
                         for outbound in config.transform_realtime_response(&event, model)?.events {
                             client_out
                                 .send(outbound)
                                 .await
-                                .map_err(|err| CoreError::Network(err.to_string()))?;
+                                .map_err(|err| Error::Network(err.to_string()))?;
                         }
                     }
                     Message::Close(_) => break,
@@ -225,7 +224,7 @@ pub async fn realtime<In, Out>(
     observe: impl FnMut(&RealtimeEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
@@ -258,7 +257,7 @@ pub async fn realtime_warm<In, Out>(
     observe: impl FnMut(&RealtimeEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
diff --git a/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs b/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs
index 4a1a3cd1166..49e9c459a88 100644
--- a/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs
+++ b/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs
@@ -28,7 +28,7 @@ use std::sync::{Arc, Mutex};
 use std::time::{Duration, Instant};
 
 use futures_util::StreamExt;
-use litellm_core::CoreResult;
+use litellm_core::Error;
 use litellm_core::realtime::types::RealtimeEvent;
 
 use crate::io::realtime::{
@@ -438,7 +438,7 @@ impl RealtimePool {
 ///
 /// `key.api_key` is already resolved (non-blank). The first frame OpenAI sends
 /// unprompted is `session.created`; we buffer exactly that and read nothing more.
-async fn warm_one(key: &UpstreamKey) -> CoreResult<WarmConnection> {
+async fn warm_one(key: &UpstreamKey) -> Result<WarmConnection, Error> {
     let upstream: UpstreamWs =
         dial_upstream(&key.model, &key.api_key, key.api_base.as_deref()).await?;
     let (tx, mut rx) = upstream.split();
diff --git a/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs b/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs
index 9b51019f4bc..0b01747b1a5 100644
--- a/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs
+++ b/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs
@@ -4,10 +4,10 @@ use std::time::Duration;
 
 use futures_util::stream::{SplitSink, SplitStream};
 use futures_util::{Sink, SinkExt, Stream, StreamExt};
+use litellm_core::Error;
 use litellm_core::providers::openai::responses::transformation::OPENAI_RESPONSES_WS_CONFIG;
 use litellm_core::responses::types::ResponsesWsEvent;
 use litellm_core::responses::websocket::ResponsesWebSocketProviderConfig;
-use litellm_core::{CoreError, CoreResult};
 use tokio::net::TcpStream;
 use tokio::sync::Mutex;
 use tokio_tungstenite::tungstenite::Message;
@@ -37,51 +37,49 @@ impl ResponsesWebSocketConnection {
         url: &str,
         headers: &HashMap<String, String>,
         timeout: Option<Duration>,
-    ) -> CoreResult<Self> {
+    ) -> Result<Self, Error> {
         let mut request = url
             .into_client_request()
-            .map_err(|error| CoreError::Network(error.to_string()))?;
+            .map_err(|error| Error::Network(error.to_string()))?;
         for (name, value) in headers {
             let header_name = name
                 .parse::<HeaderName>()
-                .map_err(|error| CoreError::InvalidRequest(error.to_string()))?;
+                .map_err(|error| Error::InvalidRequest(error.to_string()))?;
             let header_value = HeaderValue::from_str(value)
-                .map_err(|error| CoreError::InvalidRequest(error.to_string()))?;
+                .map_err(|error| Error::InvalidRequest(error.to_string()))?;
             request.headers_mut().insert(header_name, header_value);
         }
         let connect = connect_async(request);
         let result = match timeout {
             Some(timeout) => tokio::time::timeout(timeout, connect).await.map_err(|_| {
-                CoreError::Network("Responses WebSocket connection timed out".to_string())
+                Error::Network("Responses WebSocket connection timed out".to_string())
             })?,
             None => connect.await,
         };
         let (socket, _) = result.map_err(|error| match error {
-            tokio_tungstenite::tungstenite::Error::Http(response) => CoreError::Http {
+            tokio_tungstenite::tungstenite::Error::Http(response) => Error::Http {
                 status: response.status().as_u16(),
                 body: String::new(),
             },
-            other => CoreError::Network(other.to_string()),
+            other => Error::Network(other.to_string()),
         })?;
         Ok(Self {
             socket: Arc::new(Mutex::new(Some(socket))),
         })
     }
 
-    pub async fn send_text(&self, text: String) -> CoreResult<()> {
+    pub async fn send_text(&self, text: String) -> Result<(), Error> {
         let mut socket = self.socket.lock().await;
         let Some(socket) = socket.as_mut() else {
-            return Err(CoreError::Network(
-                "Responses WebSocket is closed".to_string(),
-            ));
+            return Err(Error::Network("Responses WebSocket is closed".to_string()));
         };
         socket
             .send(Message::Text(text))
             .await
-            .map_err(|error| CoreError::Network(error.to_string()))
+            .map_err(|error| Error::Network(error.to_string()))
     }
 
-    pub async fn recv_text(&self) -> CoreResult<Option<String>> {
+    pub async fn recv_text(&self) -> Result<Option<String>, Error> {
         let mut socket_guard = self.socket.lock().await;
         let Some(socket) = socket_guard.as_mut() else {
             return Ok(None);
@@ -90,27 +88,27 @@ impl ResponsesWebSocketConnection {
             Some(Ok(Message::Text(text))) => Ok(Some(text)),
             Some(Ok(Message::Binary(bytes))) => String::from_utf8(bytes.to_vec())
                 .map(Some)
-                .map_err(|error| CoreError::InvalidResponse(error.to_string())),
+                .map_err(|error| Error::InvalidResponse(error.to_string())),
             Some(Ok(Message::Close(_))) | None => Ok(None),
             Some(Ok(_)) => Ok(None),
-            Some(Err(error)) => Err(CoreError::Network(error.to_string())),
+            Some(Err(error)) => Err(Error::Network(error.to_string())),
         }
     }
 
-    pub async fn close(&self) -> CoreResult<()> {
+    pub async fn close(&self) -> Result<(), Error> {
         let mut socket = self.socket.lock().await;
         if let Some(socket) = socket.as_mut() {
             socket
                 .close(None)
                 .await
-                .map_err(|error| CoreError::Network(error.to_string()))?;
+                .map_err(|error| Error::Network(error.to_string()))?;
         }
         *socket = None;
         Ok(())
     }
 }
 
-pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
+pub(crate) fn resolve_api_key(api_key: Option<&str>) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|value| !value.is_empty())
@@ -120,38 +118,38 @@ pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
                 .ok()
                 .filter(|value| !value.trim().is_empty())
         })
-        .ok_or_else(|| CoreError::Auth(MISSING_KEY_MESSAGE.to_string()))
+        .ok_or_else(|| Error::Auth(MISSING_KEY_MESSAGE.to_string()))
 }
 
 async fn dial_upstream(
     model: &str,
     api_key: &str,
     api_base: Option<&str>,
-) -> CoreResult<ResponsesUpstreamWs> {
+) -> Result<ResponsesUpstreamWs, Error> {
     let url = OPENAI_RESPONSES_WS_CONFIG.complete_websocket_url(api_base, model);
     let mut request = url
         .as_str()
         .into_client_request()
-        .map_err(|error| CoreError::Network(error.to_string()))?;
+        .map_err(|error| Error::Network(error.to_string()))?;
     request.headers_mut().insert(
         AUTHORIZATION,
         HeaderValue::from_str(&format!("Bearer {api_key}"))
-            .map_err(|error| CoreError::Auth(error.to_string()))?,
+            .map_err(|error| Error::Auth(error.to_string()))?,
     );
     let result = tokio::time::timeout(
         Duration::from_secs(DEFAULT_RESPONSES_WS_CONNECT_TIMEOUT_SECS),
         connect_async(request),
     )
     .await
-    .map_err(|_| CoreError::Network("Responses WebSocket connection timed out".to_string()))?;
+    .map_err(|_| Error::Network("Responses WebSocket connection timed out".to_string()))?;
     result
         .map(|(socket, _)| socket)
         .map_err(|error| match error {
-            tokio_tungstenite::tungstenite::Error::Http(response) => CoreError::Http {
+            tokio_tungstenite::tungstenite::Error::Http(response) => Error::Http {
                 status: response.status().as_u16(),
                 body: String::new(),
             },
-            other => CoreError::Network(other.to_string()),
+            other => Error::Network(other.to_string()),
         })
 }
 
@@ -166,7 +164,7 @@ impl ResponsesWebSocketStreaming {
         observe: impl FnMut(&ResponsesWsEvent) + Send,
         client_in: In,
         client_out: Out,
-    ) -> CoreResult<()>
+    ) -> Result<(), Error>
     where
         In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
         Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -193,7 +191,7 @@ pub(crate) async fn splice<In, Out>(
     mut observe: impl FnMut(&ResponsesWsEvent) + Send,
     mut client_in: In,
     mut client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -210,18 +208,18 @@ where
                     .events
                 {
                     let payload = serde_json::to_string(&outbound)
-                        .map_err(|error| CoreError::InvalidResponse(error.to_string()))?;
+                        .map_err(|error| Error::InvalidResponse(error.to_string()))?;
                     upstream_tx.send(Message::Text(payload))
                         .await
-                        .map_err(|error| CoreError::Network(error.to_string()))?;
+                        .map_err(|error| Error::Network(error.to_string()))?;
                 }
             }
             message = upstream_rx.next() => {
                 let Some(message) = message else { break };
-                match message.map_err(|error| CoreError::Network(error.to_string()))? {
+                match message.map_err(|error| Error::Network(error.to_string()))? {
                     Message::Text(text) => {
                         let event = serde_json::from_str::<ResponsesWsEvent>(&text)
-                            .map_err(|error| CoreError::InvalidResponse(error.to_string()))?;
+                            .map_err(|error| Error::InvalidResponse(error.to_string()))?;
                         observe(&event);
                         for outbound in OPENAI_RESPONSES_WS_CONFIG
                             .transform_ws_response(&event, model)?
@@ -229,7 +227,7 @@ where
                         {
                             client_out.send(outbound)
                                 .await
-                                .map_err(|error| CoreError::Network(error.to_string()))?;
+                                .map_err(|error| Error::Network(error.to_string()))?;
                         }
                     }
                     Message::Close(_) => break,
@@ -252,7 +250,7 @@ pub async fn async_responses_websocket<In, Out>(
     mut observe: impl FnMut(&ResponsesWsEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -267,11 +265,11 @@ where
             .events
         {
             let payload = serde_json::to_string(&outbound)
-                .map_err(|error| CoreError::InvalidResponse(error.to_string()))?;
+                .map_err(|error| Error::InvalidResponse(error.to_string()))?;
             upstream_tx
                 .send(Message::Text(payload))
                 .await
-                .map_err(|error| CoreError::Network(error.to_string()))?;
+                .map_err(|error| Error::Network(error.to_string()))?;
         }
     }
     ResponsesWebSocketStreaming::bidirectional_forward(
@@ -296,7 +294,7 @@ pub async fn responses_ws<In, Out>(
     observe: impl FnMut(&ResponsesWsEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -514,7 +512,7 @@ mod tests {
         )
         .await
         .expect_err("status error");
-        assert!(matches!(error, CoreError::Http { status: 401, .. }));
+        assert!(matches!(error, Error::Http { status: 401, .. }));
         server.await.expect("server task");
     }
 
@@ -543,7 +541,7 @@ mod tests {
         )
         .await
         .expect_err("status error");
-        assert!(matches!(error, CoreError::Http { status: 500, .. }));
+        assert!(matches!(error, Error::Http { status: 500, .. }));
         server.await.expect("server task");
     }
 }
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs b/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs
index 9bc2818b6e7..e0ce165dc93 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs
@@ -3,8 +3,7 @@ use std::time::{Duration, Instant};
 
 use base64::Engine;
 use base64::engine::general_purpose::STANDARD as BASE64_STANDARD;
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::ocr::transformation::OcrProviderConfig;
 use reqwest::Url;
 use serde_json::{Map, Value};
@@ -56,7 +55,7 @@ fn is_azure_document_intelligence_model(model: &str) -> bool {
 
 pub(super) fn string_headers(
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     extra_headers
         .unwrap_or_default()
         .into_iter()
@@ -65,7 +64,7 @@ pub(super) fn string_headers(
                 .as_str()
                 .map(|value| (key.clone(), value.to_string()))
                 .ok_or_else(|| {
-                    CoreError::InvalidRequest(format!(
+                    Error::InvalidRequest(format!(
                         "OCR extra_headers.{key} must be a string, got {}",
                         litellm_core::error::json_type_name(&value)
                     ))
@@ -80,7 +79,7 @@ pub(super) fn has_header(headers: &[(String, String)], name: &str) -> bool {
         .any(|(key, _)| key.eq_ignore_ascii_case(name))
 }
 
-fn document_url_field(document: &Value) -> CoreResult<Option<(&str, &str)>> {
+fn document_url_field(document: &Value) -> Result<Option<(&str, &str)>, Error> {
     let Some(object) = document.as_object() else {
         return Ok(None);
     };
@@ -138,13 +137,13 @@ fn is_blocked_ip(ip: IpAddr) -> bool {
     }
 }
 
-fn blocked_url_error(url: &Url) -> CoreError {
-    CoreError::InvalidRequest(format!(
+fn blocked_url_error(url: &Url) -> Error {
+    Error::InvalidRequest(format!(
         "OCR document URL rejected by SSRF protection: {url}"
     ))
 }
 
-async fn validate_safe_fetch_url(url: &Url) -> CoreResult<()> {
+async fn validate_safe_fetch_url(url: &Url) -> Result<(), Error> {
     if !matches!(url.scheme(), "http" | "https") {
         return Err(blocked_url_error(url));
     }
@@ -162,7 +161,7 @@ async fn validate_safe_fetch_url(url: &Url) -> CoreResult<()> {
         .ok_or_else(|| blocked_url_error(url))?;
     let addresses = tokio::net::lookup_host((host, port))
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     let mut saw_address = false;
     for address in addresses {
         saw_address = true;
@@ -176,25 +175,25 @@ async fn validate_safe_fetch_url(url: &Url) -> CoreResult<()> {
     Ok(())
 }
 
-fn redirect_location(response: &reqwest::Response, url: &Url) -> CoreResult<Url> {
+fn redirect_location(response: &reqwest::Response, url: &Url) -> Result<Url, Error> {
     let location = response
         .headers()
         .get(reqwest::header::LOCATION)
         .and_then(|value| value.to_str().ok())
         .ok_or_else(|| {
-            CoreError::InvalidResponse("OCR document redirect missing Location header".to_string())
+            Error::InvalidResponse("OCR document redirect missing Location header".to_string())
         })?;
     url.join(location)
-        .map_err(|err| CoreError::InvalidResponse(format!("invalid OCR document redirect: {err}")))
+        .map_err(|err| Error::InvalidResponse(format!("invalid OCR document redirect: {err}")))
 }
 
-async fn safe_get_document_url(url: &str) -> CoreResult<(Url, reqwest::Response)> {
+async fn safe_get_document_url(url: &str) -> Result<(Url, reqwest::Response), Error> {
     let client = reqwest::Client::builder()
         .redirect(reqwest::redirect::Policy::none())
         .build()
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     let mut current_url = Url::parse(url)
-        .map_err(|err| CoreError::InvalidRequest(format!("invalid OCR document URL: {err}")))?;
+        .map_err(|err| Error::InvalidRequest(format!("invalid OCR document URL: {err}")))?;
 
     for _ in 0..MAX_SAFE_FETCH_REDIRECTS {
         validate_safe_fetch_url(&current_url).await?;
@@ -202,28 +201,28 @@ async fn safe_get_document_url(url: &str) -> CoreResult<(Url, reqwest::Response)
             .get(current_url.clone())
             .send()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .map_err(|err| Error::Network(err.to_string()))?;
         if !response.status().is_redirection() {
             return Ok((current_url, response));
         }
         current_url = redirect_location(&response, &current_url)?;
     }
 
-    Err(CoreError::InvalidRequest(
+    Err(Error::InvalidRequest(
         "Too many redirects while fetching OCR document URL".to_string(),
     ))
 }
 
-fn enforce_download_size(content_length: u64, max_bytes: u64, url: &Url) -> CoreResult<()> {
+fn enforce_download_size(content_length: u64, max_bytes: u64, url: &Url) -> Result<(), Error> {
     if max_bytes == 0 {
-        return Err(CoreError::InvalidRequest(format!(
+        return Err(Error::InvalidRequest(format!(
             "OCR document URL download is disabled (MAX_IMAGE_URL_DOWNLOAD_SIZE_MB=0). url={url}"
         )));
     }
     if content_length > max_bytes {
         let size_mb = content_length as f64 / (1024.0 * 1024.0);
         let max_size_mb = max_bytes as f64 / (1024.0 * 1024.0);
-        return Err(CoreError::InvalidRequest(format!(
+        return Err(Error::InvalidRequest(format!(
             "OCR document size ({size_mb:.2}MB) exceeds maximum allowed size ({max_size_mb:.2}MB). url={url}"
         )));
     }
@@ -233,7 +232,7 @@ fn enforce_download_size(content_length: u64, max_bytes: u64, url: &Url) -> Core
 async fn read_response_with_limit(
     mut response: reqwest::Response,
     url: &Url,
-) -> CoreResult<Vec<u8>> {
+) -> Result<Vec<u8>, Error> {
     let max_bytes = max_document_download_bytes();
     if let Some(content_length) = response.content_length() {
         enforce_download_size(content_length, max_bytes, url)?;
@@ -246,7 +245,7 @@ async fn read_response_with_limit(
     while let Some(chunk) = response
         .chunk()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?
+        .map_err(|err| Error::Network(err.to_string()))?
     {
         bytes_downloaded += chunk.len() as u64;
         enforce_download_size(bytes_downloaded, max_bytes, url)?;
@@ -255,7 +254,7 @@ async fn read_response_with_limit(
     Ok(bytes)
 }
 
-pub(super) async fn convert_document_url_to_data_uri(document: Value) -> CoreResult<Value> {
+pub(super) async fn convert_document_url_to_data_uri(document: Value) -> Result<Value, Error> {
     let Some((field, url)) = document_url_field(&document)? else {
         return Ok(document);
     };
@@ -267,7 +266,7 @@ pub(super) async fn convert_document_url_to_data_uri(document: Value) -> CoreRes
     let status = response.status();
     if !status.is_success() {
         let body = response.text().await.unwrap_or_default();
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&body),
         });
@@ -290,7 +289,7 @@ pub(super) async fn convert_document_url_to_data_uri(document: Value) -> CoreRes
     let mut transformed = document
         .as_object()
         .cloned()
-        .ok_or_else(|| CoreError::InvalidRequest("OCR document must be an object".to_string()))?;
+        .ok_or_else(|| Error::InvalidRequest("OCR document must be an object".to_string()))?;
     transformed.insert(field.to_string(), Value::String(data_uri));
     Ok(Value::Object(transformed))
 }
@@ -316,11 +315,11 @@ fn retry_after_secs(response: &reqwest::Response) -> u64 {
         .unwrap_or(2)
 }
 
-fn operation_status(response_json: &Value) -> CoreResult<&str> {
+fn operation_status(response_json: &Value) -> Result<&str, Error> {
     let status = response_json
         .get("status")
         .and_then(Value::as_str)
-        .ok_or(CoreError::MissingField("status"))?;
+        .ok_or(Error::MissingField("status"))?;
     match status {
         "succeeded" => Ok("succeeded"),
         "running" | "notStarted" => Ok("running"),
@@ -330,11 +329,11 @@ fn operation_status(response_json: &Value) -> CoreResult<&str> {
                 .and_then(|error| error.get("message"))
                 .and_then(Value::as_str)
                 .unwrap_or("Unknown error");
-            Err(CoreError::InvalidResponse(format!(
+            Err(Error::InvalidResponse(format!(
                 "Azure Document Intelligence analysis failed: {message}"
             )))
         }
-        other => Err(CoreError::InvalidResponse(format!(
+        other => Err(Error::InvalidResponse(format!(
             "Unknown operation status: {other}"
         ))),
     }
@@ -345,9 +344,9 @@ pub(super) async fn poll_document_intelligence(
     original_url: &str,
     headers: &[(String, String)],
     timeout: Option<Duration>,
-) -> CoreResult<Value> {
+) -> Result<Value, Error> {
     if !same_origin(operation_url, original_url) {
-        return Err(CoreError::InvalidResponse(
+        return Err(Error::InvalidResponse(
             "Azure Document Intelligence: rejected cross-origin polling URL".to_string(),
         ));
     }
@@ -358,7 +357,7 @@ pub(super) async fn poll_document_intelligence(
     ));
     loop {
         if start.elapsed() > timeout {
-            return Err(CoreError::Network(format!(
+            return Err(Error::Network(format!(
                 "Azure Document Intelligence operation polling timed out after {} seconds",
                 timeout.as_secs()
             )));
@@ -373,21 +372,21 @@ pub(super) async fn poll_document_intelligence(
         let response = request_builder
             .send()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .map_err(|err| Error::Network(err.to_string()))?;
         let retry_after = retry_after_secs(&response);
         let status = response.status();
         let text = response
             .text()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .map_err(|err| Error::Network(err.to_string()))?;
         if !status.is_success() {
-            return Err(CoreError::Http {
+            return Err(Error::Http {
                 status: status.as_u16(),
                 body: truncate_error_body(&text),
             });
         }
         let response_json: Value = serde_json::from_str(&text).map_err(|err| {
-            CoreError::InvalidResponse(format!("invalid Azure DI poll response JSON: {err}"))
+            Error::InvalidResponse(format!("invalid Azure DI poll response JSON: {err}"))
         })?;
         if operation_status(&response_json)? == "succeeded" {
             return Ok(response_json);
@@ -426,7 +425,7 @@ mod tests {
 
         assert!(matches!(
             error,
-            CoreError::InvalidRequest(message)
+            Error::InvalidRequest(message)
                 if message.contains("SSRF protection")
         ));
     }
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/handler.rs b/litellm-rust/crates/ai-gateway/src/ocr/handler.rs
index 1de34eb400e..815bc84363a 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/handler.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/handler.rs
@@ -1,5 +1,4 @@
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::ocr::transformation::OcrResponseHandling;
 use serde_json::Value;
 
@@ -7,7 +6,7 @@ use super::common_utils::{poll_document_intelligence, truncate_error_body};
 use super::types::ProviderOcrRequest;
 use crate::client::http_client;
 
-pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> CoreResult<Value> {
+pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> Result<Value, Error> {
     let mut request_builder = http_client().post(&request.url).json(&request.body);
     for (key, value) in &request.upstream_headers {
         request_builder = request_builder.header(key, value);
@@ -19,7 +18,7 @@ pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> Co
     let response = request_builder
         .send()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     let status = response.status();
     if request.config.response_handling() == OcrResponseHandling::AzureDocumentIntelligencePoll
@@ -31,7 +30,7 @@ pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> Co
             .and_then(|value| value.to_str().ok())
             .map(str::to_string)
             .ok_or_else(|| {
-                CoreError::InvalidResponse(
+                Error::InvalidResponse(
                     "Azure Document Intelligence returned 202 but no Operation-Location header found"
                         .to_string(),
                 )
@@ -52,17 +51,17 @@ pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> Co
     let text = response
         .text()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     if !status.is_success() {
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
     }
 
     let response_json: Value = serde_json::from_str(&text)
-        .map_err(|err| CoreError::InvalidResponse(format!("invalid OCR response JSON: {err}")))?;
+        .map_err(|err| Error::InvalidResponse(format!("invalid OCR response JSON: {err}")))?;
 
     Ok(request
         .config
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs b/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs
index 95df566dc53..401e26d3b29 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs
@@ -1,11 +1,9 @@
-use std::future::Future;
-use std::pin::Pin;
-
-use litellm_core::CoreResult;
 use litellm_core::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::ocr::transformation::OcrAuthStrategy;
 use serde_json::{Map, Value, json};
+use std::future::Future;
+use std::pin::Pin;
 
 use super::common_utils::{
     convert_document_url_to_data_uri, has_header, ocr_provider_config, string_headers,
@@ -27,7 +25,7 @@ pub(crate) struct OcrLifecycleHooks {
     request_metadata: RequestMetadata,
 }
 
-type OcrFuture<'a, T> = Pin<Box<dyn Future<Output = CoreResult<T>> + Send + 'a>>;
+type OcrFuture<'a, T> = Pin<Box<dyn Future<Output = Result<T, Error>> + Send + 'a>>;
 type OcrLogFuture<'a> = Pin<Box<dyn Future<Output = ()> + Send + 'a>>;
 
 impl OcrLifecycleHooks {
@@ -46,7 +44,7 @@ impl OcrLifecycleHooks {
     async fn run_pre_call_guardrails(
         &self,
         request: PreparedOcrRequest,
-    ) -> CoreResult<PreparedOcrRequest> {
+    ) -> Result<PreparedOcrRequest, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(request);
         }
@@ -74,9 +72,9 @@ impl OcrLifecycleHooks {
     async fn prepare_provider_request(
         &self,
         request: PreparedOcrRequest,
-    ) -> CoreResult<ProviderOcrRequest> {
+    ) -> Result<ProviderOcrRequest, Error> {
         let config = ocr_provider_config(&request.custom_llm_provider, &request.model)
-            .ok_or_else(|| CoreError::InvalidProvider(request.custom_llm_provider.clone()))?;
+            .ok_or_else(|| Error::InvalidProvider(request.custom_llm_provider.clone()))?;
         let env_lookup = |key: &str| std::env::var(key).ok();
         let headers = string_headers(request.extra_headers)?;
         let auth_strategy = config.auth_strategy();
@@ -120,7 +118,7 @@ impl OcrLifecycleHooks {
         custom_llm_provider: &str,
         url: &str,
         body: Value,
-    ) -> CoreResult<Value> {
+    ) -> Result<Value, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(body);
         }
@@ -217,7 +215,7 @@ impl CallLifecycleHooks<PreparedOcrRequest, ProviderOcrRequest, Value> for OcrLi
     fn async_log_failure_event<'a>(
         &'a self,
         context: &'a CallLifecycleContext,
-        error: &'a CoreError,
+        error: &'a Error,
         timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a> {
         Box::pin(async move {
@@ -278,19 +276,19 @@ fn guardrail_context(metadata: &RequestMetadata) -> GuardrailContext {
 
 fn parse_ocr_pre_call_guardrail_request(
     request: GuardrailRequest,
-) -> CoreResult<(Value, Map<String, Value>)> {
+) -> Result<(Value, Map<String, Value>), Error> {
     let Value::Object(mut data) = request.data else {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "OCR pre_call guardrail must return an object".to_string(),
         ));
     };
     let document = data.remove("document").ok_or_else(|| {
-        CoreError::InvalidRequest("OCR pre_call guardrail removed document".to_string())
+        Error::InvalidRequest("OCR pre_call guardrail removed document".to_string())
     })?;
     let optional_params = match data.remove("optional_params") {
         Some(Value::Object(params)) => params,
         Some(_) => {
-            return Err(CoreError::InvalidRequest(
+            return Err(Error::InvalidRequest(
                 "OCR pre_call guardrail optional_params must be an object".to_string(),
             ));
         }
@@ -299,33 +297,32 @@ fn parse_ocr_pre_call_guardrail_request(
     Ok((document, optional_params))
 }
 
-fn parse_ocr_during_call_guardrail_request(request: GuardrailRequest) -> CoreResult<Value> {
+fn parse_ocr_during_call_guardrail_request(request: GuardrailRequest) -> Result<Value, Error> {
     let Value::Object(mut data) = request.data else {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "OCR during_call guardrail must return an object".to_string(),
         ));
     };
-    data.remove("body").ok_or_else(|| {
-        CoreError::InvalidRequest("OCR during_call guardrail removed body".to_string())
-    })
+    data.remove("body")
+        .ok_or_else(|| Error::InvalidRequest("OCR during_call guardrail removed body".to_string()))
 }
 
-fn guardrail_error_to_core_error(error: GuardrailError) -> CoreError {
-    CoreError::InvalidRequest(format!("{}: {}", error.kind, error.message))
+fn guardrail_error_to_core_error(error: GuardrailError) -> Error {
+    Error::InvalidRequest(format!("{}: {}", error.kind, error.message))
 }
 
-fn core_error_kind(error: &CoreError) -> &'static str {
+fn core_error_kind(error: &Error) -> &'static str {
     match error {
-        CoreError::Auth(_) => "AuthError",
-        CoreError::InvalidProvider(_) => "InvalidProvider",
-        CoreError::InvalidRequest(_) => "InvalidRequest",
-        CoreError::InvalidType { .. } => "InvalidType",
-        CoreError::MissingField(_) => "MissingField",
-        CoreError::Http { .. } => "HttpError",
-        CoreError::InvalidResponse(_) => "InvalidResponse",
-        CoreError::Network(_) => "NetworkError",
-        CoreError::Connect(_) => "ConnectError",
-        CoreError::Routing(_) => "RoutingError",
-        CoreError::Unsupported(_) => "UnsupportedRequest",
+        Error::Auth(_) => "AuthError",
+        Error::InvalidProvider(_) => "InvalidProvider",
+        Error::InvalidRequest(_) => "InvalidRequest",
+        Error::InvalidType { .. } => "InvalidType",
+        Error::MissingField(_) => "MissingField",
+        Error::Http { .. } => "HttpError",
+        Error::InvalidResponse(_) => "InvalidResponse",
+        Error::Network(_) => "NetworkError",
+        Error::Connect(_) => "ConnectError",
+        Error::Routing(_) => "RoutingError",
+        Error::Unsupported(_) => "UnsupportedRequest",
     }
 }
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/mod.rs b/litellm-rust/crates/ai-gateway/src/ocr/mod.rs
index c4c13e2300c..b59ab626fd3 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/mod.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/mod.rs
@@ -1,4 +1,4 @@
-use litellm_core::CoreResult;
+use litellm_core::Error;
 use litellm_core::call_lifecycle::CallLifecycle;
 use serde_json::Value;
 
@@ -13,7 +13,7 @@ pub use types::OcrRequest;
 use handler::execute_ocr_provider_call;
 use prepare::{PreparedOcrCall, prepare_ocr_call};
 
-pub async fn ocr(request: OcrRequest<'_>) -> CoreResult<Value> {
+pub async fn ocr(request: OcrRequest<'_>) -> Result<Value, Error> {
     let PreparedOcrCall { request, hooks } = prepare_ocr_call(request);
     CallLifecycle::default()
         .run_request(request, &hooks, execute_ocr_provider_call)
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/tests.rs b/litellm-rust/crates/ai-gateway/src/ocr/tests.rs
index bb2a6b06501..8c3f0425149 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/tests.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/tests.rs
@@ -1,7 +1,7 @@
 use std::sync::{Arc, Mutex};
 use std::time::Duration;
 
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::ocr::transformation::OcrResponseHandling;
 use serde_json::{Map, Value, json};
 use tokio::io::{AsyncReadExt, AsyncWriteExt};
@@ -395,7 +395,7 @@ async fn ocr_lifecycle_runs_failure_hook_on_provider_error() {
     .await
     .expect_err("provider error propagates");
 
-    assert!(matches!(err, CoreError::Http { status: 500, .. }));
+    assert!(matches!(err, Error::Http { status: 500, .. }));
     server.await.expect("server task completes");
     assert_eq!(
         logger.events(),
@@ -439,7 +439,7 @@ async fn ocr_lifecycle_pre_call_block_skips_provider_socket() {
     .await
     .expect_err("guardrail blocks request");
 
-    assert!(matches!(err, CoreError::InvalidRequest(_)));
+    assert!(matches!(err, Error::InvalidRequest(_)));
     assert_eq!(guardrail.events(), vec!["async_pre_call_hook"]);
     assert_eq!(
         logger.events(),
@@ -607,7 +607,7 @@ fn string_headers_rejects_non_string_values() {
     let err = string_headers(Some(headers)).expect_err("non-string header rejected");
     assert_eq!(
         err,
-        CoreError::InvalidRequest(
+        Error::InvalidRequest(
             "OCR extra_headers.x-retry-count must be a string, got number".to_string()
         )
     );
diff --git a/litellm-rust/crates/ai-gateway/src/python/config.rs b/litellm-rust/crates/ai-gateway/src/python/config.rs
index c028d3d6b51..d5a4dd69c8d 100644
--- a/litellm-rust/crates/ai-gateway/src/python/config.rs
+++ b/litellm-rust/crates/ai-gateway/src/python/config.rs
@@ -6,33 +6,31 @@
 //! (and recorded in [`crate::gil`]); the realtime hot path never touches Python.
 //!
 //! Compiled only under the `python-config` feature.
-
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::router::{Deployment, Router};
 use pyo3::prelude::*;
 
 use crate::gil;
 
 /// Load the router's `model_list` from `config_path` via the Python reader.
-pub fn load_router_from_config(config_path: &str) -> CoreResult<Router> {
+pub fn load_router_from_config(config_path: &str) -> Result<Router, Error> {
     gil::record_acquisition();
     Python::attach(|py| {
         let model_list = py
             .import("litellm.proxy.read_model_list")
             .and_then(|module| module.getattr("read_model_list"))
             .and_then(|reader| reader.call1((config_path,)))
-            .map_err(|err| CoreError::Routing(format!("read_model_list failed: {err}")))?;
+            .map_err(|err| Error::Routing(format!("read_model_list failed: {err}")))?;
 
         let model_list_json: String = py
             .import("json")
             .and_then(|json| json.getattr("dumps"))
             .and_then(|dumps| dumps.call1((model_list,)))
             .and_then(|encoded| encoded.extract())
-            .map_err(|err| CoreError::Routing(format!("serializing model_list failed: {err}")))?;
+            .map_err(|err| Error::Routing(format!("serializing model_list failed: {err}")))?;
 
         let deployments: Vec<Deployment> = serde_json::from_str(&model_list_json)
-            .map_err(|err| CoreError::Routing(format!("parsing model_list failed: {err}")))?;
+            .map_err(|err| Error::Routing(format!("parsing model_list failed: {err}")))?;
 
         Ok(Router::new(deployments))
     })
diff --git a/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs b/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs
index 7e38d10c6ff..e9f8c477f36 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs
@@ -9,7 +9,7 @@ use axum::http::StatusCode;
 use axum::http::header::{CACHE_CONTROL, CONTENT_TYPE, HeaderMap, HeaderValue};
 use axum::response::{IntoResponse, Response};
 use axum::routing::post;
-use litellm_core::CoreError;
+use litellm_core::Error;
 use serde_json::{Map, Value};
 
 use crate::auth::RequireMasterKey;
@@ -46,7 +46,7 @@ fn stream_response(upstream: reqwest::Response) -> Result<Response, MessagesRout
     let mut response = Response::builder()
         .status(
             StatusCode::from_u16(upstream.status().as_u16()).map_err(|error| {
-                MessagesRouteError(CoreError::InvalidResponse(format!(
+                MessagesRouteError(Error::InvalidResponse(format!(
                     "invalid upstream response status: {error}"
                 )))
             })?,
@@ -58,13 +58,13 @@ fn stream_response(upstream: reqwest::Response) -> Result<Response, MessagesRout
     response
         .body(Body::from_stream(upstream.bytes_stream()))
         .map_err(|error| {
-            MessagesRouteError(CoreError::InvalidResponse(format!(
+            MessagesRouteError(Error::InvalidResponse(format!(
                 "failed to build streaming response: {error}"
             )))
         })
 }
 
-fn forwarded_headers(headers: &HeaderMap) -> Result<Option<Map<String, Value>>, CoreError> {
+fn forwarded_headers(headers: &HeaderMap) -> Result<Option<Map<String, Value>>, Error> {
     let forwarded = headers
         .iter()
         .filter(|(name, _)| {
@@ -74,19 +74,19 @@ fn forwarded_headers(headers: &HeaderMap) -> Result<Option<Map<String, Value>>,
         })
         .map(|(name, value)| {
             let value = value.to_str().map_err(|_| {
-                CoreError::InvalidRequest(format!("invalid value for header {}", name.as_str()))
+                Error::InvalidRequest(format!("invalid value for header {}", name.as_str()))
             })?;
             Ok((name.to_string(), Value::String(value.to_string())))
         })
-        .collect::<Result<Map<_, _>, CoreError>>()?;
+        .collect::<Result<Map<_, _>, Error>>()?;
     Ok((!forwarded.is_empty()).then_some(forwarded))
 }
 
 #[derive(Debug)]
-struct MessagesRouteError(CoreError);
+struct MessagesRouteError(Error);
 
-impl From<CoreError> for MessagesRouteError {
-    fn from(error: CoreError) -> Self {
+impl From<Error> for MessagesRouteError {
+    fn from(error: Error) -> Self {
         Self(error)
     }
 }
@@ -94,28 +94,28 @@ impl From<CoreError> for MessagesRouteError {
 impl IntoResponse for MessagesRouteError {
     fn into_response(self) -> Response {
         let (status, message) = match self.0 {
-            CoreError::InvalidRequest(message) => (StatusCode::BAD_REQUEST, message),
-            CoreError::InvalidProvider(_) | CoreError::Routing(_) => (
+            Error::InvalidRequest(message) => (StatusCode::BAD_REQUEST, message),
+            Error::InvalidProvider(_) | Error::Routing(_) => (
                 StatusCode::NOT_FOUND,
                 "no messages deployment is configured for this model".to_string(),
             ),
-            CoreError::Auth(_) => (
+            Error::Auth(_) => (
                 StatusCode::BAD_GATEWAY,
                 "messages provider authentication failed".to_string(),
             ),
-            CoreError::Http { .. }
-            | CoreError::Network(_)
-            | CoreError::Connect(_)
-            | CoreError::InvalidResponse(_)
-            | CoreError::InvalidType { .. }
-            | CoreError::MissingField(_) => (
+            Error::Http { .. }
+            | Error::Network(_)
+            | Error::Connect(_)
+            | Error::InvalidResponse(_)
+            | Error::InvalidType { .. }
+            | Error::MissingField(_) => (
                 StatusCode::BAD_GATEWAY,
                 "messages provider request failed".to_string(),
             ),
             // The gateway has no Python implementation to decline to, so a
             // request the core cannot serve is reported to the caller. The
             // reason is a fixed internal string, never provider content.
-            CoreError::Unsupported(reason) => (
+            Error::Unsupported(reason) => (
                 StatusCode::BAD_REQUEST,
                 format!("messages request is not supported: {reason}"),
             ),
diff --git a/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs b/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs
index 5f4c5fe8de4..4fd29db05d6 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs
@@ -1,10 +1,10 @@
 use std::sync::Arc;
 
+use litellm_core::Error;
 use litellm_core::constants::ANTHROPIC_MESSAGES_PROVIDER;
 use litellm_core::messages::types::MessagesRequest;
 use litellm_core::messages::{messages, messages_stream};
 use litellm_core::router::Router;
-use litellm_core::{CoreError, CoreResult};
 use serde_json::{Map, Value};
 
 pub(crate) enum MessagesResponse {
@@ -16,16 +16,16 @@ pub async fn run(
     router: &Arc<Router>,
     body: Value,
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<MessagesResponse> {
+) -> Result<MessagesResponse, Error> {
     let model = body
         .get("model")
         .and_then(Value::as_str)
         .map(str::trim)
         .filter(|model| !model.is_empty())
-        .ok_or_else(|| CoreError::InvalidRequest("messages body requires a model".to_string()))?;
-    let deployment = router.get_available_deployment(model).ok_or_else(|| {
-        CoreError::Routing(format!("no deployment available for model '{model}'"))
-    })?;
+        .ok_or_else(|| Error::InvalidRequest("messages body requires a model".to_string()))?;
+    let deployment = router
+        .get_available_deployment(model)
+        .ok_or_else(|| Error::Routing(format!("no deployment available for model '{model}'")))?;
     let provider_model = deployment.litellm_params.model.as_str();
     let upstream_model = provider_model
         .split_once('/')
@@ -37,7 +37,7 @@ pub async fn run(
     };
     let mut body = body;
     body.as_object_mut()
-        .ok_or_else(|| CoreError::InvalidRequest("messages body must be an object".to_string()))?
+        .ok_or_else(|| Error::InvalidRequest("messages body must be an object".to_string()))?
         .insert(
             "model".to_string(),
             Value::String(upstream_model.to_string()),
@@ -60,6 +60,6 @@ pub async fn run(
     serde_json::to_value(response)
         .map(MessagesResponse::Json)
         .map_err(|err| {
-            CoreError::InvalidResponse(format!("failed to serialize messages response: {err}"))
+            Error::InvalidResponse(format!("failed to serialize messages response: {err}"))
         })
 }
diff --git a/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs b/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs
index 4ae8cfe7379..b8ee77c4269 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs
@@ -11,8 +11,7 @@ use std::time::Duration;
 
 use crate::io::realtime_pool::{RealtimePool, upstream_key};
 use futures_util::{Sink, Stream};
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::realtime::types::RealtimeEvent;
 use litellm_core::router::Router;
 
@@ -29,15 +28,15 @@ pub async fn run<In, Out>(
     observe: impl FnMut(&RealtimeEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
     <Out as Sink<RealtimeEvent>>::Error: std::fmt::Display,
 {
-    let deployment = router.get_available_deployment(model).ok_or_else(|| {
-        CoreError::Routing(format!("no deployment available for model '{model}'"))
-    })?;
+    let deployment = router
+        .get_available_deployment(model)
+        .ok_or_else(|| Error::Routing(format!("no deployment available for model '{model}'")))?;
     let params = &deployment.litellm_params;
     // Strip a leading `openai/` so the OpenAI-only realtime fn gets the bare model.
     let provider_model = params
diff --git a/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs b/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs
index 165c95695d3..e8f840c0c8e 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs
@@ -2,13 +2,13 @@ use std::sync::Arc;
 use std::time::Duration;
 
 use futures_util::{Sink, Stream};
+use litellm_core::Error;
 use litellm_core::call_lifecycle::{CallLifecycle, CallLifecycleContext};
 use litellm_core::responses::instrumentation::{
     ResponsesWsCallbackPayload, ResponsesWsInstrumentation, ResponsesWsLogOutcome,
     ResponsesWsMetadata,
 };
 use litellm_core::responses::types::ResponsesWsEvent;
-use litellm_core::{CoreError, CoreResult};
 
 use crate::integrations::custom_logger::{
     CallbackTiming, CallbackValue, CustomLogger, CustomLoggerRunner, LoggingError, ModelCallDetails,
@@ -26,22 +26,22 @@ pub async fn run<In, Out>(
     metadata: RequestMetadata,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
     Out::Error: std::fmt::Display,
 {
-    let deployment = router.get_available_deployment(model).ok_or_else(|| {
-        CoreError::Routing(format!("no deployment available for model '{model}'"))
-    })?;
+    let deployment = router
+        .get_available_deployment(model)
+        .ok_or_else(|| Error::Routing(format!("no deployment available for model '{model}'")))?;
     let params = &deployment.litellm_params;
     let provider_model = params
         .model
         .strip_prefix("openai/")
         .unwrap_or(&params.model);
     if params.model.contains('/') && !params.model.starts_with("openai/") {
-        return Err(CoreError::InvalidProvider(
+        return Err(Error::InvalidProvider(
             "Responses WebSocket route supports OpenAI deployments only".to_string(),
         ));
     }
diff --git a/litellm-rust/crates/core/src/audio_transcription/transformation.rs b/litellm-rust/crates/core/src/audio_transcription/transformation.rs
index eab34c13843..16a28fbcac0 100644
--- a/litellm-rust/crates/core/src/audio_transcription/transformation.rs
+++ b/litellm-rust/crates/core/src/audio_transcription/transformation.rs
@@ -1,7 +1,6 @@
+use crate::Error;
 use serde_json::{Map, Value};
 
-use crate::CoreResult;
-
 use super::types::{AudioTranscriptionRequestData, AudioTranscriptionResponseData};
 
 #[derive(Clone, Debug, PartialEq, Eq)]
@@ -32,13 +31,13 @@ pub trait AudioTranscriptionProviderConfig: Sync {
         model: &str,
         audio: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<AudioTranscriptionRequestData>;
+    ) -> Result<AudioTranscriptionRequestData, Error>;
 
     fn transform_transcription_response(
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<AudioTranscriptionResponseData>;
+    ) -> Result<AudioTranscriptionResponseData, Error>;
 
     fn complete_url(
         &self,
@@ -46,12 +45,12 @@ pub trait AudioTranscriptionProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn auth_strategy(
         &self,
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<AudioTranscriptionAuth>;
+    ) -> Result<AudioTranscriptionAuth, Error>;
 }
diff --git a/litellm-rust/crates/core/src/call_lifecycle/mod.rs b/litellm-rust/crates/core/src/call_lifecycle/mod.rs
index d9b68a1b726..637c156e192 100644
--- a/litellm-rust/crates/core/src/call_lifecycle/mod.rs
+++ b/litellm-rust/crates/core/src/call_lifecycle/mod.rs
@@ -1,7 +1,7 @@
 use std::future::Future;
 use std::time::{Instant, SystemTime, UNIX_EPOCH};
 
-use crate::{CoreError, CoreResult};
+use crate::Error;
 
 pub mod types;
 
@@ -11,14 +11,14 @@ pub use types::{
 };
 
 pub trait CallLifecycleHooks<InitialReq, ProviderReq, Resp>: Send + Sync {
-    type PreCallFuture<'a>: Future<Output = CoreResult<InitialReq>> + Send + 'a
+    type PreCallFuture<'a>: Future<Output = Result<InitialReq, Error>> + Send + 'a
     where
         Self: 'a,
         InitialReq: 'a,
         ProviderReq: 'a,
         Resp: 'a;
 
-    type DuringCallFuture<'a>: Future<Output = CoreResult<ProviderReq>> + Send + 'a
+    type DuringCallFuture<'a>: Future<Output = Result<ProviderReq, Error>> + Send + 'a
     where
         Self: 'a,
         InitialReq: 'a,
@@ -56,7 +56,7 @@ pub trait CallLifecycleHooks<InitialReq, ProviderReq, Resp>: Send + Sync {
     fn async_log_failure_event<'a>(
         &'a self,
         context: &'a CallLifecycleContext,
-        error: &'a CoreError,
+        error: &'a Error,
         timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a>;
 }
@@ -86,12 +86,12 @@ impl<'a> CallLifecycle<'a> {
         request: InitialReq,
         hooks: &Hooks,
         provider_call: ProviderCall,
-    ) -> CoreResult<Resp>
+    ) -> Result<Resp, Error>
     where
         InitialReq: CallLifecycleRequest,
         Hooks: CallLifecycleHooks<InitialReq, ProviderReq, Resp>,
         ProviderCall: FnOnce(ProviderReq) -> ProviderFuture,
-        ProviderFuture: Future<Output = CoreResult<Resp>>,
+        ProviderFuture: Future<Output = Result<Resp, Error>>,
     {
         let context = request.lifecycle_context();
         self.run(context, request, hooks, provider_call).await
@@ -103,11 +103,11 @@ impl<'a> CallLifecycle<'a> {
         request: InitialReq,
         hooks: &Hooks,
         provider_call: ProviderCall,
-    ) -> CoreResult<Resp>
+    ) -> Result<Resp, Error>
     where
         Hooks: CallLifecycleHooks<InitialReq, ProviderReq, Resp>,
         ProviderCall: FnOnce(ProviderReq) -> ProviderFuture,
-        ProviderFuture: Future<Output = CoreResult<Resp>>,
+        ProviderFuture: Future<Output = Result<Resp, Error>>,
     {
         let call_start = epoch_seconds();
         let mut phases = Vec::new();
@@ -166,7 +166,7 @@ impl<'a> CallLifecycle<'a> {
         &self,
         context: &CallLifecycleContext,
         hooks: &Hooks,
-        error: &CoreError,
+        error: &Error,
         call_start: f64,
         phases: &mut Vec<CallLifecyclePhaseTiming>,
     ) where
@@ -251,8 +251,8 @@ mod tests {
     }
 
     impl CallLifecycleHooks<String, String, String> for RecordingHooks {
-        type PreCallFuture<'a> = BoxFuture<'a, CoreResult<String>>;
-        type DuringCallFuture<'a> = BoxFuture<'a, CoreResult<String>>;
+        type PreCallFuture<'a> = BoxFuture<'a, Result<String, Error>>;
+        type DuringCallFuture<'a> = BoxFuture<'a, Result<String, Error>>;
         type SuccessFuture<'a> = BoxFuture<'a, ()>;
         type FailureFuture<'a> = BoxFuture<'a, ()>;
 
@@ -294,7 +294,7 @@ mod tests {
         fn async_log_failure_event<'a>(
             &'a self,
             _context: &'a CallLifecycleContext,
-            _error: &'a CoreError,
+            _error: &'a Error,
             _timing: &'a CallLifecycleTiming,
         ) -> Self::FailureFuture<'a> {
             Box::pin(async move {
@@ -304,8 +304,8 @@ mod tests {
     }
 
     impl CallLifecycleHooks<RecordingRequest, String, String> for RecordingHooks {
-        type PreCallFuture<'a> = BoxFuture<'a, CoreResult<RecordingRequest>>;
-        type DuringCallFuture<'a> = BoxFuture<'a, CoreResult<String>>;
+        type PreCallFuture<'a> = BoxFuture<'a, Result<RecordingRequest, Error>>;
+        type DuringCallFuture<'a> = BoxFuture<'a, Result<String, Error>>;
         type SuccessFuture<'a> = BoxFuture<'a, ()>;
         type FailureFuture<'a> = BoxFuture<'a, ()>;
 
@@ -345,7 +345,7 @@ mod tests {
         fn async_log_failure_event<'a>(
             &'a self,
             _context: &'a CallLifecycleContext,
-            _error: &'a CoreError,
+            _error: &'a Error,
             _timing: &'a CallLifecycleTiming,
         ) -> Self::FailureFuture<'a> {
             Box::pin(async move {
@@ -383,13 +383,13 @@ mod tests {
                 "request".to_string(),
                 &hooks,
                 |_request| async move {
-                    Err::<String, CoreError>(CoreError::Network("provider down".to_string()))
+                    Err::<String, Error>(Error::Network("provider down".to_string()))
                 },
             )
             .await
             .expect_err("call fails");
 
-        assert_eq!(error, CoreError::Network("provider down".to_string()));
+        assert_eq!(error, Error::Network("provider down".to_string()));
         assert_eq!(hooks.events(), vec!["pre_call", "during_call", "failure"]);
     }
 
diff --git a/litellm-rust/crates/core/src/chat_completions/common_utils.rs b/litellm-rust/crates/core/src/chat_completions/common_utils.rs
index 36eaf242a5a..ca51471eb7c 100644
--- a/litellm-rust/crates/core/src/chat_completions/common_utils.rs
+++ b/litellm-rust/crates/core/src/chat_completions/common_utils.rs
@@ -1,8 +1,7 @@
-use serde_json::{Map, Value};
-
-use crate::error::CoreResult;
+use crate::Error;
 use crate::http_utils::string_headers as shared_string_headers;
 use crate::providers::anthropic::chat_completions::transformation::ANTHROPIC_CHAT_COMPLETIONS_CONFIG;
+use serde_json::{Map, Value};
 
 use super::transformation::ChatCompletionsProviderConfig;
 
@@ -23,6 +22,6 @@ pub(super) fn chat_completions_provider_config(
 
 pub(super) fn string_headers(
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     shared_string_headers(HEADER_CONTEXT, extra_headers)
 }
diff --git a/litellm-rust/crates/core/src/chat_completions/handler.rs b/litellm-rust/crates/core/src/chat_completions/handler.rs
index afc4529fd26..7e2731442cc 100644
--- a/litellm-rust/crates/core/src/chat_completions/handler.rs
+++ b/litellm-rust/crates/core/src/chat_completions/handler.rs
@@ -1,6 +1,6 @@
 use serde_json::Value;
 
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::http_utils::truncate_error_body;
 
 use super::client::http_client;
@@ -11,9 +11,9 @@ use super::types::{
 
 pub(super) async fn execute_chat_completions_provider_call(
     request: ProviderChatCompletionsRequest,
-) -> CoreResult<ChatCompletionsResponse> {
+) -> Result<ChatCompletionsResponse, Error> {
     let body = serde_json::to_vec(&request.body).map_err(|err| {
-        CoreError::InvalidRequest(format!(
+        Error::InvalidRequest(format!(
             "failed to serialize chat completions request: {err}"
         ))
     })?;
@@ -32,9 +32,9 @@ pub(super) async fn execute_chat_completions_provider_call(
         // so the host can still serve it. Everything else here, a timeout
         // above all, may have reached the provider and been answered.
         if err.is_connect() || err.is_builder() {
-            CoreError::Connect(err.to_string())
+            Error::Connect(err.to_string())
         } else {
-            CoreError::Network(err.to_string())
+            Error::Network(err.to_string())
         }
     })?;
 
@@ -42,17 +42,17 @@ pub(super) async fn execute_chat_completions_provider_call(
     let text = response
         .text()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     if !status.is_success() {
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
     }
 
     let body: Value = serde_json::from_str(&text).map_err(|err| {
-        CoreError::InvalidResponse(format!("invalid chat completions response JSON: {err}"))
+        Error::InvalidResponse(format!("invalid chat completions response JSON: {err}"))
     })?;
     request
         .config
@@ -69,10 +69,10 @@ pub(super) async fn execute_chat_completions_provider_call(
 /// second kind has already been billed, and a host that keeps a reference
 /// implementation must not retry those, so collapse them to one variant that
 /// can only mean the provider was already called.
-pub(super) fn as_response_error(err: CoreError) -> CoreError {
+pub(super) fn as_response_error(err: Error) -> Error {
     match err {
-        already @ (CoreError::InvalidResponse(_) | CoreError::Http { .. }) => already,
-        other => CoreError::InvalidResponse(other.to_string()),
+        already @ (Error::InvalidResponse(_) | Error::Http { .. }) => already,
+        other => Error::InvalidResponse(other.to_string()),
     }
 }
 
@@ -80,7 +80,7 @@ pub(super) fn as_response_error(err: CoreError) -> CoreError {
 pub(super) async fn signed_headers(
     request: &ProviderChatCompletionsRequest,
     body: &[u8],
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     use std::collections::BTreeMap;
     use std::time::SystemTime;
 
@@ -101,7 +101,7 @@ pub(super) async fn signed_headers(
         .iter()
         .any(|(name, _)| is_sigv4_computed_header(name))
     {
-        return Err(CoreError::Unsupported(
+        return Err(Error::Unsupported(
             "request forwards a header AWS SigV4 computes",
         ));
     }
@@ -137,9 +137,9 @@ pub(super) async fn signed_headers(
 pub(super) async fn signed_headers(
     request: &ProviderChatCompletionsRequest,
     _body: &[u8],
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     match &request.auth {
-        ChatCompletionsAuth::AwsSigV4 { .. } => Err(CoreError::Unsupported(
+        ChatCompletionsAuth::AwsSigV4 { .. } => Err(Error::Unsupported(
             "AWS SigV4 requires the bedrock-auth feature",
         )),
         _ => Ok(request.upstream_headers.clone()),
diff --git a/litellm-rust/crates/core/src/chat_completions/mod.rs b/litellm-rust/crates/core/src/chat_completions/mod.rs
index f30ac1a24bf..0d009d36d16 100644
--- a/litellm-rust/crates/core/src/chat_completions/mod.rs
+++ b/litellm-rust/crates/core/src/chat_completions/mod.rs
@@ -6,6 +6,7 @@
 //! credentials, and it resolves the provider, translates the conversation,
 //! calls the provider, and returns a typed OpenAI-shaped response.
 
+use crate::Error;
 mod client;
 mod common_utils;
 pub mod conversation;
@@ -17,15 +18,13 @@ pub mod types;
 
 use serde_json::{Map, Value};
 
-use crate::error::CoreResult;
-
 use handler::execute_chat_completions_provider_call;
 use prepare::{parse_messages, prepare_chat_completions_call, resolve_provider_config};
 use types::{ChatCompletionsRequest, ChatCompletionsResponse};
 
 pub async fn chat_completions(
     request: ChatCompletionsRequest<'_>,
-) -> CoreResult<ChatCompletionsResponse> {
+) -> Result<ChatCompletionsResponse, Error> {
     execute_chat_completions_provider_call(prepare_chat_completions_call(request)?).await
 }
 
diff --git a/litellm-rust/crates/core/src/chat_completions/prepare.rs b/litellm-rust/crates/core/src/chat_completions/prepare.rs
index 1e1c8d1bafd..142b2f2aaed 100644
--- a/litellm-rust/crates/core/src/chat_completions/prepare.rs
+++ b/litellm-rust/crates/core/src/chat_completions/prepare.rs
@@ -1,6 +1,6 @@
 use serde_json::Value;
 
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::http_utils::has_header;
 use crate::routing_utils::provider::{CustomLlmProvider, get_custom_llm_provider};
 
@@ -11,7 +11,7 @@ use super::types::{ChatCompletionsRequest, ChatMessage, ProviderChatCompletionsR
 pub(super) fn resolve_provider_config<'a>(
     model: &'a str,
     custom_llm_provider: Option<&'a str>,
-) -> CoreResult<(String, &'static dyn ChatCompletionsProviderConfig)> {
+) -> Result<(String, &'static dyn ChatCompletionsProviderConfig), Error> {
     let provider_info = get_custom_llm_provider(model, custom_llm_provider)
         .or_else(|| {
             custom_llm_provider.map(|provider| CustomLlmProvider {
@@ -20,35 +20,34 @@ pub(super) fn resolve_provider_config<'a>(
             })
         })
         .ok_or_else(|| {
-            CoreError::InvalidProvider(
+            Error::InvalidProvider(
                 "unable to resolve custom_llm_provider for chat completions request".to_string(),
             )
         })?;
     let config = chat_completions_provider_config(provider_info.custom_llm_provider)
-        .ok_or_else(|| CoreError::InvalidProvider(provider_info.custom_llm_provider.to_string()))?;
+        .ok_or_else(|| Error::InvalidProvider(provider_info.custom_llm_provider.to_string()))?;
     Ok((provider_info.model.to_string(), config))
 }
 
-pub(super) fn parse_messages(messages: Value) -> CoreResult<Vec<ChatMessage>> {
-    serde_json::from_value(messages).map_err(|err| {
-        CoreError::InvalidRequest(format!("invalid chat completions messages: {err}"))
-    })
+pub(super) fn parse_messages(messages: Value) -> Result<Vec<ChatMessage>, Error> {
+    serde_json::from_value(messages)
+        .map_err(|err| Error::InvalidRequest(format!("invalid chat completions messages: {err}")))
 }
 
 pub(super) fn prepare_chat_completions_call(
     request: ChatCompletionsRequest<'_>,
-) -> CoreResult<ProviderChatCompletionsRequest> {
+) -> Result<ProviderChatCompletionsRequest, Error> {
     let (model, config) = resolve_provider_config(request.model, request.custom_llm_provider)?;
     let env_lookup = |key: &str| std::env::var(key).ok();
 
     let messages = parse_messages(request.messages)?;
     if messages.is_empty() {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "chat completions requires at least one message".to_string(),
         ));
     }
     if let Some(reason) = config.unsupported_reason(&messages, &request.optional_params) {
-        return Err(CoreError::Unsupported(reason.0));
+        return Err(Error::Unsupported(reason.0));
     }
 
     let mut headers = string_headers(request.extra_headers)?;
diff --git a/litellm-rust/crates/core/src/chat_completions/tests.rs b/litellm-rust/crates/core/src/chat_completions/tests.rs
index e2383723cb0..2858d180e27 100644
--- a/litellm-rust/crates/core/src/chat_completions/tests.rs
+++ b/litellm-rust/crates/core/src/chat_completions/tests.rs
@@ -1,6 +1,6 @@
 use serde_json::{Map, Value, json};
 
-use crate::error::CoreError;
+use crate::error::Error;
 
 use super::prepare::prepare_chat_completions_call;
 use super::transformation::ChatCompletionsAuth;
@@ -29,7 +29,7 @@ fn request<'a>(
 
 /// `ProviderChatCompletionsRequest` deliberately has no `Debug` (its headers
 /// carry resolved credentials), so unwrap the failure case by hand.
-fn decline(request: ChatCompletionsRequest<'_>) -> CoreError {
+fn decline(request: ChatCompletionsRequest<'_>) -> Error {
     match prepare_chat_completions_call(request) {
         Err(error) => error,
         Ok(prepared) => panic!("expected a decline, prepared a call to {}", prepared.url),
@@ -196,7 +196,7 @@ fn declines_an_unsupported_request_before_resolving_credentials() {
     call.api_key = None;
     // No api_key is set and no env is consulted: the gate must run first, so the
     // error is the decline rather than a missing-credential error.
-    assert_eq!(decline(call), CoreError::Unsupported("streaming"));
+    assert_eq!(decline(call), Error::Unsupported("streaming"));
 }
 
 #[test]
@@ -208,7 +208,7 @@ fn rejects_an_unknown_provider() {
             json!([{"role": "user", "content": "hi"}]),
             json!({}),
         )),
-        CoreError::InvalidProvider("openai".to_string())
+        Error::InvalidProvider("openai".to_string())
     );
 }
 
@@ -221,7 +221,7 @@ fn rejects_a_model_with_no_resolvable_provider() {
             json!([{"role": "user", "content": "hi"}]),
             json!({}),
         )),
-        CoreError::InvalidProvider(_)
+        Error::InvalidProvider(_)
     ));
 }
 
@@ -234,7 +234,7 @@ fn rejects_an_empty_or_malformed_message_list() {
             json!([]),
             json!({}),
         )),
-        CoreError::InvalidRequest("chat completions requires at least one message".to_string())
+        Error::InvalidRequest("chat completions requires at least one message".to_string())
     );
     assert!(matches!(
         decline(request(
@@ -243,7 +243,7 @@ fn rejects_an_empty_or_malformed_message_list() {
             json!("not a list"),
             json!({}),
         )),
-        CoreError::InvalidRequest(_)
+        Error::InvalidRequest(_)
     ));
 }
 
@@ -258,7 +258,7 @@ fn rejects_non_string_extra_headers() {
     call.extra_headers = Some(Map::from_iter([("x-trace".to_string(), json!(7))]));
     assert_eq!(
         decline(call),
-        CoreError::InvalidRequest(
+        Error::InvalidRequest(
             "chat completions extra_headers.x-trace must be a string, got number".to_string()
         )
     );
@@ -374,7 +374,7 @@ async fn a_forwarded_header_the_signer_computes_declines_to_python() {
             .await
             .expect_err("{forwarded} should decline instead of being signed");
         assert!(
-            matches!(error, CoreError::Unsupported(_)),
+            matches!(error, Error::Unsupported(_)),
             "{forwarded} declined as {error:?}, which the host would not fall back on"
         );
     }
@@ -727,7 +727,7 @@ mod round_trip {
         .expect_err("response cannot be normalized");
         handle.await.expect("server task");
         assert!(
-            matches!(err, CoreError::InvalidResponse(_)),
+            matches!(err, Error::InvalidResponse(_)),
             "expected a post-send error, got {err:?}"
         );
     }
@@ -745,7 +745,7 @@ mod round_trip {
         .expect_err("response cannot be normalized");
         handle.await.expect("server task");
         assert!(
-            matches!(err, CoreError::InvalidResponse(_)),
+            matches!(err, Error::InvalidResponse(_)),
             "expected a post-send error, got {err:?}"
         );
     }
@@ -763,7 +763,7 @@ mod round_trip {
         .expect_err("upstream rejects");
         handle.await.expect("server task");
         assert!(
-            matches!(err, CoreError::Http { status: 429, .. }),
+            matches!(err, Error::Http { status: 429, .. }),
             "expected a 429, got {err:?}"
         );
     }
@@ -787,7 +787,7 @@ mod round_trip {
         .await
         .expect_err("nothing is listening");
         assert!(
-            matches!(err, CoreError::Connect(_)),
+            matches!(err, Error::Connect(_)),
             "expected a pre-send connect failure, got {err:?}"
         );
     }
@@ -797,24 +797,24 @@ mod round_trip {
         use crate::chat_completions::handler::as_response_error;
 
         for original in [
-            CoreError::MissingField("usage"),
-            CoreError::Unsupported("non-text response content block"),
-            CoreError::InvalidRequest("whatever".to_string()),
-            CoreError::Auth("whatever".to_string()),
+            Error::MissingField("usage"),
+            Error::Unsupported("non-text response content block"),
+            Error::InvalidRequest("whatever".to_string()),
+            Error::Auth("whatever".to_string()),
         ] {
             let label = format!("{original:?}");
             assert!(
-                matches!(as_response_error(original), CoreError::InvalidResponse(_)),
+                matches!(as_response_error(original), Error::InvalidResponse(_)),
                 "{label} must not stay retryable once the provider has answered"
             );
         }
         // An upstream status is already unambiguous, so it survives intact.
         assert!(matches!(
-            as_response_error(CoreError::Http {
+            as_response_error(Error::Http {
                 status: 500,
                 body: "boom".to_string()
             }),
-            CoreError::Http { status: 500, .. }
+            Error::Http { status: 500, .. }
         ));
     }
 }
diff --git a/litellm-rust/crates/core/src/chat_completions/transformation.rs b/litellm-rust/crates/core/src/chat_completions/transformation.rs
index a30ce9dc77c..a0868209305 100644
--- a/litellm-rust/crates/core/src/chat_completions/transformation.rs
+++ b/litellm-rust/crates/core/src/chat_completions/transformation.rs
@@ -1,7 +1,6 @@
+use crate::Error;
 use serde_json::{Map, Value};
 
-use crate::error::CoreResult;
-
 use super::types::{
     ChatCompletionsResponse, ChatMessage, ChatMessageContent, ProviderChatRequestData,
     ProviderChatResponseData,
@@ -39,7 +38,7 @@ pub trait ChatCompletionsProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn auth(
         &self,
@@ -47,7 +46,7 @@ pub trait ChatCompletionsProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<ChatCompletionsAuth>;
+    ) -> Result<ChatCompletionsAuth, Error>;
 
     fn default_headers(&self) -> &'static [(&'static str, &'static str)] {
         &[("content-type", "application/json")]
@@ -91,13 +90,13 @@ pub trait ChatCompletionsProviderConfig: Sync {
         model: &str,
         messages: Vec<ChatMessage>,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<ProviderChatRequestData>;
+    ) -> Result<ProviderChatRequestData, Error>;
 
     fn transform_response(
         &self,
         model: &str,
         response: ProviderChatResponseData,
-    ) -> CoreResult<ChatCompletionsResponse>;
+    ) -> Result<ChatCompletionsResponse, Error>;
 }
 
 pub fn unsupported_param(
diff --git a/litellm-rust/crates/core/src/error.rs b/litellm-rust/crates/core/src/error.rs
index 739532f8cb5..db3fa2ec704 100644
--- a/litellm-rust/crates/core/src/error.rs
+++ b/litellm-rust/crates/core/src/error.rs
@@ -1,9 +1,7 @@
-use thiserror::Error;
+use thiserror::Error as ThisError;
 
-pub type CoreResult<T> = Result<T, CoreError>;
-
-#[derive(Debug, Error, PartialEq, Eq)]
-pub enum CoreError {
+#[derive(Debug, ThisError, PartialEq, Eq)]
+pub enum Error {
     #[error("expected {expected}, got {actual}")]
     InvalidType {
         expected: &'static str,
diff --git a/litellm-rust/crates/core/src/http_utils.rs b/litellm-rust/crates/core/src/http_utils.rs
index c541f50275b..10661fadf96 100644
--- a/litellm-rust/crates/core/src/http_utils.rs
+++ b/litellm-rust/crates/core/src/http_utils.rs
@@ -3,7 +3,7 @@
 use serde_json::{Map, Value};
 
 use crate::constants::UPSTREAM_ERROR_BODY_MAX_CHARS;
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 
 /// Bound an upstream error body before it crosses a host boundary, so provider
 /// bodies stay data-minimized.
@@ -18,7 +18,7 @@ pub fn truncate_error_body(body: &str) -> String {
 pub fn string_headers(
     context: &'static str,
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     extra_headers
         .unwrap_or_default()
         .into_iter()
@@ -27,7 +27,7 @@ pub fn string_headers(
                 .as_str()
                 .map(|value| (key.clone(), value.to_string()))
                 .ok_or_else(|| {
-                    CoreError::InvalidRequest(format!(
+                    Error::InvalidRequest(format!(
                         "{context} extra_headers.{key} must be a string, got {}",
                         json_type_name(&value)
                     ))
@@ -81,7 +81,7 @@ mod tests {
         let err = string_headers("chat completions", Some(headers)).expect_err("non-string value");
         assert_eq!(
             err,
-            CoreError::InvalidRequest(
+            Error::InvalidRequest(
                 "chat completions extra_headers.x-trace must be a string, got number".to_string()
             )
         );
diff --git a/litellm-rust/crates/core/src/lib.rs b/litellm-rust/crates/core/src/lib.rs
index dce4a425ea0..0e18d24e5d8 100644
--- a/litellm-rust/crates/core/src/lib.rs
+++ b/litellm-rust/crates/core/src/lib.rs
@@ -13,4 +13,4 @@ pub mod responses;
 pub mod router;
 pub mod routing_utils;
 
-pub use error::{CoreError, CoreResult};
+pub use error::Error;
diff --git a/litellm-rust/crates/core/src/messages/common_utils.rs b/litellm-rust/crates/core/src/messages/common_utils.rs
index a14dffbc1fe..8dfdb2e361a 100644
--- a/litellm-rust/crates/core/src/messages/common_utils.rs
+++ b/litellm-rust/crates/core/src/messages/common_utils.rs
@@ -1,9 +1,8 @@
-use serde_json::{Map, Value};
-
-use crate::error::CoreResult;
+use crate::Error;
 use crate::http_utils::string_headers as shared_string_headers;
 use crate::providers::anthropic::messages::transformation::ANTHROPIC_MESSAGES_CONFIG;
 use crate::providers::azure_ai::messages::transformation::AZURE_ANTHROPIC_MESSAGES_CONFIG;
+use serde_json::{Map, Value};
 
 use super::transformation::AnthropicMessagesProviderConfig;
 
@@ -23,6 +22,6 @@ pub(super) fn messages_provider_config(
 
 pub(super) fn string_headers(
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     shared_string_headers(HEADER_CONTEXT, extra_headers)
 }
diff --git a/litellm-rust/crates/core/src/messages/handler.rs b/litellm-rust/crates/core/src/messages/handler.rs
index 1c895f66eba..13a65d86131 100644
--- a/litellm-rust/crates/core/src/messages/handler.rs
+++ b/litellm-rust/crates/core/src/messages/handler.rs
@@ -1,5 +1,5 @@
 use crate::constants::ANTHROPIC_MESSAGES_PROVIDER;
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 
 use super::client::http_client;
 use super::common_utils::truncate_error_body;
@@ -7,7 +7,7 @@ use super::types::{AnthropicMessagesResponse, ProviderMessagesRequest};
 
 pub(super) async fn execute_messages_provider_call(
     request: ProviderMessagesRequest,
-) -> CoreResult<AnthropicMessagesResponse> {
+) -> Result<AnthropicMessagesResponse, Error> {
     let mut request_builder = http_client().post(&request.url).json(&request.body);
     for (key, value) in &request.upstream_headers {
         request_builder = request_builder.header(key, value);
@@ -19,32 +19,31 @@ pub(super) async fn execute_messages_provider_call(
     let response = request_builder
         .send()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     let status = response.status();
     let text = response
         .text()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     if !status.is_success() {
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
     }
 
-    let response = serde_json::from_str(&text).map_err(|err| {
-        CoreError::InvalidResponse(format!("invalid messages response JSON: {err}"))
-    })?;
+    let response = serde_json::from_str(&text)
+        .map_err(|err| Error::InvalidResponse(format!("invalid messages response JSON: {err}")))?;
     request.config.transform_response(&request.model, response)
 }
 
 pub(super) async fn execute_messages_provider_stream(
     request: ProviderMessagesRequest,
-) -> CoreResult<reqwest::Response> {
+) -> Result<reqwest::Response, Error> {
     if request.provider != ANTHROPIC_MESSAGES_PROVIDER {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "streaming messages is not supported for this provider".to_string(),
         ));
     }
@@ -60,14 +59,14 @@ pub(super) async fn execute_messages_provider_stream(
     let response = request_builder
         .send()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     let status = response.status();
     if !status.is_success() {
         let text = response
             .text()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
-        return Err(CoreError::Http {
+            .map_err(|err| Error::Network(err.to_string()))?;
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
diff --git a/litellm-rust/crates/core/src/messages/mod.rs b/litellm-rust/crates/core/src/messages/mod.rs
index acb36d89daf..ee2877e61fc 100644
--- a/litellm-rust/crates/core/src/messages/mod.rs
+++ b/litellm-rust/crates/core/src/messages/mod.rs
@@ -7,6 +7,7 @@
 //! is the streaming variant; it hands the raw upstream response back so a host
 //! can splice the event stream to its own caller.
 
+use crate::Error;
 mod client;
 mod common_utils;
 mod handler;
@@ -14,17 +15,15 @@ mod prepare;
 pub mod transformation;
 pub mod types;
 
-use crate::error::CoreResult;
-
 use handler::{execute_messages_provider_call, execute_messages_provider_stream};
 use prepare::prepare_messages_call;
 use types::{AnthropicMessagesResponse, MessagesRequest};
 
-pub async fn messages(request: MessagesRequest<'_>) -> CoreResult<AnthropicMessagesResponse> {
+pub async fn messages(request: MessagesRequest<'_>) -> Result<AnthropicMessagesResponse, Error> {
     execute_messages_provider_call(prepare_messages_call(request)?).await
 }
 
-pub async fn messages_stream(request: MessagesRequest<'_>) -> CoreResult<reqwest::Response> {
+pub async fn messages_stream(request: MessagesRequest<'_>) -> Result<reqwest::Response, Error> {
     execute_messages_provider_stream(prepare_messages_call(request)?).await
 }
 
diff --git a/litellm-rust/crates/core/src/messages/prepare.rs b/litellm-rust/crates/core/src/messages/prepare.rs
index 94b5b1eaed7..3b253ac3766 100644
--- a/litellm-rust/crates/core/src/messages/prepare.rs
+++ b/litellm-rust/crates/core/src/messages/prepare.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::routing_utils::provider::{CustomLlmProvider, get_custom_llm_provider};
 
 use super::common_utils::{has_bearer_auth, has_header, messages_provider_config, string_headers};
@@ -7,7 +7,7 @@ use super::types::{MessagesRequest, ProviderMessagesRequest};
 
 pub(super) fn prepare_messages_call(
     request: MessagesRequest<'_>,
-) -> CoreResult<ProviderMessagesRequest> {
+) -> Result<ProviderMessagesRequest, Error> {
     let provider_info = get_custom_llm_provider(request.model, request.custom_llm_provider)
         .or_else(|| {
             request
@@ -18,7 +18,7 @@ pub(super) fn prepare_messages_call(
                 })
         })
         .ok_or_else(|| {
-            CoreError::InvalidProvider(
+            Error::InvalidProvider(
                 "unable to resolve custom_llm_provider for messages request".to_string(),
             )
         })?;
@@ -26,7 +26,7 @@ pub(super) fn prepare_messages_call(
     let provider = provider_info.custom_llm_provider;
 
     let config = messages_provider_config(provider)
-        .ok_or_else(|| CoreError::InvalidProvider(provider.to_string()))?;
+        .ok_or_else(|| Error::InvalidProvider(provider.to_string()))?;
     let env_lookup = |key: &str| std::env::var(key).ok();
 
     let mut headers = string_headers(request.extra_headers)?;
@@ -53,11 +53,11 @@ pub(super) fn prepare_messages_call(
 
     let url = config.complete_url(request.api_base, &model, &env_lookup)?;
     let typed_request = serde_json::from_value(request.body).map_err(|err| {
-        CoreError::InvalidRequest(format!("invalid Anthropic messages request: {err}"))
+        Error::InvalidRequest(format!("invalid Anthropic messages request: {err}"))
     })?;
     let transformed = config.transform_request(typed_request)?;
     let body = serde_json::to_value(transformed).map_err(|err| {
-        CoreError::InvalidRequest(format!(
+        Error::InvalidRequest(format!(
             "failed to serialize Anthropic messages request: {err}"
         ))
     })?;
diff --git a/litellm-rust/crates/core/src/messages/tests.rs b/litellm-rust/crates/core/src/messages/tests.rs
index 9fc1763683b..df9f7051011 100644
--- a/litellm-rust/crates/core/src/messages/tests.rs
+++ b/litellm-rust/crates/core/src/messages/tests.rs
@@ -4,7 +4,7 @@ use serde_json::{Map, Value, json};
 use tokio::io::{AsyncReadExt, AsyncWriteExt};
 use tokio::net::{TcpListener, TcpStream};
 
-use crate::error::CoreError;
+use crate::error::Error;
 
 use super::common_utils::{
     has_bearer_auth, has_header, messages_provider_config, string_headers, truncate_error_body,
@@ -77,7 +77,7 @@ fn truncate_error_body_caps_long_payloads() {
 fn string_headers_rejects_non_string_values() {
     let headers = json!({"x-count": 3}).as_object().unwrap().clone();
     let err = string_headers(Some(headers)).expect_err("non-string header rejected");
-    assert!(matches!(err, CoreError::InvalidRequest(_)));
+    assert!(matches!(err, Error::InvalidRequest(_)));
 }
 
 #[test]
@@ -341,7 +341,7 @@ async fn messages_requires_auth_when_no_key_and_no_header() {
     .await
     .expect_err("missing auth errors");
 
-    assert!(matches!(err, CoreError::Auth(_)));
+    assert!(matches!(err, Error::Auth(_)));
 }
 
 #[tokio::test]
@@ -420,7 +420,7 @@ async fn messages_maps_provider_error_status_to_http_error() {
     .await
     .expect_err("provider error propagates");
 
-    assert!(matches!(err, CoreError::Http { status: 401, .. }));
+    assert!(matches!(err, Error::Http { status: 401, .. }));
 }
 
 #[tokio::test]
@@ -437,5 +437,5 @@ async fn messages_rejects_unsupported_provider() {
     .await
     .expect_err("unsupported provider errors");
 
-    assert!(matches!(err, CoreError::InvalidProvider(provider) if provider == "openai"));
+    assert!(matches!(err, Error::InvalidProvider(provider) if provider == "openai"));
 }
diff --git a/litellm-rust/crates/core/src/messages/transformation.rs b/litellm-rust/crates/core/src/messages/transformation.rs
index b478e20d24b..673a5728aca 100644
--- a/litellm-rust/crates/core/src/messages/transformation.rs
+++ b/litellm-rust/crates/core/src/messages/transformation.rs
@@ -1,6 +1,5 @@
-use crate::error::CoreResult;
-
 use super::types::{AnthropicMessagesRequest, AnthropicMessagesResponse};
+use crate::Error;
 
 #[derive(Clone, Copy, Debug, PartialEq, Eq)]
 pub enum MessagesAuthStrategy {
@@ -23,13 +22,13 @@ pub trait AnthropicMessagesProviderConfig: Sync {
         api_base: Option<&str>,
         model: &str,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn resolve_api_key(
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn auth_strategy(&self) -> MessagesAuthStrategy {
         MessagesAuthStrategy::Header("x-api-key")
@@ -49,7 +48,7 @@ pub trait AnthropicMessagesProviderConfig: Sync {
     fn transform_request(
         &self,
         request: AnthropicMessagesRequest,
-    ) -> CoreResult<AnthropicMessagesRequest> {
+    ) -> Result<AnthropicMessagesRequest, Error> {
         Ok(request)
     }
 
@@ -57,7 +56,7 @@ pub trait AnthropicMessagesProviderConfig: Sync {
         &self,
         _model: &str,
         response: AnthropicMessagesResponse,
-    ) -> CoreResult<AnthropicMessagesResponse> {
+    ) -> Result<AnthropicMessagesResponse, Error> {
         Ok(response)
     }
 }
diff --git a/litellm-rust/crates/core/src/ocr/transformation.rs b/litellm-rust/crates/core/src/ocr/transformation.rs
index cb3e735e533..3d3c16c8cb6 100644
--- a/litellm-rust/crates/core/src/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/ocr/transformation.rs
@@ -1,7 +1,6 @@
+use crate::Error;
 use serde_json::{Map, Value};
 
-use crate::CoreResult;
-
 use super::types::{OcrRequestData, OcrResponseData};
 
 #[derive(Clone, Copy, Debug, PartialEq, Eq)]
@@ -43,13 +42,13 @@ pub trait OcrProviderConfig: Sync {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData>;
+    ) -> Result<OcrRequestData, Error>;
 
     fn transform_ocr_response(
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData>;
+    ) -> Result<OcrResponseData, Error>;
 
     fn complete_url(
         &self,
@@ -57,13 +56,13 @@ pub trait OcrProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn resolve_api_key(
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn auth_strategy(&self) -> OcrAuthStrategy {
         OcrAuthStrategy::Bearer
diff --git a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs
index 4534ac0182c..b22de6c47de 100644
--- a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs
+++ b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs
@@ -1,4 +1,5 @@
 use super::*;
+use crate::Error;
 use serde_json::json;
 
 fn messages(value: Value) -> Vec<ChatMessage> {
@@ -19,7 +20,7 @@ fn transform(model: &str, msgs: Value, opts: Value) -> Value {
         .body
 }
 
-fn transform_response(body: Value) -> CoreResult<ChatCompletionsResponse> {
+fn transform_response(body: Value) -> Result<ChatCompletionsResponse, Error> {
     ANTHROPIC_CHAT_COMPLETIONS_CONFIG
         .transform_response("claude-sonnet-4-5", ProviderChatResponseData { body })
 }
@@ -390,29 +391,26 @@ fn declines_a_response_carrying_a_non_text_block() {
         "usage": {"input_tokens": 1, "output_tokens": 1}
     }))
     .expect_err("non-text block");
-    assert_eq!(
-        err,
-        CoreError::Unsupported("non-text response content block")
-    );
+    assert_eq!(err, Error::Unsupported("non-text response content block"));
 }
 
 #[test]
 fn errors_on_a_response_missing_required_fields() {
     assert_eq!(
         transform_response(json!("nope")).expect_err("not an object"),
-        CoreError::InvalidResponse("messages response is not an object".to_string())
+        Error::InvalidResponse("messages response is not an object".to_string())
     );
     assert_eq!(
         transform_response(json!({"model": "m", "usage": {}})).expect_err("no content"),
-        CoreError::MissingField("content")
+        Error::MissingField("content")
     );
     assert_eq!(
         transform_response(json!({"model": "m", "content": []})).expect_err("no usage"),
-        CoreError::MissingField("usage")
+        Error::MissingField("usage")
     );
     assert_eq!(
         transform_response(json!({"content": [], "usage": {}})).expect_err("no model"),
-        CoreError::MissingField("model")
+        Error::MissingField("model")
     );
 }
 
diff --git a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs
index 3658642b539..97cc48aa6f2 100644
--- a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs
@@ -10,7 +10,7 @@ use crate::chat_completions::types::{
     ProviderChatRequestData, ProviderChatResponseData,
 };
 use crate::constants::ANTHROPIC_OAUTH_TOKEN_PREFIX;
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::providers::anthropic::messages::transformation::{
     complete_anthropic_url, resolve_anthropic_api_key,
 };
@@ -74,7 +74,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         _model: &str,
         _optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         Ok(complete_anthropic_url(api_base, env_lookup))
     }
 
@@ -84,7 +84,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         _model: &str,
         _optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<ChatCompletionsAuth> {
+    ) -> Result<ChatCompletionsAuth, Error> {
         Ok(ChatCompletionsAuth::Header {
             name: "x-api-key",
             value: resolve_anthropic_api_key(api_key, env_lookup)?,
@@ -137,7 +137,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         model: &str,
         messages: Vec<ChatMessage>,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<ProviderChatRequestData> {
+    ) -> Result<ProviderChatRequestData, Error> {
         Ok(ProviderChatRequestData {
             body: anthropic_body(model, &build_conversation(&messages), optional_params),
         })
@@ -147,15 +147,16 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         &self,
         _model: &str,
         response: ProviderChatResponseData,
-    ) -> CoreResult<ChatCompletionsResponse> {
-        let body = response.body.as_object().ok_or_else(|| {
-            CoreError::InvalidResponse("messages response is not an object".into())
-        })?;
+    ) -> Result<ChatCompletionsResponse, Error> {
+        let body = response
+            .body
+            .as_object()
+            .ok_or_else(|| Error::InvalidResponse("messages response is not an object".into()))?;
 
         let content = body
             .get("content")
             .and_then(Value::as_array)
-            .ok_or(CoreError::MissingField("content"))?;
+            .ok_or(Error::MissingField("content"))?;
         // The route declines tool and thinking requests, so a non-text block
         // means the response carries something this path never asked for.
         // Decline rather than silently dropping it; the host falls back.
@@ -163,7 +164,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
             .iter()
             .any(|block| block.get("type").and_then(Value::as_str) != Some("text"))
         {
-            return Err(CoreError::Unsupported("non-text response content block"));
+            return Err(Error::Unsupported("non-text response content block"));
         }
         let text: String = content
             .iter()
@@ -173,7 +174,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         let usage = body
             .get("usage")
             .and_then(Value::as_object)
-            .ok_or(CoreError::MissingField("usage"))?;
+            .ok_or(Error::MissingField("usage"))?;
         let field = |name: &str| usage.get(name).and_then(Value::as_u64).unwrap_or(0);
 
         Ok(ChatCompletionsResponse {
@@ -181,7 +182,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
             model: body
                 .get("model")
                 .and_then(Value::as_str)
-                .ok_or(CoreError::MissingField("model"))?
+                .ok_or(Error::MissingField("model"))?
                 .to_string(),
             choices: vec![ChatCompletionsChoice {
                 index: 0,
diff --git a/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs b/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs
index 829f2260d3c..8fcc0f36c7d 100644
--- a/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::messages::transformation::{AnthropicMessagesProviderConfig, MessagesAuthStrategy};
 
 const ANTHROPIC_API_KEY_ENV: &str = "ANTHROPIC_API_KEY";
@@ -17,12 +17,12 @@ pub fn non_empty(value: Option<&str>) -> Option<&str> {
 pub fn resolve_anthropic_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     non_empty(api_key)
         .map(str::to_string)
         .or_else(|| env_lookup(ANTHROPIC_API_KEY_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Anthropic API Key - Set `api_key` or the ANTHROPIC_API_KEY \
                  environment variable"
                     .to_string(),
@@ -52,7 +52,7 @@ impl AnthropicMessagesProviderConfig for AnthropicMessagesConfig {
         api_base: Option<&str>,
         _model: &str,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         Ok(complete_anthropic_url(api_base, env_lookup))
     }
 
@@ -60,7 +60,7 @@ impl AnthropicMessagesProviderConfig for AnthropicMessagesConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_anthropic_api_key(api_key, env_lookup)
     }
 
@@ -121,7 +121,7 @@ mod tests {
         );
         assert!(matches!(
             resolve_anthropic_api_key(None, &|_| None).expect_err("missing key"),
-            CoreError::Auth(_)
+            Error::Auth(_)
         ));
     }
 
diff --git a/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs b/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs
index 7b958c77ba3..70dad0300f1 100644
--- a/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::messages::transformation::{AnthropicMessagesProviderConfig, MessagesAuthStrategy};
 use crate::messages::types::{
     AnthropicMessage, AnthropicMessagesRequest, AnthropicMessagesResponse, ContentBlock,
@@ -28,12 +28,12 @@ pub const AZURE_ANTHROPIC_MESSAGES_CONFIG: AzureAnthropicMessagesConfig =
 pub fn resolve_azure_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     non_empty(api_key)
         .map(str::to_string)
         .or_else(|| env_lookup(AZURE_API_KEY_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Azure API Key - Set `api_key` or the AZURE_API_KEY environment variable"
                     .to_string(),
             )
@@ -43,12 +43,12 @@ pub fn resolve_azure_api_key(
 pub fn complete_azure_anthropic_url(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let api_base = non_empty(api_base)
         .map(str::to_string)
         .or_else(|| env_lookup(AZURE_API_BASE_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Azure API Base - Set `api_base` or the AZURE_API_BASE environment variable. \
                  Expected format: https://<resource-name>.services.ai.azure.com/anthropic"
                     .to_string(),
@@ -147,7 +147,7 @@ impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
         api_base: Option<&str>,
         _model: &str,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_azure_anthropic_url(api_base, env_lookup)
     }
 
@@ -155,7 +155,7 @@ impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_azure_api_key(api_key, env_lookup)
     }
 
@@ -174,7 +174,7 @@ impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
     fn transform_request(
         &self,
         request: AnthropicMessagesRequest,
-    ) -> CoreResult<AnthropicMessagesRequest> {
+    ) -> Result<AnthropicMessagesRequest, Error> {
         let mut request = fold_system_role_messages(request);
         if let Some(system) = request.system.as_mut() {
             strip_scope_from_system(system);
@@ -190,7 +190,7 @@ impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
         &self,
         model: &str,
         response: AnthropicMessagesResponse,
-    ) -> CoreResult<AnthropicMessagesResponse> {
+    ) -> Result<AnthropicMessagesResponse, Error> {
         self.anthropic.transform_response(model, response)
     }
 }
@@ -268,7 +268,7 @@ mod tests {
             "https://env.services.ai.azure.com/anthropic/v1/messages"
         );
         let err = complete_azure_anthropic_url(Some("  "), &|_| None).expect_err("missing base");
-        assert!(matches!(err, CoreError::Auth(_)));
+        assert!(matches!(err, Error::Auth(_)));
     }
 
     #[test]
@@ -284,7 +284,7 @@ mod tests {
         );
         assert!(matches!(
             resolve_azure_api_key(None, &|_| None).expect_err("missing key"),
-            CoreError::Auth(_)
+            Error::Auth(_)
         ));
     }
 
diff --git a/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs b/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs
index eabd15677cc..b26a7925e8a 100644
--- a/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs
@@ -1,6 +1,6 @@
 use std::collections::BTreeSet;
 
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 use crate::ocr::transformation::{OcrAuthStrategy, OcrProviderConfig, OcrResponseHandling};
 use crate::ocr::types::{OcrRequestData, OcrResponseData};
 use serde_json::{Map, Value, json};
@@ -32,17 +32,17 @@ fn resolve_value(
     env_name: &str,
     env_lookup: &dyn Fn(&str) -> Option<String>,
     missing_message: &str,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     non_empty(explicit)
         .map(str::to_string)
         .or_else(|| env_lookup(env_name).filter(|value| !value.trim().is_empty()))
-        .ok_or_else(|| CoreError::Auth(missing_message.to_string()))
+        .ok_or_else(|| Error::Auth(missing_message.to_string()))
 }
 
 pub fn resolve_azure_ai_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_key,
         AZURE_AI_API_KEY_ENV,
@@ -54,7 +54,7 @@ pub fn resolve_azure_ai_api_key(
 pub fn resolve_azure_ai_api_base(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_base,
         AZURE_AI_API_BASE_ENV,
@@ -66,7 +66,7 @@ pub fn resolve_azure_ai_api_base(
 pub fn complete_azure_ai_url(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let base = resolve_azure_ai_api_base(api_base, env_lookup)?;
     Ok(format!(
         "{}/providers/mistral/azure/ocr",
@@ -77,7 +77,7 @@ pub fn complete_azure_ai_url(
 pub fn resolve_document_intelligence_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_key,
         AZURE_DOCUMENT_INTELLIGENCE_API_KEY_ENV,
@@ -89,7 +89,7 @@ pub fn resolve_document_intelligence_api_key(
 pub fn resolve_document_intelligence_endpoint(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_base,
         AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT_ENV,
@@ -127,7 +127,7 @@ fn pages_token_is_valid(token: &str) -> bool {
     }
 }
 
-fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
+fn normalize_pages_param(pages: &Value) -> Result<Option<String>, Error> {
     match pages {
         Value::String(value) => {
             let normalized = value
@@ -138,7 +138,7 @@ fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
             if normalized.split(',').all(pages_token_is_valid) {
                 Ok(Some(normalized))
             } else {
-                Err(CoreError::InvalidRequest(format!(
+                Err(Error::InvalidRequest(format!(
                     "Invalid `pages` string for Azure Document Intelligence: {value:?}. Expected format like '1-3,5,7-9'."
                 )))
             }
@@ -152,7 +152,7 @@ fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
                 for value in values {
                     let page = value.as_i64().expect("checked is_i64");
                     if page < 0 {
-                        return Err(CoreError::InvalidRequest(
+                        return Err(Error::InvalidRequest(
                             "`pages` integers must be >= 0 (Mistral 0-based indices)".to_string(),
                         ));
                     }
@@ -176,16 +176,16 @@ fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
                 if normalized.split(',').all(pages_token_is_valid) {
                     return Ok(Some(normalized));
                 }
-                return Err(CoreError::InvalidRequest(format!(
+                return Err(Error::InvalidRequest(format!(
                     "Invalid `pages` list for Azure Document Intelligence: {values:?}. Expected tokens like '1' or '3-5'."
                 )));
             }
-            Err(CoreError::InvalidRequest(
+            Err(Error::InvalidRequest(
                 "`pages` must be a list[int] (0-based, Mistral-style) or a string like '1-3,5,7-9'."
                     .to_string(),
             ))
         }
-        _ => Err(CoreError::InvalidRequest(
+        _ => Err(Error::InvalidRequest(
             "`pages` must be a list[int] (0-based, Mistral-style) or a string like '1-3,5,7-9'."
                 .to_string(),
         )),
@@ -197,7 +197,7 @@ pub fn complete_document_intelligence_url(
     model: &str,
     optional_params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let endpoint = resolve_document_intelligence_endpoint(api_base, env_lookup)?;
     let mut url = format!(
         "{}/documentintelligence/documentModels/{}:analyze?api-version={}",
@@ -216,20 +216,20 @@ pub fn complete_document_intelligence_url(
     Ok(url)
 }
 
-fn document_url_from_mistral_document(document: &Value) -> CoreResult<&str> {
-    let object = document.as_object().ok_or_else(|| CoreError::InvalidType {
+fn document_url_from_mistral_document(document: &Value) -> Result<&str, Error> {
+    let object = document.as_object().ok_or_else(|| Error::InvalidType {
         expected: "object",
         actual: json_type_name(document),
     })?;
     let doc_type = object
         .get("type")
         .and_then(Value::as_str)
-        .ok_or(CoreError::MissingField("document.type"))?;
+        .ok_or(Error::MissingField("document.type"))?;
     let field_name = match doc_type {
         "document_url" => "document_url",
         "image_url" => "image_url",
         other => {
-            return Err(CoreError::InvalidRequest(format!(
+            return Err(Error::InvalidRequest(format!(
                 "Invalid document type: {other}. Must be 'document_url' or 'image_url'"
             )));
         }
@@ -238,7 +238,7 @@ fn document_url_from_mistral_document(document: &Value) -> CoreResult<&str> {
         .get(field_name)
         .and_then(Value::as_str)
         .filter(|value| !value.is_empty())
-        .ok_or(CoreError::MissingField(field_name))
+        .ok_or(Error::MissingField(field_name))
 }
 
 fn extract_base64_from_data_uri(data_uri: &str) -> &str {
@@ -290,7 +290,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_request(model, document, optional_params)
     }
 
@@ -298,7 +298,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_response(model, response_json)
     }
 
@@ -308,7 +308,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         _model: &str,
         _optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_azure_ai_url(api_base, env_lookup)
     }
 
@@ -316,7 +316,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_azure_ai_api_key(api_key, env_lookup)
     }
 
@@ -335,7 +335,7 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         _model: &str,
         document: Value,
         _optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         let document_url = document_url_from_mistral_document(&document)?;
         let mut data = Map::new();
         if document_url.starts_with("data:") {
@@ -359,19 +359,19 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         let response = response_json
             .as_object()
-            .ok_or_else(|| CoreError::InvalidType {
+            .ok_or_else(|| Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&response_json),
             })?;
         let status = response
             .get("status")
             .and_then(Value::as_str)
-            .ok_or(CoreError::MissingField("status"))?;
+            .ok_or(Error::MissingField("status"))?;
         if status != "succeeded" {
-            return Err(CoreError::InvalidResponse(format!(
+            return Err(Error::InvalidResponse(format!(
                 "Azure Document Intelligence analysis failed with status: {status}"
             )));
         }
@@ -414,7 +414,7 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_document_intelligence_url(api_base, model, optional_params, env_lookup)
     }
 
@@ -422,7 +422,7 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_document_intelligence_api_key(api_key, env_lookup)
     }
 
diff --git a/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs b/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs
index 5e885734182..bb4f6afe5f9 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs
@@ -6,7 +6,7 @@ use crate::audio_transcription::transformation::{
 use crate::audio_transcription::types::{
     AudioTranscriptionRequestData, AudioTranscriptionResponseData,
 };
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 
 pub use super::aws_base::{aws_auth_config, bedrock_model_id_and_region, resolve_bedrock_region};
 use super::constants::{BEDROCK_RUNTIME_ENDPOINT_TEMPLATE, BEDROCK_SERVICE};
@@ -18,8 +18,8 @@ pub static BEDROCK_AUDIO_TRANSCRIPTION_CONFIG: BedrockAudioTranscriptionConfig =
 
 pub struct BedrockAudioTranscriptionConfig;
 
-fn audio_fields(audio: Value) -> CoreResult<(String, String)> {
-    let object = audio.as_object().ok_or_else(|| CoreError::InvalidType {
+fn audio_fields(audio: Value) -> Result<(String, String), Error> {
+    let object = audio.as_object().ok_or_else(|| Error::InvalidType {
         expected: "object",
         actual: json_type_name(&audio),
     })?;
@@ -27,13 +27,13 @@ fn audio_fields(audio: Value) -> CoreResult<(String, String)> {
         .get("data")
         .and_then(Value::as_str)
         .filter(|value| !value.is_empty())
-        .ok_or(CoreError::MissingField("audio.data"))?;
+        .ok_or(Error::MissingField("audio.data"))?;
     let format = object
         .get("format")
         .and_then(Value::as_str)
         .filter(|value| matches!(*value, "wav" | "mp3" | "flac" | "ogg"))
         .ok_or_else(|| {
-            CoreError::InvalidRequest("audio.format must be wav, mp3, flac, or ogg".to_string())
+            Error::InvalidRequest("audio.format must be wav, mp3, flac, or ogg".to_string())
         })?;
     Ok((data.to_string(), format.to_string()))
 }
@@ -55,7 +55,7 @@ impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
         _model: &str,
         audio: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<AudioTranscriptionRequestData> {
+    ) -> Result<AudioTranscriptionRequestData, Error> {
         let (data, format) = audio_fields(audio)?;
         let mut instruction = "Transcribe the audio. Respond with only the transcript.".to_string();
         if let Some(language) = optional_string(&optional_params, "language") {
@@ -87,14 +87,14 @@ impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
         &self,
         _model: &str,
         response_json: Value,
-    ) -> CoreResult<AudioTranscriptionResponseData> {
+    ) -> Result<AudioTranscriptionResponseData, Error> {
         let content = response_json
             .get("output")
             .and_then(|value| value.get("message"))
             .and_then(|value| value.get("content"))
             .and_then(Value::as_array)
             .ok_or_else(|| {
-                CoreError::InvalidResponse("Bedrock response has no output content".to_string())
+                Error::InvalidResponse("Bedrock response has no output content".to_string())
             })?;
         let mut text = String::new();
         for block in content {
@@ -111,7 +111,7 @@ impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         let (model_id, model_region) = bedrock_model_id_and_region(model);
         let region = resolve_bedrock_region(model_region.as_deref(), optional_params, env_lookup);
         let endpoint = optional_params
@@ -133,7 +133,7 @@ impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<AudioTranscriptionAuth> {
+    ) -> Result<AudioTranscriptionAuth, Error> {
         let (_, model_region) = bedrock_model_id_and_region(model);
         Ok(AudioTranscriptionAuth::AwsSigV4 {
             region: resolve_bedrock_region(model_region.as_deref(), optional_params, env_lookup),
diff --git a/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs b/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs
index b11639aa09b..e5e52bfce95 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs
@@ -4,7 +4,7 @@ use std::time::Duration;
 use std::time::{SystemTime, UNIX_EPOCH};
 
 use crate::caching::in_memory_cache::InMemoryCache;
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use aws_credential_types::Credentials;
 use aws_credential_types::provider::ProvideCredentials;
 use aws_sigv4::http_request::{
@@ -197,7 +197,7 @@ pub fn classify_auth(
 pub async fn resolve_credentials(
     config: AwsAuthConfig,
     env_lookup: &(dyn Fn(&str) -> Option<String> + Sync),
-) -> CoreResult<Credentials> {
+) -> Result<Credentials, Error> {
     let resolved = config.clone().with_environment(env_lookup);
     let flow = classify_auth(config, env_lookup);
     match flow {
@@ -244,9 +244,10 @@ pub async fn resolve_credentials(
             let provider = aws_config::profile::ProfileFileCredentialsProvider::builder()
                 .profile_name(name)
                 .build();
-            provider.provide_credentials().await.map_err(|error| {
-                CoreError::Auth(format!("AWS profile credentials failed: {error}"))
-            })
+            provider
+                .provide_credentials()
+                .await
+                .map_err(|error| Error::Auth(format!("AWS profile credentials failed: {error}")))
         }
         AwsAuthFlow::AssumeRole { role, session_name } => {
             if is_already_running_as_role(&role, &resolved).await? {
@@ -260,7 +261,7 @@ pub async fn resolve_credentials(
                         .build()
                         .await;
                 let credentials = provider.provide_credentials().await.map_err(|error| {
-                    CoreError::Auth(format!("AWS default credentials failed: {error}"))
+                    Error::Auth(format!("AWS default credentials failed: {error}"))
                 })?;
                 set_cached_credentials(
                     key,
@@ -301,7 +302,7 @@ pub async fn resolve_credentials(
             provider
                 .provide_credentials()
                 .await
-                .map_err(|error| CoreError::Auth(format!("AWS role credentials failed: {error}")))
+                .map_err(|error| Error::Auth(format!("AWS role credentials failed: {error}")))
         }
         AwsAuthFlow::WebIdentity {
             token,
@@ -325,13 +326,13 @@ pub async fn resolve_credentials(
                 .send()
                 .await
                 .map_err(|error| {
-                    CoreError::Auth(format!("AWS web identity credentials failed: {error}"))
+                    Error::Auth(format!("AWS web identity credentials failed: {error}"))
                 })?;
             let credentials = response.credentials().ok_or_else(|| {
-                CoreError::Auth("AWS web identity response had no credentials".to_string())
+                Error::Auth("AWS web identity response had no credentials".to_string())
             })?;
             let expiration = SystemTime::try_from(*credentials.expiration()).map_err(|error| {
-                CoreError::Auth(format!("AWS web identity expiration was invalid: {error}"))
+                Error::Auth(format!("AWS web identity expiration was invalid: {error}"))
             })?;
             Ok(Credentials::new(
                 credentials.access_key_id(),
@@ -350,9 +351,10 @@ pub async fn resolve_credentials(
                 aws_config::default_provider::credentials::DefaultCredentialsChain::builder()
                     .build()
                     .await;
-            let credentials = provider.provide_credentials().await.map_err(|error| {
-                CoreError::Auth(format!("AWS default credentials failed: {error}"))
-            })?;
+            let credentials = provider
+                .provide_credentials()
+                .await
+                .map_err(|error| Error::Auth(format!("AWS default credentials failed: {error}")))?;
             set_cached_credentials(
                 key,
                 credentials.clone(),
@@ -363,7 +365,7 @@ pub async fn resolve_credentials(
     }
 }
 
-async fn is_already_running_as_role(role: &str, config: &AwsAuthConfig) -> CoreResult<bool> {
+async fn is_already_running_as_role(role: &str, config: &AwsAuthConfig) -> Result<bool, Error> {
     if role_identity(role).is_none() {
         return Ok(false);
     }
@@ -437,7 +439,7 @@ pub fn sign_bedrock_post(
     region: &str,
     credentials: &Credentials,
     signing_time: SystemTime,
-) -> CoreResult<BTreeMap<String, String>> {
+) -> Result<BTreeMap<String, String>, Error> {
     let identity: Identity = credentials.clone().into();
     let params = v4::SigningParams::builder()
         .identity(&identity)
@@ -447,14 +449,14 @@ pub fn sign_bedrock_post(
         .settings(SigningSettings::default())
         .build()
         .map(SigningParams::from)
-        .map_err(|error| CoreError::Auth(format!("AWS signing parameters failed: {error}")))?;
+        .map_err(|error| Error::Auth(format!("AWS signing parameters failed: {error}")))?;
     let header_refs = headers
         .iter()
         .map(|(name, value)| (name.as_str(), value.as_str()));
     let request = SignableRequest::new("POST", url, header_refs, SignableBody::Bytes(body))
-        .map_err(|error| CoreError::Auth(format!("AWS signable request failed: {error}")))?;
+        .map_err(|error| Error::Auth(format!("AWS signable request failed: {error}")))?;
     let (instructions, _) = sign(request, &params)
-        .map_err(|error| CoreError::Auth(format!("AWS request signing failed: {error}")))?
+        .map_err(|error| Error::Auth(format!("AWS request signing failed: {error}")))?
         .into_parts();
     Ok(instructions
         .headers()
diff --git a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs
index 4b75dcb8e9d..c86f061b9ca 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs
@@ -1,4 +1,5 @@
 use super::*;
+use crate::Error;
 use serde_json::json;
 
 fn messages(value: Value) -> Vec<ChatMessage> {
@@ -23,7 +24,7 @@ fn transform(msgs: Value, opts: Value) -> Value {
         .body
 }
 
-fn transform_response(body: Value) -> CoreResult<ChatCompletionsResponse> {
+fn transform_response(body: Value) -> Result<ChatCompletionsResponse, Error> {
     BEDROCK_CHAT_COMPLETIONS_CONFIG.transform_response(
         "anthropic.claude-sonnet-4-5-v1:0",
         ProviderChatResponseData { body },
@@ -478,25 +479,22 @@ fn declines_a_response_carrying_a_tool_use_block() {
         "usage": {"inputTokens": 1, "outputTokens": 1}
     }))
     .expect_err("tool use block");
-    assert_eq!(
-        err,
-        CoreError::Unsupported("non-text response content block")
-    );
+    assert_eq!(err, Error::Unsupported("non-text response content block"));
 }
 
 #[test]
 fn errors_on_a_response_missing_required_fields() {
     assert_eq!(
         transform_response(json!("nope")).expect_err("not an object"),
-        CoreError::InvalidResponse("converse response is not an object".to_string())
+        Error::InvalidResponse("converse response is not an object".to_string())
     );
     assert_eq!(
         transform_response(json!({"usage": {}})).expect_err("no output"),
-        CoreError::MissingField("output.message.content")
+        Error::MissingField("output.message.content")
     );
     assert_eq!(
         transform_response(json!({"output": {"message": {"content": []}}})).expect_err("no usage"),
-        CoreError::MissingField("usage")
+        Error::MissingField("usage")
     );
 }
 
diff --git a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs
index b107950748e..ef5f44b4a14 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs
@@ -11,7 +11,7 @@ use crate::chat_completions::types::{
     ChatCompletionsUsage, ChatMessage, ChatMessageContent, ProviderChatRequestData,
     ProviderChatResponseData,
 };
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 
 use super::super::aws_base::{bedrock_model_id_and_region, resolve_bedrock_region};
 use super::super::constants::{AWS_BEARER_TOKEN_BEDROCK, BEDROCK_RUNTIME_ENDPOINT_TEMPLATE};
@@ -110,7 +110,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         let (model_id, model_region) = bedrock_model_id_and_region(model);
         let region = resolve_bedrock_region(model_region.as_deref(), optional_params, env_lookup);
         let endpoint = optional_params
@@ -137,7 +137,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<ChatCompletionsAuth> {
+    ) -> Result<ChatCompletionsAuth, Error> {
         // Python reads `api_key` as the Bedrock bearer token and consults the
         // env only when the caller passed none, so a caller-supplied empty key
         // falls through to SigV4 without reaching for the environment. An
@@ -208,7 +208,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         _model: &str,
         messages: Vec<ChatMessage>,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<ProviderChatRequestData> {
+    ) -> Result<ProviderChatRequestData, Error> {
         Ok(ProviderChatRequestData {
             body: converse_body(&build_conversation(&messages), &optional_params),
         })
@@ -218,17 +218,18 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         &self,
         model: &str,
         response: ProviderChatResponseData,
-    ) -> CoreResult<ChatCompletionsResponse> {
-        let body = response.body.as_object().ok_or_else(|| {
-            CoreError::InvalidResponse("converse response is not an object".into())
-        })?;
+    ) -> Result<ChatCompletionsResponse, Error> {
+        let body = response
+            .body
+            .as_object()
+            .ok_or_else(|| Error::InvalidResponse("converse response is not an object".into()))?;
 
         let content = body
             .get("output")
             .and_then(|output| output.get("message"))
             .and_then(|message| message.get("content"))
             .and_then(Value::as_array)
-            .ok_or(CoreError::MissingField("output.message.content"))?;
+            .ok_or(Error::MissingField("output.message.content"))?;
         // The route declines tool requests, so anything other than a text block
         // is something this path never asked for. Decline; the host falls back.
         if content.iter().any(|block| {
@@ -236,7 +237,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
                 .as_object()
                 .is_none_or(|block| block.len() != 1 || !block.contains_key("text"))
         }) {
-            return Err(CoreError::Unsupported("non-text response content block"));
+            return Err(Error::Unsupported("non-text response content block"));
         }
         let text: String = content
             .iter()
@@ -246,7 +247,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         let usage = body
             .get("usage")
             .and_then(Value::as_object)
-            .ok_or(CoreError::MissingField("usage"))?;
+            .ok_or(Error::MissingField("usage"))?;
         let field = |name: &str| usage.get(name).and_then(Value::as_u64).unwrap_or(0);
         let computed = usage_from_parts(
             field("inputTokens"),
diff --git a/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs b/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs
index dc720cc4244..6a8a38204a9 100644
--- a/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 use crate::ocr::transformation::OcrProviderConfig;
 use crate::ocr::types::{OcrRequestData, OcrResponseData};
 use serde_json::{Map, Value};
@@ -47,7 +47,7 @@ pub fn complete_url(api_base: Option<&str>) -> String {
 
 /// Resolve the Mistral API key from the explicit param or the environment.
 ///
-/// Blank/whitespace values are treated as absent. Returns `CoreError::Auth`
+/// Blank/whitespace values are treated as absent. Returns `Error::Auth`
 /// when no usable key is available.
 ///
 /// Note: the env fallback only reads the process environment. Secret-manager
@@ -56,13 +56,13 @@ pub fn complete_url(api_base: Option<&str>) -> String {
 pub fn resolve_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|key| !key.is_empty())
         .map(str::to_string)
         .or_else(|| env_lookup(MISTRAL_API_KEY_ENV).filter(|key| !key.trim().is_empty()))
-        .ok_or_else(|| CoreError::Auth(MISSING_KEY_MESSAGE.to_string()))
+        .ok_or_else(|| Error::Auth(MISSING_KEY_MESSAGE.to_string()))
 }
 
 pub struct MistralOcrConfig;
@@ -79,9 +79,9 @@ impl OcrProviderConfig for MistralOcrConfig {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         if !document.is_object() {
-            return Err(CoreError::InvalidType {
+            return Err(Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&document),
             });
@@ -104,10 +104,10 @@ impl OcrProviderConfig for MistralOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         let response_object = response_json
             .as_object()
-            .ok_or_else(|| CoreError::InvalidType {
+            .ok_or_else(|| Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&response_json),
             })?;
@@ -140,7 +140,7 @@ impl OcrProviderConfig for MistralOcrConfig {
         _model: &str,
         _optional_params: &Map<String, Value>,
         _env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         Ok(complete_url(api_base))
     }
 
@@ -148,7 +148,7 @@ impl OcrProviderConfig for MistralOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_api_key(api_key, env_lookup)
     }
 }
@@ -165,11 +165,11 @@ pub fn transform_ocr_request(
     model: &str,
     document: Value,
     optional_params: Map<String, Value>,
-) -> CoreResult<OcrRequestData> {
+) -> Result<OcrRequestData, Error> {
     MISTRAL_OCR_CONFIG.transform_ocr_request(model, document, optional_params)
 }
 
-pub fn transform_ocr_response(model: &str, response_json: Value) -> CoreResult<OcrResponseData> {
+pub fn transform_ocr_response(model: &str, response_json: Value) -> Result<OcrResponseData, Error> {
     MISTRAL_OCR_CONFIG.transform_ocr_response(model, response_json)
 }
 
@@ -250,7 +250,7 @@ mod tests {
 
         assert_eq!(
             err,
-            CoreError::InvalidType {
+            Error::InvalidType {
                 expected: "object",
                 actual: "string",
             }
@@ -307,6 +307,6 @@ mod tests {
     #[test]
     fn resolve_api_key_errors_when_absent() {
         let err = resolve_api_key(None, &|_| None).expect_err("missing key should error");
-        assert_eq!(err, CoreError::Auth(MISSING_KEY_MESSAGE.to_string()));
+        assert_eq!(err, Error::Auth(MISSING_KEY_MESSAGE.to_string()));
     }
 }
diff --git a/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs b/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs
index b3f6b03b28a..f1985f81b7d 100644
--- a/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::realtime::transformation::RealtimeProviderConfig;
 use crate::realtime::types::{RealtimeEvent, RealtimeTransformResult};
 
@@ -72,7 +72,7 @@ impl RealtimeProviderConfig for OpenAiRealtimeConfig {
         &self,
         event: &RealtimeEvent,
         _model: &str,
-    ) -> CoreResult<RealtimeTransformResult> {
+    ) -> Result<RealtimeTransformResult, Error> {
         Ok(RealtimeTransformResult::passthrough(event.clone()))
     }
 
@@ -80,7 +80,7 @@ impl RealtimeProviderConfig for OpenAiRealtimeConfig {
         &self,
         event: &RealtimeEvent,
         _model: &str,
-    ) -> CoreResult<RealtimeTransformResult> {
+    ) -> Result<RealtimeTransformResult, Error> {
         Ok(RealtimeTransformResult::passthrough(event.clone()))
     }
 }
@@ -88,14 +88,14 @@ impl RealtimeProviderConfig for OpenAiRealtimeConfig {
 pub fn transform_realtime_request(
     event: &RealtimeEvent,
     model: &str,
-) -> CoreResult<RealtimeTransformResult> {
+) -> Result<RealtimeTransformResult, Error> {
     OPENAI_REALTIME_CONFIG.transform_realtime_request(event, model)
 }
 
 pub fn transform_realtime_response(
     event: &RealtimeEvent,
     model: &str,
-) -> CoreResult<RealtimeTransformResult> {
+) -> Result<RealtimeTransformResult, Error> {
     OPENAI_REALTIME_CONFIG.transform_realtime_response(event, model)
 }
 
diff --git a/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs b/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs
index e15197c468c..be86bb90311 100644
--- a/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::responses::types::{ResponsesWsEvent, ResponsesWsTransformResult};
 use crate::responses::websocket::{ResponsesWebSocketProviderConfig, enforce_model};
 
@@ -15,7 +15,7 @@ impl ResponsesWebSocketProviderConfig for OpenAIResponsesWsConfig {
         &self,
         event: &ResponsesWsEvent,
         model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult> {
+    ) -> Result<ResponsesWsTransformResult, Error> {
         Ok(ResponsesWsTransformResult::passthrough(enforce_model(
             event, model,
         )))
@@ -25,7 +25,7 @@ impl ResponsesWebSocketProviderConfig for OpenAIResponsesWsConfig {
         &self,
         event: &ResponsesWsEvent,
         _model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult> {
+    ) -> Result<ResponsesWsTransformResult, Error> {
         Ok(ResponsesWsTransformResult::passthrough(event.clone()))
     }
 }
diff --git a/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs b/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs
index 6300149c237..ee095447028 100644
--- a/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 use crate::ocr::transformation::OcrProviderConfig;
 use crate::ocr::types::{OcrRequestData, OcrResponseData};
 use serde_json::{Map, Value, json};
@@ -43,7 +43,7 @@ pub fn is_deepseek_model(model: &str) -> bool {
 pub fn resolve_vertex_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|key| !key.is_empty())
@@ -51,7 +51,7 @@ pub fn resolve_vertex_api_key(
         .or_else(|| env_lookup(VERTEX_AI_API_KEY_ENV).filter(|key| !key.trim().is_empty()))
         .or_else(|| env_lookup(VERTEXAI_API_KEY_ENV).filter(|key| !key.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Vertex AI access token - pass api_key or provide Authorization via extra_headers"
                     .to_string(),
             )
@@ -61,12 +61,12 @@ pub fn resolve_vertex_api_key(
 fn vertex_project(
     params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     string_param(params, &["vertex_project", "vertex_ai_project"])
         .map(str::to_string)
         .or_else(|| env_lookup(VERTEXAI_PROJECT_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::InvalidRequest(
+            Error::InvalidRequest(
                 "Missing vertex_project - Set VERTEXAI_PROJECT environment variable or pass vertex_project parameter"
                     .to_string(),
             )
@@ -99,7 +99,7 @@ pub fn complete_vertex_mistral_url(
     model: &str,
     optional_params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let project = vertex_project(optional_params, env_lookup)?;
     let location = vertex_location(optional_params, env_lookup);
     let base = vertex_mistral_api_base(api_base, &location);
@@ -112,7 +112,7 @@ pub fn complete_vertex_deepseek_url(
     api_base: Option<&str>,
     optional_params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let project = vertex_project(optional_params, env_lookup)?;
     let location = vertex_location(optional_params, env_lookup);
     let base = api_base
@@ -125,20 +125,20 @@ pub fn complete_vertex_deepseek_url(
     ))
 }
 
-fn document_content_item(document: &Value) -> CoreResult<Value> {
-    let object = document.as_object().ok_or_else(|| CoreError::InvalidType {
+fn document_content_item(document: &Value) -> Result<Value, Error> {
+    let object = document.as_object().ok_or_else(|| Error::InvalidType {
         expected: "object",
         actual: json_type_name(document),
     })?;
     let doc_type = object
         .get("type")
         .and_then(Value::as_str)
-        .ok_or(CoreError::MissingField("document.type"))?;
+        .ok_or(Error::MissingField("document.type"))?;
     let url_field = match doc_type {
         "image_url" => "image_url",
         "document_url" => "document_url",
         other => {
-            return Err(CoreError::InvalidRequest(format!(
+            return Err(Error::InvalidRequest(format!(
                 "Unsupported document type: {other}. Expected 'image_url' or 'document_url'"
             )));
         }
@@ -147,7 +147,7 @@ fn document_content_item(document: &Value) -> CoreResult<Value> {
         .get(url_field)
         .and_then(Value::as_str)
         .filter(|value| !value.is_empty())
-        .ok_or(CoreError::MissingField(url_field))?;
+        .ok_or(Error::MissingField(url_field))?;
 
     Ok(json!({
         "type": "image_url",
@@ -163,7 +163,7 @@ fn deepseek_model_name(model: &str) -> String {
     }
 }
 
-fn first_choice_content(response: &Value) -> CoreResult<Value> {
+fn first_choice_content(response: &Value) -> Result<Value, Error> {
     response
         .get("choices")
         .and_then(Value::as_array)
@@ -176,9 +176,7 @@ fn first_choice_content(response: &Value) -> CoreResult<Value> {
             Value::Object(_) => true,
             _ => false,
         })
-        .ok_or_else(|| {
-            CoreError::InvalidResponse("No content in DeepSeek OCR response".to_string())
-        })
+        .ok_or_else(|| Error::InvalidResponse("No content in DeepSeek OCR response".to_string()))
 }
 
 fn ocr_data_from_content(content: Value, usage: Option<Value>, model: &str) -> Value {
@@ -219,7 +217,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_request(model, document, optional_params)
     }
 
@@ -227,7 +225,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_response(model, response_json)
     }
 
@@ -237,7 +235,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_vertex_mistral_url(api_base, model, optional_params, env_lookup)
     }
 
@@ -245,7 +243,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_vertex_api_key(api_key, env_lookup)
     }
 
@@ -264,7 +262,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         let mut data = Map::new();
         data.insert(
             "model".to_string(),
@@ -289,10 +287,10 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         let response = response_json
             .as_object()
-            .ok_or_else(|| CoreError::InvalidType {
+            .ok_or_else(|| Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&response_json),
             })?;
@@ -314,7 +312,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
             });
         }
 
-        let object = ocr_data.as_object().ok_or_else(|| CoreError::InvalidType {
+        let object = ocr_data.as_object().ok_or_else(|| Error::InvalidType {
             expected: "object",
             actual: json_type_name(&ocr_data),
         })?;
@@ -346,7 +344,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         _model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_vertex_deepseek_url(api_base, optional_params, env_lookup)
     }
 
@@ -354,7 +352,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_vertex_api_key(api_key, env_lookup)
     }
 }
diff --git a/litellm-rust/crates/core/src/realtime/transformation.rs b/litellm-rust/crates/core/src/realtime/transformation.rs
index 69b88687000..b08084514ef 100644
--- a/litellm-rust/crates/core/src/realtime/transformation.rs
+++ b/litellm-rust/crates/core/src/realtime/transformation.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::realtime::types::{RealtimeEvent, RealtimeTransformResult};
 
 pub trait RealtimeProviderConfig {
@@ -11,12 +11,12 @@ pub trait RealtimeProviderConfig {
         &self,
         event: &RealtimeEvent,
         model: &str,
-    ) -> CoreResult<RealtimeTransformResult>;
+    ) -> Result<RealtimeTransformResult, Error>;
 
     /// Transform a backend → client event before it is forwarded downstream.
     fn transform_realtime_response(
         &self,
         event: &RealtimeEvent,
         model: &str,
-    ) -> CoreResult<RealtimeTransformResult>;
+    ) -> Result<RealtimeTransformResult, Error>;
 }
diff --git a/litellm-rust/crates/core/src/responses/instrumentation.rs b/litellm-rust/crates/core/src/responses/instrumentation.rs
index ec04571da14..b1098f4d386 100644
--- a/litellm-rust/crates/core/src/responses/instrumentation.rs
+++ b/litellm-rust/crates/core/src/responses/instrumentation.rs
@@ -5,9 +5,9 @@ use std::time::{SystemTime, UNIX_EPOCH};
 
 use serde_json::Value;
 
+use crate::Error;
 use crate::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
 use crate::responses::types::{ResponsesWsEvent, ResponsesWsEventType};
-use crate::{CoreError, CoreResult};
 
 #[derive(Clone, Debug, Default, PartialEq, Eq)]
 pub struct ResponsesWsUsage {
@@ -205,7 +205,7 @@ impl ResponsesWsInstrumentation {
     }
 }
 
-type LifecycleFuture<'a, T> = Pin<Box<dyn Future<Output = CoreResult<T>> + Send + 'a>>;
+type LifecycleFuture<'a, T> = Pin<Box<dyn Future<Output = Result<T, Error>> + Send + 'a>>;
 
 impl CallLifecycleHooks<(), (), ()> for ResponsesWsInstrumentation {
     type PreCallFuture<'a> = LifecycleFuture<'a, ()>;
@@ -246,7 +246,7 @@ impl CallLifecycleHooks<(), (), ()> for ResponsesWsInstrumentation {
     fn async_log_failure_event<'a>(
         &'a self,
         _context: &'a CallLifecycleContext,
-        _error: &'a CoreError,
+        _error: &'a Error,
         _timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a> {
         Box::pin(async move {
@@ -342,7 +342,7 @@ mod tests {
                 ),
                 (),
                 &instrumentation,
-                |_| async { Ok::<(), CoreError>(()) },
+                |_| async { Ok::<(), Error>(()) },
             )
             .await;
 
diff --git a/litellm-rust/crates/core/src/responses/websocket.rs b/litellm-rust/crates/core/src/responses/websocket.rs
index 92dc19627a0..5d037e9cf1b 100644
--- a/litellm-rust/crates/core/src/responses/websocket.rs
+++ b/litellm-rust/crates/core/src/responses/websocket.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::constants::{OPENAI_RESPONSES_DEFAULT_API_BASE, OPENAI_RESPONSES_PATH};
 use crate::responses::types::{ResponsesWsEvent, ResponsesWsEventType, ResponsesWsTransformResult};
 
@@ -19,13 +19,13 @@ pub trait ResponsesWebSocketProviderConfig: Sync {
         &self,
         event: &ResponsesWsEvent,
         model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult>;
+    ) -> Result<ResponsesWsTransformResult, Error>;
 
     fn transform_ws_response(
         &self,
         event: &ResponsesWsEvent,
         model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult>;
+    ) -> Result<ResponsesWsTransformResult, Error>;
 }
 
 pub fn complete_websocket_url(
diff --git a/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs b/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs
index 656ba033b62..8a8a5ea263a 100644
--- a/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs
+++ b/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs
@@ -1,7 +1,8 @@
-//! Enforcement: the litellm-rust workspace has exactly three crates.
+//! Enforcement: the litellm-rust workspace has exactly four crates.
 //!
-//! `core` (pure translation), `ai-gateway` (routes + all network I/O), and
-//! `python-bridge` (the PyO3 cdylib). Adding or removing a crate must be a
+//! `core` (the Rust SDK), `ai-gateway` (the HTTP/WebSocket host),
+//! `python-interop` (domain-neutral PyO3 primitives), and `python-bridge` (the
+//! PyO3 cdylib). Adding or removing a crate must be a
 //! deliberate act: this test fails until the allowlist here is updated, forcing
 //! whoever changes the crate set to justify the new crate per the rule that a
 //! crate is a layer needing independent compilation / its own deps / a separate
@@ -16,10 +17,15 @@ use std::path::{Path, PathBuf};
 
 /// The one true crate set. Update BOTH this and `litellm-rust/AGENTS.md` when the
 /// workspace legitimately gains or loses a crate.
-const EXPECTED_MEMBERS: &[&str] = &["crates/core", "crates/ai-gateway", "crates/python-bridge"];
+const EXPECTED_MEMBERS: &[&str] = &[
+    "crates/core",
+    "crates/ai-gateway",
+    "crates/python-interop",
+    "crates/python-bridge",
+];
 
 /// The crate subdirectory names that must exist under `crates/`.
-const EXPECTED_CRATE_DIRS: &[&str] = &["core", "ai-gateway", "python-bridge"];
+const EXPECTED_CRATE_DIRS: &[&str] = &["core", "ai-gateway", "python-interop", "python-bridge"];
 
 const MISMATCH: &str = "litellm-rust crate set changed — update this allowlist AND litellm-rust/AGENTS.md, and justify the crate per the rule (crate = layer needing independent compilation / its own deps / a separate artifact).";
 
diff --git a/litellm-rust/crates/python-bridge/AGENTS.md b/litellm-rust/crates/python-bridge/AGENTS.md
index ad3cddfa5fd..42282ca4da4 100644
--- a/litellm-rust/crates/python-bridge/AGENTS.md
+++ b/litellm-rust/crates/python-bridge/AGENTS.md
@@ -1,3 +1,3 @@
-litellm-python-bridge is the PyO3 cdylib that exposes Rust to the litellm Python SDK — a thin adapter (Python objects → Rust calls → Python results) over the litellm-core route entrypoints (e.g. `litellm_core::messages::messages`).
+litellm-python-bridge is the PyO3 cdylib that exposes LiteLLM Rust APIs to the Python SDK. Keep API registration, domain dependency wiring, request assembly, and Python exception mapping here. Put domain-neutral Python/Serde conversion and GIL primitives in litellm-python-interop.
 
 Keep it thin: no business logic, no transforms, no I/O orchestration — just marshal in/out and call the core entrypoint.
diff --git a/litellm-rust/crates/python-bridge/CLAUDE.md b/litellm-rust/crates/python-bridge/CLAUDE.md
index 3ce8b8c639a..d25ae5a8130 100644
--- a/litellm-rust/crates/python-bridge/CLAUDE.md
+++ b/litellm-rust/crates/python-bridge/CLAUDE.md
@@ -5,8 +5,9 @@ Rules for `litellm-rust/crates/python-bridge`.
 ## Responsibility
 
 `python-bridge` is the PyO3 boundary between Python LiteLLM and Rust transforms.
-Keep this crate thin. It adapts Python objects to Rust payloads and returns
-Python-compatible dictionaries.
+Keep this crate thin. It exposes LiteLLM Rust APIs, assembles domain requests,
+maps domain errors to Python exceptions, and delegates generic conversion and
+GIL handling to `litellm-python-interop`.
 
 ## Bridge Shape
 
diff --git a/litellm-rust/crates/python-bridge/Cargo.toml b/litellm-rust/crates/python-bridge/Cargo.toml
index d461a483ae0..498003de149 100644
--- a/litellm-rust/crates/python-bridge/Cargo.toml
+++ b/litellm-rust/crates/python-bridge/Cargo.toml
@@ -13,14 +13,14 @@ crate-type = ["cdylib"]
 default = ["abi3"]
 abi3 = ["pyo3/abi3-py310"]
 extension-module = ["pyo3/extension-module"]
+panic-test = []
 
 [dependencies]
 litellm-core = { workspace = true, features = ["bedrock-auth"] }
 litellm-ai-gateway = { workspace = true, default-features = false }
+litellm-python-interop.workspace = true
 pyo3.workspace = true
 pyo3-async-runtimes.workspace = true
-pythonize.workspace = true
-serde.workspace = true
 serde_json.workspace = true
 tokio.workspace = true
 
diff --git a/litellm-rust/crates/python-bridge/benches/serialization.rs b/litellm-rust/crates/python-bridge/benches/serialization.rs
index 8a90cf667d0..0b9436d0cb7 100644
--- a/litellm-rust/crates/python-bridge/benches/serialization.rs
+++ b/litellm-rust/crates/python-bridge/benches/serialization.rs
@@ -2,6 +2,7 @@ use std::hint::black_box;
 use std::time::Duration;
 
 use criterion::{BenchmarkId, Criterion, criterion_group, criterion_main};
+use litellm_python_interop::{from_py, to_py};
 use pyo3::prelude::*;
 use pyo3::types::PyDict;
 use serde_json::{Value, json};
@@ -25,7 +26,7 @@ fn former_json_roundtrip_from_py(py: Python<'_>, value: &Bound<'_, PyAny>) -> Va
 }
 
 fn pythonize_from_py(value: &Bound<'_, PyAny>) -> Value {
-    pythonize::depythonize(value).expect("payload should depythonize")
+    from_py(value).expect("payload should depythonize")
 }
 
 fn former_json_roundtrip_to_py(py: Python<'_>, value: &Value) -> Py<PyAny> {
@@ -37,12 +38,10 @@ fn former_json_roundtrip_to_py(py: Python<'_>, value: &Value) -> Py<PyAny> {
 }
 
 fn pythonize_to_py(py: Python<'_>, value: &Value) -> Py<PyAny> {
-    pythonize::pythonize(py, value)
-        .expect("response should pythonize")
-        .unbind()
+    to_py(py, value).expect("response should pythonize")
 }
 
-fn serialization(c: &mut Criterion) {
+fn bridge_serialization(c: &mut Criterion) {
     Python::initialize();
     Python::attach(|py| {
         for &(label, payload_bytes) in PAYLOAD_SIZES {
@@ -98,6 +97,6 @@ criterion_group! {
         .sample_size(20)
         .warm_up_time(Duration::from_secs(1))
         .measurement_time(Duration::from_secs(4));
-    targets = serialization
+    targets = bridge_serialization
 }
 criterion_main!(benches);
diff --git a/litellm-rust/crates/python-bridge/src/gil.rs b/litellm-rust/crates/python-bridge/src/gil.rs
deleted file mode 100644
index e887c8ec1e3..00000000000
--- a/litellm-rust/crates/python-bridge/src/gil.rs
+++ /dev/null
@@ -1,32 +0,0 @@
-//! GIL accounting.
-//!
-//! A single chokepoint for releasing the GIL around blocking work. Every
-//! blocking call in the bridge goes through [`release_gil`] instead of calling
-//! `Python::detach` directly, so the release count stays accurate and we
-//! have one place to extend later (timing histograms, per-call labels, etc.).
-
-use std::sync::atomic::{AtomicU64, Ordering};
-
-use pyo3::prelude::*;
-
-/// Number of times the bridge has released the GIL since process start.
-static GIL_RELEASES: AtomicU64 = AtomicU64::new(0);
-
-/// Release the GIL around `f`, recording the release.
-///
-/// `f` must not touch any Python state — that is what makes releasing the GIL
-/// safe. Returning the value back to Python re-acquires the GIL at the call
-/// site, after `f` has finished.
-pub fn release_gil<T, F>(py: Python<'_>, f: F) -> T
-where
-    F: FnOnce() -> T + Send,
-    T: Send,
-{
-    GIL_RELEASES.fetch_add(1, Ordering::Relaxed);
-    py.detach(f)
-}
-
-/// Total GIL releases performed by the bridge so far.
-pub fn release_count() -> u64 {
-    GIL_RELEASES.load(Ordering::Relaxed)
-}
diff --git a/litellm-rust/crates/python-bridge/src/lib.rs b/litellm-rust/crates/python-bridge/src/lib.rs
index f9e75f45f75..68aa9436b15 100644
--- a/litellm-rust/crates/python-bridge/src/lib.rs
+++ b/litellm-rust/crates/python-bridge/src/lib.rs
@@ -10,19 +10,15 @@ use litellm_core::chat_completions::types::{ChatCompletionsRequest, ChatCompleti
 use litellm_core::chat_completions::{
     chat_completions as run_chat_completions, chat_completions_decline_reason,
 };
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::messages::messages as run_messages;
 use litellm_core::messages::types::{AnthropicMessagesResponse, MessagesRequest};
+use litellm_python_interop::{from_py, release_count, release_gil, to_py};
 use pyo3::exceptions::{PyRuntimeError, PyValueError};
 use pyo3::prelude::*;
 use pyo3::types::{PyAny, PyDict};
 use serde_json::{Map, Value};
 
-mod gil;
-mod marshal;
-
-use marshal::{from_py, to_py};
-
 pyo3::create_exception!(
     _native,
     RustBridgeDeclined,
@@ -58,13 +54,13 @@ fn chat_completions_response_to_py(
     to_py(py, &response)
 }
 
-fn core_error_to_pyerr(err: CoreError) -> PyErr {
+fn core_error_to_pyerr(err: Error) -> PyErr {
     match err {
-        CoreError::Auth(message) => PyValueError::new_err(message),
-        CoreError::InvalidProvider(_)
-        | CoreError::InvalidRequest(_)
-        | CoreError::InvalidType { .. }
-        | CoreError::MissingField(_) => PyValueError::new_err(err.to_string()),
+        Error::Auth(message) => PyValueError::new_err(message),
+        Error::InvalidProvider(_)
+        | Error::InvalidRequest(_)
+        | Error::InvalidType { .. }
+        | Error::MissingField(_) => PyValueError::new_err(err.to_string()),
         other => PyRuntimeError::new_err(other.to_string()),
     }
 }
@@ -75,22 +71,22 @@ fn core_error_to_pyerr(err: CoreError) -> PyErr {
 /// Everything raised before the request goes out is safe for the host to retry
 /// on its own path; anything after it is not, because the provider has already
 /// done the work and billed for it.
-fn chat_completions_error_to_pyerr(err: CoreError) -> PyErr {
+fn chat_completions_error_to_pyerr(err: Error) -> PyErr {
     match err {
-        CoreError::Unsupported(_)
-        | CoreError::Auth(_)
-        | CoreError::InvalidProvider(_)
-        | CoreError::InvalidRequest(_)
-        | CoreError::InvalidType { .. }
-        | CoreError::MissingField(_)
-        | CoreError::Routing(_)
+        Error::Unsupported(_)
+        | Error::Auth(_)
+        | Error::InvalidProvider(_)
+        | Error::InvalidRequest(_)
+        | Error::InvalidType { .. }
+        | Error::MissingField(_)
+        | Error::Routing(_)
         // Nothing reached the provider, so serving it on Python cannot double
         // bill and is the only way the caller gets an answer at all.
-        | CoreError::Connect(_) => RustBridgeDeclined::new_err(err.to_string()),
-        CoreError::Http { status, body } => {
+        | Error::Connect(_) => RustBridgeDeclined::new_err(err.to_string()),
+        Error::Http { status, body } => {
             RustUpstreamError::new_err((status, format!("{status}: {body}")))
         }
-        CoreError::Network(message) | CoreError::InvalidResponse(message) => {
+        Error::Network(message) | Error::InvalidResponse(message) => {
             RustUpstreamError::new_err((0u16, message))
         }
     }
@@ -230,7 +226,7 @@ fn ocr(
         timeout_seconds,
     )?;
 
-    let result = gil::release_gil(py, || {
+    let result = release_gil(py, || {
         pyo3_async_runtimes::tokio::get_runtime().block_on(run_ocr(OcrRequest {
             model: &model,
             document,
@@ -318,7 +314,7 @@ fn transcription(
     };
     let optional_params = optional_object_to_map(py, "optional_params", optional_params)?;
     let timeout = optional_timeout(timeout_seconds);
-    let result = gil::release_gil(py, || {
+    let result = release_gil(py, || {
         pyo3_async_runtimes::tokio::get_runtime().block_on(run_audio_transcription(
             AudioTranscriptionRequest {
                 model: &model,
@@ -419,7 +415,7 @@ fn messages(
     let (body, extra_headers, timeout) =
         marshal_messages_inputs(py, body, extra_headers, timeout_seconds)?;
 
-    let result = gil::release_gil(py, || {
+    let result = release_gil(py, || {
         pyo3_async_runtimes::tokio::get_runtime().block_on(run_messages(MessagesRequest {
             model: &model,
             body,
@@ -546,7 +542,7 @@ fn chat_completions(
         timeout_seconds,
     )?;
 
-    let result = gil::release_gil(py, || {
+    let result = release_gil(py, || {
         pyo3_async_runtimes::tokio::get_runtime().block_on(run_chat_completions(
             ChatCompletionsRequest {
                 model: &model,
@@ -610,10 +606,16 @@ fn achat_completions(
 #[pyfunction]
 fn gil_stats(py: Python<'_>) -> PyResult<Py<PyAny>> {
     let stats = PyDict::new(py);
-    stats.set_item("releases", gil::release_count())?;
+    stats.set_item("releases", release_count())?;
     Ok(stats.into_any().unbind())
 }
 
+#[cfg(feature = "panic-test")]
+#[pyfunction]
+fn _panic_for_test() {
+    panic!("intentional PyO3 panic smoke test");
+}
+
 #[pymodule]
 fn _native(module: &Bound<'_, PyModule>) -> PyResult<()> {
     let py = module.py();
@@ -630,5 +632,7 @@ fn _native(module: &Bound<'_, PyModule>) -> PyResult<()> {
     module.add_function(wrap_pyfunction!(achat_completions, module)?)?;
     module.add_class::<ResponsesWebSocketConnection>()?;
     module.add_function(wrap_pyfunction!(gil_stats, module)?)?;
+    #[cfg(feature = "panic-test")]
+    module.add_function(wrap_pyfunction!(_panic_for_test, module)?)?;
     Ok(())
 }
diff --git a/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs b/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs
index 6a6ede22e85..d397d20b9fd 100644
--- a/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs
+++ b/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs
@@ -1,7 +1,7 @@
 use std::fs;
 use std::path::{Path, PathBuf};
 
-const DISALLOWED_OUTSIDE_MARSHAL: &[&str] = &[
+const DISALLOWED_OUTSIDE_INTEROP: &[&str] = &[
     "py.import(\"json\")",
     "pythonize::",
     "serde_json::to_string",
@@ -33,18 +33,15 @@ fn rust_sources(directory: &Path) -> Vec<PathBuf> {
 }
 
 #[test]
-fn serialization_is_centralized_in_marshal_module() {
+fn serialization_uses_the_interop_boundary() {
     let root = source_root();
 
     for path in rust_sources(&root) {
-        if path == root.join("marshal.rs") {
-            continue;
-        }
         let source = fs::read_to_string(&path).expect("bridge source should be readable");
-        for disallowed in DISALLOWED_OUTSIDE_MARSHAL {
+        for disallowed in DISALLOWED_OUTSIDE_INTEROP {
             assert!(
                 !source.contains(disallowed),
-                "{} bypasses the typed marshal module with `{disallowed}`",
+                "{} bypasses litellm-python-interop with `{disallowed}`",
                 path.display()
             );
         }
diff --git a/litellm-rust/crates/python-interop/AGENTS.md b/litellm-rust/crates/python-interop/AGENTS.md
new file mode 100644
index 00000000000..d1d61e5dfa0
--- /dev/null
+++ b/litellm-rust/crates/python-interop/AGENTS.md
@@ -0,0 +1 @@
+litellm-python-interop is the domain-neutral PyO3 foundation. Keep generic Python/Serde conversion and interpreter primitives here. Do not add LiteLLM domain crates, route types, API registration, or cdylib build features.
diff --git a/litellm-rust/crates/python-interop/Cargo.toml b/litellm-rust/crates/python-interop/Cargo.toml
new file mode 100644
index 00000000000..9da6af6e2e2
--- /dev/null
+++ b/litellm-rust/crates/python-interop/Cargo.toml
@@ -0,0 +1,15 @@
+[package]
+name = "litellm-python-interop"
+version = "0.1.0"
+edition.workspace = true
+license.workspace = true
+repository.workspace = true
+
+[dependencies]
+pyo3.workspace = true
+pythonize.workspace = true
+serde.workspace = true
+
+[dev-dependencies]
+rstest.workspace = true
+serde_json.workspace = true
diff --git a/litellm-rust/crates/python-interop/src/gil.rs b/litellm-rust/crates/python-interop/src/gil.rs
new file mode 100644
index 00000000000..04b966a6002
--- /dev/null
+++ b/litellm-rust/crates/python-interop/src/gil.rs
@@ -0,0 +1,21 @@
+use std::sync::atomic::{AtomicU64, Ordering};
+
+use pyo3::prelude::*;
+
+static GIL_RELEASES: AtomicU64 = AtomicU64::new(0);
+
+/// Runs work detached from the interpreter and records the release.
+///
+/// `f` must not access Python state while the interpreter is detached.
+pub fn release_gil<T, F>(py: Python<'_>, f: F) -> T
+where
+    F: FnOnce() -> T + Send,
+    T: Send,
+{
+    GIL_RELEASES.fetch_add(1, Ordering::Relaxed);
+    py.detach(f)
+}
+
+pub fn release_count() -> u64 {
+    GIL_RELEASES.load(Ordering::Relaxed)
+}
diff --git a/litellm-rust/crates/python-interop/src/lib.rs b/litellm-rust/crates/python-interop/src/lib.rs
new file mode 100644
index 00000000000..df2bd260fdb
--- /dev/null
+++ b/litellm-rust/crates/python-interop/src/lib.rs
@@ -0,0 +1,5 @@
+mod gil;
+mod marshal;
+
+pub use gil::{release_count, release_gil};
+pub use marshal::{from_py, to_py};
diff --git a/litellm-rust/crates/python-bridge/src/marshal.rs b/litellm-rust/crates/python-interop/src/marshal.rs
similarity index 100%
rename from litellm-rust/crates/python-bridge/src/marshal.rs
rename to litellm-rust/crates/python-interop/src/marshal.rs
diff --git a/litellm-rust/crates/python-interop/tests/interop.rs b/litellm-rust/crates/python-interop/tests/interop.rs
new file mode 100644
index 00000000000..9c456dcb938
--- /dev/null
+++ b/litellm-rust/crates/python-interop/tests/interop.rs
@@ -0,0 +1,44 @@
+use pyo3::Python;
+use rstest::{fixture, rstest};
+use serde_json::{Value, json};
+
+use litellm_python_interop::{from_py, release_count, release_gil, to_py};
+
+struct InitializedPython;
+
+impl InitializedPython {
+    fn attach<F, R>(&self, f: F) -> R
+    where
+        F: for<'py> FnOnce(Python<'py>) -> R,
+    {
+        Python::attach(f)
+    }
+}
+
+#[fixture]
+#[once]
+fn initialized_python() -> InitializedPython {
+    Python::initialize();
+    InitializedPython
+}
+
+#[rstest]
+fn serde_values_round_trip_through_python(#[from(initialized_python)] python: &InitializedPython) {
+    python.attach(|py| {
+        let expected = json!({"model": "test", "items": [1, true, null]});
+        let python_value = to_py(py, &expected).expect("value should convert to Python");
+        let actual: Value =
+            from_py(python_value.bind(py)).expect("Python value should convert to serde");
+
+        assert_eq!(actual, expected);
+    });
+}
+
+#[rstest]
+fn release_gil_runs_work_and_records_it(#[from(initialized_python)] python: &InitializedPython) {
+    let before = release_count();
+    let result = python.attach(|py| release_gil(py, || 42));
+
+    assert_eq!(result, 42);
+    assert_eq!(release_count(), before + 1);
+}
diff --git a/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py b/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py
index 32252711997..1e8cc4ff90e 100644
--- a/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py
+++ b/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py
@@ -10,8 +10,19 @@ from collections.abc import AsyncIterator, Mapping
 from typing import Any, Final
 
 from litellm._logging import verbose_logger
+from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+    A2A_USER_API_KEY_HASH_PARAM,
+)
+from litellm.a2a_protocol.utils import (
+    get_session_id_from_a2a_params,
+    scope_session_to_principal,
+)
+from litellm.exceptions import BadRequestError
 from litellm.llms.bedrock.chat.agentcore.transformation import AmazonAgentCoreConfig
 
+RUNTIME_SESSION_ID_MIN_LENGTH: Final = 33
+RUNTIME_SESSION_ID_MAX_LENGTH: Final = 256
+
 # Reserved outbound header names that must never be sourced from per-request
 # ``agent_extra_headers`` for AgentCore requests. ``agent_extra_headers`` carries
 # values rewritten from the client-controlled ``x-a2a-{agent}-*`` convention, so
@@ -19,8 +30,9 @@ from litellm.llms.bedrock.chat.agentcore.transformation import AmazonAgentCoreCo
 # request identity / SigV4 metadata by overwriting headers the proxy sets from
 # trusted server-side config.
 #
-# The runtime headers (session / user id) are derived server-side from
-# ``runtimeSessionId`` / ``runtimeUserId`` in the agent's ``litellm_params``;
+# The runtime headers (session / user id) are derived server-side from the A2A
+# ``message.contextId`` and ``runtimeSessionId`` / ``runtimeUserId`` in the
+# agent's ``litellm_params``;
 # ``authorization`` is set by the AgentCore signer (JWT or SigV4); ``host`` and
 # the ``x-amz-*`` family are owned by SigV4 itself.
 _RESERVED_EXACT_HEADERS: Final = frozenset(
@@ -66,6 +78,31 @@ def _filter_reserved_headers(
     return filtered or None
 
 
+def _request_scoped_runtime_session_id(
+    params: Mapping[str, Any],
+    litellm_params: Mapping[str, Any],
+) -> str | None:
+    context_id: Final = get_session_id_from_a2a_params(params)
+    if not isinstance(context_id, str) or not context_id:
+        return None
+    return scope_session_to_principal(context_id, litellm_params.get(A2A_USER_API_KEY_HASH_PARAM))
+
+
+def _validate_runtime_session_id(session_id: str, model: str) -> str:
+    if RUNTIME_SESSION_ID_MIN_LENGTH <= len(session_id) <= RUNTIME_SESSION_ID_MAX_LENGTH:
+        return session_id
+    raise BadRequestError(
+        message=(
+            f"Invalid AgentCore runtime session id {session_id!r}: AWS requires "
+            f"{RUNTIME_SESSION_ID_MIN_LENGTH}-{RUNTIME_SESSION_ID_MAX_LENGTH} characters. It is built from the A2A "
+            "message.contextId (prefixed with a 16-hex-char hash of the calling key and '-') when set, "
+            "otherwise from the agent's configured runtimeSessionId."
+        ),
+        model=model,
+        llm_provider="bedrock",
+    )
+
+
 class BedrockAgentCoreA2ATransformation:
     """
     Request/response transformation for Bedrock AgentCore A2A agents.
@@ -100,7 +137,9 @@ class BedrockAgentCoreA2ATransformation:
                 here to prevent a caller-controlled ``x-a2a-{agent}-*`` header from
                 spoofing the AgentCore runtime user id or other SigV4 metadata. Use
                 ``api_key`` / ``runtimeUserId`` / ``runtimeSessionId`` in litellm_params
-                (not ``agent_extra_headers``) to override those values.
+                (not ``agent_extra_headers``) to override those values. The runtime
+                session id is taken from ``params["message"]["contextId"]`` (scoped to
+                the calling key) when present, then ``runtimeSessionId``, else generated.
 
         Returns:
             Tuple of (url, signed_headers, signed_body_bytes)
@@ -139,7 +178,11 @@ class BedrockAgentCoreA2ATransformation:
         # Set required AgentCore session headers (normally set by transform_request,
         # which we skip because it also builds {"prompt": "..."})
         headers: Final[dict] = {}
-        session_id: Final = agentcore_config._get_runtime_session_id(optional_params)
+        session_id: Final = _validate_runtime_session_id(
+            _request_scoped_runtime_session_id(params, litellm_params)
+            or agentcore_config._get_runtime_session_id(optional_params),
+            model=model,
+        )
         headers["X-Amzn-Bedrock-AgentCore-Runtime-Session-Id"] = session_id
         runtime_user_id: Final = agentcore_config._get_runtime_user_id(optional_params)
         if runtime_user_id:
diff --git a/litellm/a2a_protocol/utils.py b/litellm/a2a_protocol/utils.py
index f2e61f66105..7c459daf720 100644
--- a/litellm/a2a_protocol/utils.py
+++ b/litellm/a2a_protocol/utils.py
@@ -2,6 +2,8 @@
 Utility functions for A2A protocol.
 """
 
+import hashlib
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final
 
 import litellm
@@ -140,6 +142,29 @@ class A2ARequestUtils:
         return prompt_tokens, completion_tokens, total_tokens
 
 
+def get_session_id_from_a2a_params(params: Mapping[str, Any]) -> str | None:
+    message: Final = params.get("message", {})
+    if isinstance(message, dict):
+        return message.get("contextId")
+    return getattr(message, "contextId", None)
+
+
+def scope_session_to_principal(session_id: str, principal: str | None) -> str:
+    """
+    Bind a client-supplied A2A contextId to the authenticated principal.
+
+    Without this, two distinct keys authorized for the same agent could set the
+    same contextId and read/append to each other's backend memory. The
+    principal is hashed (it is already a hashed token) so the raw value is never
+    sent to the agent backend, while the original contextId is kept as a suffix
+    for operator-side correlation.
+    """
+    if not principal:
+        return session_id
+    principal_prefix: Final = hashlib.sha256(principal.encode("utf-8")).hexdigest()[:16]
+    return f"{principal_prefix}-{session_id}"
+
+
 # Backwards compatibility aliases
 def extract_text_from_a2a_message(message: Any) -> str:
     return A2ARequestUtils.extract_text_from_message(message)
diff --git a/litellm/constants.py b/litellm/constants.py
index 1bd977dd9a9..1c1939bd350 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -9,6 +9,38 @@ DEFAULT_HEALTH_CHECK_PROMPT: Final = str(os.getenv("DEFAULT_HEALTH_CHECK_PROMPT"
 AZURE_DEFAULT_RESPONSES_API_VERSION: Final = str(os.getenv("AZURE_DEFAULT_RESPONSES_API_VERSION", "preview"))
 ROUTER_MAX_FALLBACKS: Final = int(os.getenv("ROUTER_MAX_FALLBACKS", 5))
 ROUTER_FALLBACK_ERROR_DETAIL_MAX_CHARS: Final = 2000
+RUNTIME_UPDATABLE_ROUTER_SETTINGS: Final[frozenset[str]] = frozenset(
+    {
+        "routing_strategy_args",
+        "routing_strategy",
+        "routing_groups",
+        "allowed_fails",
+        "cooldown_time",
+        "num_retries",
+        "timeout",
+        "max_retries",
+        "retry_after",
+        "fallbacks",
+        "context_window_fallbacks",
+        "retry_policy",
+        "model_group_retry_policy",
+        "model_group_alias",
+        "enable_weighted_failover",
+        "enable_tag_filtering",
+        "tag_routing_prefix",
+        "optional_pre_call_checks",
+    }
+)
+ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG: Final[frozenset[str]] = frozenset(
+    {
+        "model_list",
+        "search_tools",
+        "assistants_config",
+        "router_general_settings",
+        "ignore_invalid_deployments",
+        "fallback_access_check",
+    }
+)
 DEFAULT_BATCH_SIZE: Final = int(os.getenv("DEFAULT_BATCH_SIZE", 512))
 DEFAULT_FLUSH_INTERVAL_SECONDS: Final = int(os.getenv("DEFAULT_FLUSH_INTERVAL_SECONDS", 5))
 DEFAULT_S3_FLUSH_INTERVAL_SECONDS: Final = int(os.getenv("DEFAULT_S3_FLUSH_INTERVAL_SECONDS", 10))
diff --git a/litellm/containers/main.py b/litellm/containers/main.py
index 97ca11872c1..90d59af009f 100644
--- a/litellm/containers/main.py
+++ b/litellm/containers/main.py
@@ -1,7 +1,7 @@
 import asyncio
 import contextvars
 import json
-from collections.abc import Coroutine, Mapping
+from collections.abc import Callable, Coroutine, Mapping
 from functools import partial
 from typing import Final, Literal, overload
 
@@ -47,6 +47,13 @@ __all__ = [
 
 
 ##### Container Create #######################
+async def _encode_created_container_id(
+    pending: Coroutine[object, object, ContainerObject],
+    encode: Callable[[ContainerObject], ContainerObject],
+) -> ContainerObject:
+    return encode(await pending)
+
+
 @client
 async def acreate_container(
     name: str,
@@ -256,16 +263,16 @@ def create_container(
             _is_async=_is_async,
         )
 
-        # Encode container_id with provider/model metadata for routing
+        encode: Final = partial(
+            ContainerRequestUtils.encode_container_id_in_response,
+            custom_llm_provider=custom_llm_provider,
+            litellm_metadata=kwargs.get("litellm_metadata"),
+            extra_body=extra_body,
+        )
         if isinstance(container_obj, ContainerObject):
-            container_obj = ContainerRequestUtils.encode_container_id_in_response(
-                response_obj=container_obj,
-                custom_llm_provider=custom_llm_provider,
-                litellm_metadata=kwargs.get("litellm_metadata"),
-                extra_body=extra_body,
-            )
+            return encode(container_obj)
 
-        return container_obj
+        return _encode_created_container_id(pending=container_obj, encode=encode)
 
     except Exception as e:
         raise litellm.exception_type(
diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py
index e87ac9521ae..372c9bf6b91 100644
--- a/litellm/integrations/custom_guardrail.py
+++ b/litellm/integrations/custom_guardrail.py
@@ -1,4 +1,5 @@
 import contextvars
+import copy
 import hashlib
 import os
 import secrets
@@ -39,6 +40,7 @@ except ImportError:
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
 dc: Final = DualCache()
 
 
@@ -852,6 +854,69 @@ class CustomGuardrail(CustomLogger):
 
         return result
 
+    async def async_logging_hook(
+        self,
+        kwargs: dict,  # mutable-ok: CustomLogger.async_logging_hook contract
+        result: object,
+        call_type: str,
+    ) -> tuple[dict, object]:  # mutable-ok: CustomLogger.async_logging_hook contract
+        """logging_only: run apply_guardrail on copies of the logged request/response and record the verdict."""
+        from litellm.llms import get_guardrail_translation_mapping
+
+        if not self.uses_apply_guardrail_interface() or self.use_native_lifecycle_hooks:
+            return kwargs, result
+        try:
+            translation: Final = get_guardrail_translation_mapping(CallTypes(call_type))()
+        except ValueError:
+            verbose_logger.debug(
+                "Guardrail %s: no guardrail translation for call_type=%s, skipping logging_only scan",
+                self.guardrail_name,
+                call_type,
+            )
+            return kwargs, result
+        litellm_params: Final = kwargs.get("litellm_params") or {}
+        scratch_metadata: Final = {
+            key: value
+            for key, value in (litellm_params.get("metadata") or {}).items()
+            if key != "standard_logging_guardrail_information"
+        }
+        try:
+            await self._scan_logged_call(kwargs, result, translation, scratch_metadata)
+        except Exception as e:
+            verbose_logger.warning("Guardrail %s: logging_only scan raised: %s", self.guardrail_name, e)
+        recorded: Final = scratch_metadata.get("standard_logging_guardrail_information")
+        standard_logging_object: Final = kwargs.get("standard_logging_object")
+        if not recorded or not isinstance(standard_logging_object, dict):
+            return kwargs, result
+        entries: Final = recorded if isinstance(recorded, list) else [recorded]
+        existing: Final = standard_logging_object.get("guardrail_information") or []
+        return {
+            **kwargs,
+            "standard_logging_object": {**standard_logging_object, "guardrail_information": [*existing, *entries]},
+        }, result
+
+    async def _scan_logged_call(
+        self,
+        kwargs: dict,  # mutable-ok: CustomLogger.async_logging_hook contract
+        result: object,
+        translation: "BaseTranslation",
+        scratch_metadata: dict,  # mutable-ok: apply_guardrail records its verdict into request metadata
+    ) -> None:
+        optional_params: Final = kwargs.get("optional_params") or {}
+        scratch_input: Final = copy.deepcopy(kwargs.get("messages") or kwargs.get("input"))
+        scratch_request: Final = {
+            "model": kwargs.get("model"),
+            "messages": scratch_input,
+            "input": scratch_input,
+            "tools": copy.deepcopy(optional_params.get("tools")),
+            "litellm_call_id": kwargs.get("litellm_call_id"),
+            "metadata": scratch_metadata,
+        }
+        await translation.process_input_messages(data=scratch_request, guardrail_to_apply=self)
+        await translation.process_output_response(
+            response=copy.deepcopy(result), guardrail_to_apply=self, request_data=scratch_request
+        )
+
     def supports_scan_only_tool_results(self) -> bool:
         """Whether this guardrail can scan tool-result content.
 
diff --git a/litellm/integrations/datadog/datadog_llm_obs.py b/litellm/integrations/datadog/datadog_llm_obs.py
index e5789965c6e..5e116b7301a 100644
--- a/litellm/integrations/datadog/datadog_llm_obs.py
+++ b/litellm/integrations/datadog/datadog_llm_obs.py
@@ -11,6 +11,7 @@ import json
 import os
 from collections.abc import Mapping, Sequence
 from datetime import datetime
+from types import MappingProxyType
 from typing import Any, Final, Literal
 
 import httpx
@@ -30,12 +31,16 @@ from litellm.integrations.datadog.datadog_mock_client import (
 )
 from litellm.litellm_core_utils.dd_tracing import tracer
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    convert_content_list_to_str,
     handle_any_messages_to_chat_completion_str_messages_conversion,
 )
+from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+from litellm.litellm_core_utils.safe_json_loads import safe_json_loads
 from litellm.llms.custom_httpx.http_handler import (
     get_async_httpx_client,
     httpxSpecialProvider,
 )
+from litellm.proxy.spend_tracking.savings import extract_cache_creation_tokens, extract_cache_read_tokens
 from litellm.types.integrations.datadog_llm_obs import *
 from litellm.types.utils import (
     CallTypes,
@@ -44,6 +49,189 @@ from litellm.types.utils import (
     StandardLoggingPayloadErrorInformation,
 )
 
+_EMPTY_MAPPING: Final[Mapping[str, Any]] = MappingProxyType({})
+_EMPTY_MESSAGE: Final[Message] = {"role": "", "content": ""}
+_MAX_PARSED_TOOL_ARGUMENT_CHARS: Final = 256 * 1024
+
+
+def _mapping_field(source: Mapping[str, Any], key: str) -> Mapping[str, Any]:
+    """The value at `key` when it is a mapping, else an empty one."""
+    value: Final = source.get(key)
+    return value if isinstance(value, dict) else _EMPTY_MAPPING
+
+
+def _content_blocks(message: Mapping[str, Any]) -> tuple[Mapping[str, Any], ...]:
+    content: Final = message.get("content")
+    if not isinstance(content, list):
+        return ()
+    return tuple(block for block in content if isinstance(block, dict))
+
+
+def _to_dd_arguments(raw_arguments: object) -> dict[str, Any] | str:
+    """
+    Arguments as the object LLM Obs types them as, or the raw string when they are not one.
+
+    Strings past the size bound ship unparsed: decoding multiplies memory on hostile compact
+    JSON, and the raw string is what the intake receives either way.
+    """
+    if not isinstance(raw_arguments, str):
+        return raw_arguments if isinstance(raw_arguments, dict) else str(raw_arguments)
+    if len(raw_arguments) > _MAX_PARSED_TOOL_ARGUMENT_CHARS:
+        return raw_arguments
+    parsed: Final = safe_json_loads(raw_arguments)
+    return parsed if isinstance(parsed, dict) else raw_arguments
+
+
+def _to_dd_tool_calls(message: Mapping[str, Any]) -> tuple[ToolCall, ...]:
+    """
+    The tool calls a message carries, in LLM Obs' ToolCall schema, from either dialect.
+
+    OpenAI puts them in `tool_calls` with the callee nested under `function` and `arguments`
+    serialized; Anthropic puts them in `content` as `tool_use` blocks with `input` already an
+    object. LLM Obs reads `name` / `arguments` / `tool_id` either way.
+    """
+    raw_tool_calls: Final = message.get("tool_calls")
+    openai_calls: Final = tuple(
+        ToolCall(
+            name=function.get("name", ""),
+            arguments=_to_dd_arguments(function.get("arguments", "")),
+            tool_id=tool_call.get("id", ""),
+            type=tool_call.get("type", "function"),
+        )
+        for tool_call in (raw_tool_calls if isinstance(raw_tool_calls, list) else ())
+        if isinstance(tool_call, dict)
+        for function in [_mapping_field(tool_call, "function")]
+    )
+    anthropic_calls: Final = tuple(
+        ToolCall(
+            name=block.get("name", ""),
+            arguments=_to_dd_arguments(block.get("input") or {}),
+            tool_id=block.get("id", ""),
+            type="tool_use",
+        )
+        for block in _content_blocks(message)
+        if block.get("type") == "tool_use"
+    )
+    return openai_calls + anthropic_calls
+
+
+def _to_dd_tool_results(message: Mapping[str, Any], tool_call_names: Mapping[str, str]) -> tuple[ToolResult, ...]:
+    """
+    The tool results a message carries, linked back to the call each answers.
+
+    OpenAI models a result as a whole `role: "tool"` message keyed by `tool_call_id`;
+    Anthropic nests `tool_result` blocks inside a user message, keyed by `tool_use_id`.
+    """
+
+    def to_result(tool_id: str, result: object) -> ToolResult:
+        return ToolResult(
+            name=tool_call_names.get(tool_id, ""),
+            result=result if isinstance(result, str) else safe_dumps(result),
+            tool_id=tool_id,
+            type="function",
+        )
+
+    if message.get("role") == "tool":
+        return (to_result(str(message.get("tool_call_id", "")), message.get("content") or ""),)
+    return tuple(
+        to_result(str(block.get("tool_use_id", "")), block.get("content") or "")
+        for block in _content_blocks(message)
+        if block.get("type") == "tool_result"
+    )
+
+
+def _tool_call_names_by_id(messages: Sequence[object]) -> Mapping[str, str]:
+    """Ids to tool names for result linking; reads names structurally and parses nothing."""
+    openai_pairs: Final = tuple(
+        (tool_call.get("id"), function.get("name", ""))
+        for message in messages
+        if isinstance(message, dict) and isinstance(message.get("tool_calls"), list)
+        for tool_call in message["tool_calls"]
+        if isinstance(tool_call, dict)
+        for function in [_mapping_field(tool_call, "function")]
+    )
+    anthropic_pairs: Final = tuple(
+        (block.get("id"), block.get("name", ""))
+        for message in messages
+        if isinstance(message, dict)
+        for block in _content_blocks(message)
+        if block.get("type") == "tool_use"
+    )
+    return MappingProxyType({str(tool_id): str(name) for tool_id, name in openai_pairs + anthropic_pairs if tool_id})
+
+
+def _to_dd_message(message: object, tool_call_names: Mapping[str, str]) -> Message:
+    """
+    Map one chat message onto LLM Obs' Message schema, adding fields and never destroying content.
+
+    Content collapses to its text only when it has text; a content list with none (tool blocks,
+    images) rides along unchanged so nothing the caller logged is lost. Tool calls and results
+    move into the fields the LLM Obs Tools panel reads, from both the OpenAI and Anthropic shapes.
+    """
+    if not isinstance(message, dict):
+        converted: Final = handle_any_messages_to_chat_completion_str_messages_conversion(message)
+        return converted[0] if converted else _EMPTY_MESSAGE
+
+    text: Final = convert_content_list_to_str(message)  # pyright: ignore[reportArgumentType]  # caller-supplied dict
+    original_content: Final = message.get("content")
+    content: Final = (
+        text if text or not isinstance(original_content, list) or not original_content else original_content
+    )
+    reasoning: Final = message.get("reasoning_content")
+    tool_calls: Final = _to_dd_tool_calls(message)
+    tool_results: Final = _to_dd_tool_results(message, tool_call_names)
+    dd_message: Final[Message] = {
+        "role": message.get("role", ""),
+        "content": content,
+        **({"reasoning_content": reasoning} if reasoning is not None else {}),
+        **({"tool_calls": tool_calls} if tool_calls else {}),
+        **({"tool_results": tool_results} if tool_results else {}),
+    }
+    return dd_message
+
+
+def _to_dd_messages(messages: object) -> tuple[Message, ...]:
+    """Map a whole conversation, resolving each tool result against the calls that precede it."""
+    if messages is None:
+        return ()
+    if not isinstance(messages, list):
+        return tuple(handle_any_messages_to_chat_completion_str_messages_conversion(messages))
+    tool_call_names: Final = _tool_call_names_by_id(messages)
+    return tuple(_to_dd_message(message, tool_call_names) for message in messages)
+
+
+def _to_dd_tool_definition(entry: Mapping[str, Any]) -> ToolDefinition | None:
+    function: Final = entry.get("function")
+    declared: Final[Mapping[str, Any]] = function if isinstance(function, dict) else entry
+    name: Final = declared.get("name")
+    if not name:
+        return None
+    schema: Final = declared.get("parameters") or declared.get("input_schema")
+    description: Final = declared.get("description", "")
+    if not isinstance(schema, dict):
+        return ToolDefinition(name=name, description=description)
+    return ToolDefinition(name=name, description=description, schema=schema)
+
+
+def _to_dd_tool_definitions(model_parameters: object) -> tuple[ToolDefinition, ...]:
+    """
+    Map the request's declared tools onto LLM Obs' ToolDefinition schema.
+
+    Handles the wrapped chat-completions shape and the bare shape the Anthropic and
+    Responses surfaces use, since both reach this logger through `model_parameters`.
+    """
+    if not isinstance(model_parameters, dict):
+        return ()
+    raw_tools: Final = model_parameters.get("tools") or model_parameters.get("functions")
+    if not isinstance(raw_tools, list):
+        return ()
+    return tuple(
+        definition
+        for entry in raw_tools
+        if isinstance(entry, dict)
+        if (definition := _to_dd_tool_definition(entry)) is not None
+    )
+
 
 class DataDogLLMObsLogger(CustomBatchLogger):
     def __init__(self, **kwargs):
@@ -222,12 +410,9 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         if standard_logging_payload is None:
             raise Exception("DataDogLLMObs: standard_logging_object is not set")
 
-        messages = standard_logging_payload["messages"]
-        messages = self._ensure_string_content(messages=messages)
-
         metadata: Final = kwargs.get("litellm_params", {}).get("metadata", {})
 
-        input_meta: Final = InputMeta(messages=handle_any_messages_to_chat_completion_str_messages_conversion(messages))
+        input_meta: Final = InputMeta(messages=_to_dd_messages(standard_logging_payload["messages"]))
         output_meta: Final = OutputMeta(
             messages=self._get_response_messages(
                 standard_logging_payload=standard_logging_payload,
@@ -241,22 +426,20 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         if isinstance(metadata, dict):
             metadata_parent_id = metadata.get("parent_id")
 
-        meta: Final = Meta(
-            kind=self._get_datadog_span_kind(standard_logging_payload.get("call_type"), metadata_parent_id),
-            input=input_meta,
-            output=output_meta,
-            metadata=self._get_dd_llm_obs_payload_metadata(standard_logging_payload),
-            error=error_info,
-        )
+        tool_definitions: Final = _to_dd_tool_definitions(standard_logging_payload.get("model_parameters"))
+        span_kind: Final = self._get_datadog_span_kind(standard_logging_payload.get("call_type"), metadata_parent_id)
+        payload_metadata: Final = self._get_dd_llm_obs_payload_metadata(standard_logging_payload)
 
-        # Calculate metrics (you may need to adjust these based on available data)
-        metrics: Final = LLMMetrics(
-            input_tokens=float(standard_logging_payload.get("prompt_tokens", 0)),
-            output_tokens=float(standard_logging_payload.get("completion_tokens", 0)),
-            total_tokens=float(standard_logging_payload.get("total_tokens", 0)),
-            total_cost=float(standard_logging_payload.get("response_cost", 0)),
-            time_to_first_token=self._get_time_to_first_token_seconds(standard_logging_payload),
-        )
+        meta: Final[Meta] = {
+            "kind": span_kind,
+            "input": input_meta,
+            "output": output_meta,
+            "metadata": payload_metadata,
+            "error": error_info,
+            **({"tool_definitions": tool_definitions} if tool_definitions else {}),
+        }
+
+        metrics: Final = self._assemble_metrics(standard_logging_payload)
 
         payload: Final[LLMObsPayload] = LLMObsPayload(
             parent_id=metadata_parent_id if metadata_parent_id else "undefined",
@@ -314,6 +497,45 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                 )
         return error_info
 
+    def _assemble_metrics(self, standard_logging_payload: StandardLoggingPayload) -> LLMMetrics:
+        """
+        Build the span metrics, including the prompt-cache counts LLM Obs charts cache savings from.
+
+        Cache counts resolve through the same owners the savings dashboard uses, so every provider
+        spelling is covered, and `non_cached_input_tokens` subtracts BOTH cache categories because
+        litellm's normalized prompt count includes both (the invariant the cost calculator's custom
+        pricing helper documents). A zero residual on a fully cached request is real data and is
+        emitted; a zero read or write count is absence and is not.
+        """
+        prompt_tokens: Final = float(standard_logging_payload.get("prompt_tokens", 0))
+        completion_tokens: Final = float(standard_logging_payload.get("completion_tokens", 0))
+        total_tokens: Final = float(standard_logging_payload.get("total_tokens", 0))
+        total_cost: Final = float(standard_logging_payload.get("response_cost", 0))
+        time_to_first_token: Final = self._get_time_to_first_token_seconds(standard_logging_payload)
+
+        raw_usage: Final = (standard_logging_payload.get("metadata") or {}).get("usage_object")
+        usage_object: Final = raw_usage if isinstance(raw_usage, dict) else None
+        cache_read: Final = float(extract_cache_read_tokens(usage_object))
+        cache_write: Final = float(extract_cache_creation_tokens(usage_object))
+
+        metrics: Final[LLMMetrics] = {
+            "input_tokens": prompt_tokens,
+            "output_tokens": completion_tokens,
+            "total_tokens": total_tokens,
+            "total_cost": total_cost,
+            "time_to_first_token": time_to_first_token,
+            **(
+                {
+                    **({"cache_read_input_tokens": cache_read} if cache_read else {}),
+                    **({"cache_write_input_tokens": cache_write} if cache_write else {}),
+                    "non_cached_input_tokens": max(prompt_tokens - cache_read - cache_write, 0.0),
+                }
+                if cache_read or cache_write
+                else {}
+            ),
+        }
+        return metrics
+
     def _get_time_to_first_token_seconds(self, standard_logging_payload: StandardLoggingPayload) -> float:
         """
         Get the time to first token in seconds
@@ -335,7 +557,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
     def _get_response_messages(
         self, standard_logging_payload: StandardLoggingPayload, call_type: str | None
-    ) -> list[object]:
+    ) -> tuple[Message, ...]:
         """
         Get the messages from the response object
 
@@ -344,7 +566,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
         response_obj = standard_logging_payload.get("response")
         if response_obj is None:
-            return []
+            return ()
 
         # edge case: handle response_obj is a string representation of a dict
         if isinstance(response_obj, str):
@@ -357,7 +579,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                     # fallback to json parsing
                     response_obj = json.loads(str(response_obj))
                 except json.JSONDecodeError:
-                    return []
+                    return ()
 
         if call_type in [
             CallTypes.completion.value,
@@ -375,12 +597,12 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                 if isinstance(response_obj, dict) and "choices" in response_obj:
                     choices: Final = response_obj["choices"]
                     if choices and len(choices) > 0 and "message" in choices[0]:
-                        return [choices[0]["message"]]
-                return []
+                        return _to_dd_messages([choices[0]["message"]])
+                return ()
             except (KeyError, IndexError, TypeError):
                 # In case of any error accessing the response structure, return empty list
-                return []
-        return []
+                return ()
+        return ()
 
     def _get_datadog_span_kind(
         self, call_type: str | None, parent_id: str | None = None
@@ -485,17 +707,6 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         # Default fallback for unknown or passthrough operations
         return "llm"
 
-    def _ensure_string_content(self, messages: str | Sequence[object] | Mapping[object, object] | None) -> list[object]:
-        if messages is None:
-            return []
-        if isinstance(messages, str):
-            return [messages]
-        elif isinstance(messages, list):
-            return [message for message in messages]
-        elif isinstance(messages, dict):
-            return [str(messages.get("content", ""))]
-        return []
-
     def _get_dd_llm_obs_payload_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, object]:
         """
         Fields to track in DD LLM Observability metadata from litellm standard logging payload
@@ -524,10 +735,6 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         spend_metrics: Final = self._get_spend_metrics(standard_logging_payload)
         _metadata.update({"spend_metrics": dict(spend_metrics)})
 
-        ## extract tool calls and add to metadata
-        tool_call_metadata: Final = self._extract_tool_call_metadata(standard_logging_payload)
-        _metadata.update(tool_call_metadata)
-
         _standard_logging_metadata: Final[dict] = dict(standard_logging_payload.get("metadata", {})) or {}
         _metadata.update(_standard_logging_metadata)
         return _metadata
@@ -647,107 +854,3 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                 verbose_logger.debug("Original value: %s", user_api_key_budget_reset_at)
 
         return spend_metrics
-
-    def _process_input_messages_preserving_tool_calls(self, messages: Sequence[object]) -> list[dict[str, object]]:
-        """
-        Process input messages while preserving tool_calls and tool message types.
-
-        This bypasses the lossy string conversion when tool calls are present,
-        allowing complex nested tool_calls objects to be preserved for Datadog.
-        """
-        processed: Final = []
-        for msg in messages:
-            if isinstance(msg, dict):
-                # Preserve messages with tool_calls or tool role as-is
-                if "tool_calls" in msg or msg.get("role") == "tool":
-                    processed.append(msg)
-                else:
-                    # For regular messages, still apply string conversion
-                    converted = handle_any_messages_to_chat_completion_str_messages_conversion([msg])
-                    processed.extend(converted)
-            else:
-                # For non-dict messages, apply string conversion
-                converted = handle_any_messages_to_chat_completion_str_messages_conversion([msg])
-                processed.extend(converted)
-        return processed
-
-    @staticmethod
-    def _tool_calls_kv_pair(tool_calls: list[dict[str, Any]]) -> dict[str, object]:
-        """
-        Extract tool call information into key-value pairs for Datadog metadata.
-
-        Similar to OpenTelemetry's implementation but adapted for Datadog's format.
-        """
-        kv_pairs: Final[dict[str, object]] = {}
-        for idx, tool_call in enumerate(tool_calls):
-            try:
-                # Extract tool call ID
-                tool_id = tool_call.get("id")
-                if tool_id:
-                    kv_pairs[f"tool_calls.{idx}.id"] = tool_id
-
-                # Extract tool call type
-                tool_type = tool_call.get("type")
-                if tool_type:
-                    kv_pairs[f"tool_calls.{idx}.type"] = tool_type
-
-                # Extract function information
-                function = tool_call.get("function")
-                if function:
-                    function_name = function.get("name")
-                    if function_name:
-                        kv_pairs[f"tool_calls.{idx}.function.name"] = function_name
-
-                    function_arguments = function.get("arguments")
-                    if function_arguments:
-                        # Store arguments as JSON string for Datadog
-                        if isinstance(function_arguments, str):
-                            kv_pairs[f"tool_calls.{idx}.function.arguments"] = function_arguments
-                        else:
-                            import json
-
-                            kv_pairs[f"tool_calls.{idx}.function.arguments"] = json.dumps(function_arguments)
-            except (KeyError, TypeError, ValueError) as e:
-                verbose_logger.debug("DataDogLLMObs: Error processing tool call %s: %s", idx, e)
-                continue
-
-        return kv_pairs
-
-    def _extract_tool_call_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, object]:
-        """
-        Extract tool call information from both input messages and response for Datadog metadata.
-        """
-        tool_call_metadata: Final[dict[str, object]] = {}
-
-        try:
-            # Extract tool calls from input messages
-            messages: Final = standard_logging_payload.get("messages", [])
-            if messages and isinstance(messages, list):
-                for message in messages:
-                    if isinstance(message, dict) and "tool_calls" in message:
-                        tool_calls = message.get("tool_calls")
-                        if tool_calls:
-                            input_tool_calls_kv = self._tool_calls_kv_pair(tool_calls)
-                            # Prefix with "input_" to distinguish from response tool calls
-                            for key, value in input_tool_calls_kv.items():
-                                tool_call_metadata[f"input_{key}"] = value
-
-            # Extract tool calls from response
-            response_obj: Final = standard_logging_payload.get("response")
-            if response_obj and isinstance(response_obj, dict):
-                choices: Final = response_obj.get("choices", [])
-                for choice in choices:
-                    if isinstance(choice, dict):
-                        message = choice.get("message")
-                        if message and isinstance(message, dict):
-                            tool_calls = message.get("tool_calls")
-                            if tool_calls:
-                                response_tool_calls_kv = self._tool_calls_kv_pair(tool_calls)
-                                # Prefix with "output_" to distinguish from input tool calls
-                                for key, value in response_tool_calls_kv.items():
-                                    tool_call_metadata[f"output_{key}"] = value
-
-        except Exception as e:
-            verbose_logger.debug("DataDogLLMObs: Error extracting tool call metadata: %s", e)
-
-        return tool_call_metadata
diff --git a/litellm/integrations/otel/model/payloads.py b/litellm/integrations/otel/model/payloads.py
index d35405538f6..e8ed269f6cb 100644
--- a/litellm/integrations/otel/model/payloads.py
+++ b/litellm/integrations/otel/model/payloads.py
@@ -6,6 +6,7 @@ import json
 from collections.abc import Mapping
 from dataclasses import dataclass, field
 from enum import Enum
+from types import MappingProxyType
 from typing import TYPE_CHECKING, ClassVar, Final, cast
 from urllib.parse import urlsplit
 
@@ -62,6 +63,31 @@ if TYPE_CHECKING:
 # --- typed sub-structures ---------------------------------------------------- #
 
 
+def _cache_token_value(*values: object) -> int | None:
+    explicit_zero = False
+    invalid_before_zero = False
+    for raw_value in values:
+        if raw_value is None:
+            continue
+        if isinstance(raw_value, bool):
+            parsed = None
+        else:
+            try:
+                parsed = as_int(raw_value)
+            except (OverflowError, ValueError):
+                parsed = None
+        if parsed is None:
+            if not explicit_zero:
+                invalid_before_zero = True
+        elif parsed > 0:
+            return parsed
+        elif parsed == 0:
+            explicit_zero = True
+        elif not explicit_zero:
+            invalid_before_zero = True
+    return 0 if explicit_zero and not invalid_before_zero else None
+
+
 @dataclass(frozen=True)
 class LLMRequestParams:
     temperature: float | None = None
@@ -104,12 +130,25 @@ class LLMUsage:
         metadata: Final[Mapping[str, object]] = payload.get("metadata") or {}
         raw_usage: Final = metadata.get("usage_object")
         usage_object: Final[Mapping[str, object]] = raw_usage if isinstance(raw_usage, Mapping) else {}
+        raw_details: Final = usage_object.get("prompt_tokens_details")
+        prompt_details: Final[Mapping[str, object]] = (
+            raw_details if isinstance(raw_details, Mapping) else MappingProxyType({})
+        )
         return cls(
             input_tokens=as_int(payload.get("prompt_tokens")),
             output_tokens=as_int(payload.get("completion_tokens")),
             total_tokens=as_int(payload.get("total_tokens")),
-            cache_creation_input_tokens=as_int(usage_object.get("cache_creation_input_tokens")),
-            cache_read_input_tokens=as_int(usage_object.get("cache_read_input_tokens")),
+            cache_creation_input_tokens=_cache_token_value(
+                usage_object.get("cache_creation_input_tokens"),
+                prompt_details.get("cache_write_tokens"),
+                prompt_details.get("cache_creation_tokens"),
+                prompt_details.get("cache_creation_input_tokens"),
+            ),
+            cache_read_input_tokens=_cache_token_value(
+                usage_object.get("cache_read_input_tokens"),
+                prompt_details.get("cached_tokens"),
+                usage_object.get("prompt_cache_hit_tokens"),
+            ),
         )
 
 
diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index add91033ff3..975a9bd8639 100644
--- a/litellm/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -8,6 +8,7 @@ import math
 import os
 import sys
 from collections.abc import Awaitable, Callable, Mapping, Sequence
+from dataclasses import replace
 from datetime import datetime, timedelta
 from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, TypeVar, cast
 
@@ -58,6 +59,7 @@ from litellm.types.utils import (
 
 if TYPE_CHECKING:
     from apscheduler.schedulers.asyncio import AsyncIOScheduler
+    from prometheus_client import Gauge
     from prometheus_client.metrics import MetricWrapperBase
 
     from litellm.router import Router
@@ -476,6 +478,30 @@ class PrometheusLogger(CustomLogger):
                 labelnames=self.get_labels_for_metric("litellm_remaining_api_key_tokens_for_model"),
             )
 
+            self.litellm_api_key_rate_limit_allowed_metric = self._gauge_factory(
+                "litellm_api_key_rate_limit_allowed_metric",
+                "Configured rate limit for the API Key in the current window (rpm_limit / tpm_limit), by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_api_key_rate_limit_allowed_metric"),
+            )
+
+            self.litellm_api_key_rate_limit_used_metric = self._gauge_factory(
+                "litellm_api_key_rate_limit_used_metric",
+                "Requests or tokens the API Key has consumed in the current rate limit window, by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_api_key_rate_limit_used_metric"),
+            )
+
+            self.litellm_team_rate_limit_allowed_metric = self._gauge_factory(
+                "litellm_team_rate_limit_allowed_metric",
+                "Configured rate limit for the Team in the current window (team rpm_limit / tpm_limit), by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_team_rate_limit_allowed_metric"),
+            )
+
+            self.litellm_team_rate_limit_used_metric = self._gauge_factory(
+                "litellm_team_rate_limit_used_metric",
+                "Requests or tokens the Team has consumed in the current rate limit window, by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_team_rate_limit_used_metric"),
+            )
+
             ########################################
             # LLM API Deployment Metrics / analytics
             ########################################
@@ -1475,6 +1501,11 @@ class PrometheusLogger(CustomLogger):
             model_id=enum_values.model_id,
         )
 
+        self._set_key_and_team_rate_limit_metrics(
+            standard_logging_payload=standard_logging_payload,  # pyright: ignore[reportArgumentType]  # isinstance(dict) above narrows the TypedDict to dict[Unknown, Unknown]
+            enum_values=enum_values,
+        )
+
         # set latency metrics
         self._set_latency_metrics(
             kwargs=kwargs,
@@ -2002,17 +2033,102 @@ class PrometheusLogger(CustomLogger):
         """
         if standard_logging_payload is None:
             return None
+        return PrometheusLogger._get_int_from_v3_rate_limit_headers(
+            standard_logging_payload=standard_logging_payload,
+            header_name=f"x-ratelimit-model_per_key-remaining-{rate_limit_type}",
+        )
+
+    @staticmethod
+    def _get_int_from_v3_rate_limit_headers(
+        standard_logging_payload: StandardLoggingPayload,
+        header_name: str,
+    ) -> int | None:
         hidden_params: Final = standard_logging_payload.get("hidden_params")
         if hidden_params is None:
             return None
-        additional_headers: Final = hidden_params.get("additional_headers")
+        additional_headers: Final[Mapping[str, object] | None] = hidden_params.get("additional_headers")
         if additional_headers is None:
             return None
-        value: Final = dict(additional_headers).get(f"x-ratelimit-model_per_key-remaining-{rate_limit_type}")
+        value: Final = additional_headers.get(header_name)
         if isinstance(value, bool) or not isinstance(value, int):
             return None
         return value
 
+    def _set_key_and_team_rate_limit_metrics(
+        self,
+        standard_logging_payload: StandardLoggingPayload,
+        enum_values: UserAPIKeyLabelValues,
+    ) -> None:
+        """
+        Export the key-level and team-level RPM / TPM limit and current window
+        usage from the ``x-ratelimit-{api_key,team}-{limit,remaining}-*``
+        headers the v3 rate limiter mirrors into the logging payload. The
+        limiter already read these counters (from Redis when configured) on
+        the request path, so no extra store lookup happens here. Descriptors
+        without a configured limit emit no header, so their series is removed
+        rather than left at the value from before the limit was dropped.
+        """
+        descriptor_gauges: Final[
+            tuple[tuple[Literal["api_key", "team"], DEFINED_PROMETHEUS_METRICS, Gauge, Gauge], ...]
+        ] = (
+            (
+                "api_key",
+                "litellm_api_key_rate_limit_allowed_metric",
+                self.litellm_api_key_rate_limit_allowed_metric,
+                self.litellm_api_key_rate_limit_used_metric,
+            ),
+            (
+                "team",
+                "litellm_team_rate_limit_allowed_metric",
+                self.litellm_team_rate_limit_allowed_metric,
+                self.litellm_team_rate_limit_used_metric,
+            ),
+        )
+        for descriptor_key, metric_name, allowed_gauge, used_gauge in descriptor_gauges:
+            for rate_limit_type in ("requests", "tokens"):
+                self._set_rate_limit_allowed_and_used_gauges(
+                    standard_logging_payload=standard_logging_payload,
+                    enum_values=enum_values,
+                    descriptor_key=descriptor_key,
+                    metric_name=metric_name,
+                    allowed_gauge=allowed_gauge,
+                    used_gauge=used_gauge,
+                    rate_limit_type=rate_limit_type,
+                )
+
+    def _set_rate_limit_allowed_and_used_gauges(
+        self,
+        standard_logging_payload: StandardLoggingPayload,
+        enum_values: UserAPIKeyLabelValues,
+        descriptor_key: Literal["api_key", "team"],
+        metric_name: DEFINED_PROMETHEUS_METRICS,
+        allowed_gauge: Gauge,
+        used_gauge: Gauge,
+        rate_limit_type: Literal["requests", "tokens"],
+    ) -> None:
+        limit: Final = self._get_int_from_v3_rate_limit_headers(
+            standard_logging_payload=standard_logging_payload,
+            header_name=f"x-ratelimit-{descriptor_key}-limit-{rate_limit_type}",
+        )
+        remaining: Final = self._get_int_from_v3_rate_limit_headers(
+            standard_logging_payload=standard_logging_payload,
+            header_name=f"x-ratelimit-{descriptor_key}-remaining-{rate_limit_type}",
+        )
+        labelled_values: Final = replace(enum_values, rate_limit_type=rate_limit_type)
+        labelnames: Final = self.get_labels_for_metric(metric_name)
+        labels: Final = prometheus_label_factory(
+            supported_enum_labels=labelnames,
+            enum_values=labelled_values,
+            label_context=PrometheusLabelFactoryContext(labelled_values),
+        )
+        if limit is None or remaining is None:
+            label_values: Final = tuple(labels.get(label) for label in labelnames)
+            self._bounded_prometheus_series_tracker.remove_series(allowed_gauge, label_values)
+            self._bounded_prometheus_series_tracker.remove_series(used_gauge, label_values)
+            return
+        allowed_gauge.labels(**labels).set(limit)
+        used_gauge.labels(**labels).set(limit - remaining)
+
     def _set_virtual_key_rate_limit_metrics(
         self,
         user_api_key: str | None,
diff --git a/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py b/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py
index c54790b8ae7..c1ccf09d5d6 100644
--- a/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py
+++ b/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py
@@ -60,6 +60,10 @@ class BoundedPrometheusSeriesTracker:
                         break
                     del series[tracked_label_values]
 
+    def remove_series(self, metric: object, label_values: tuple[str | None, ...]) -> bool:
+        """Drop one child series, True when it is gone (removed or never existed)."""
+        return self._remove_metric_child(metric, label_values)
+
     def _should_run_ttl_cleanup(
         self,
         metric_name: str,
diff --git a/litellm/litellm_core_utils/get_model_cost_map.py b/litellm/litellm_core_utils/get_model_cost_map.py
index 2043a9e2f89..9cba5db8ab7 100644
--- a/litellm/litellm_core_utils/get_model_cost_map.py
+++ b/litellm/litellm_core_utils/get_model_cost_map.py
@@ -12,6 +12,7 @@ import asyncio
 import json
 import os
 import random
+import time
 from collections.abc import Awaitable, Callable
 from dataclasses import dataclass
 from datetime import datetime, timezone
@@ -154,18 +155,6 @@ class GetModelCostMap:
 
         return True
 
-    @staticmethod
-    def fetch_remote_model_cost_map(url: str, timeout: int = 5) -> dict:
-        """
-        Fetch the model cost map from a remote URL.
-
-        Returns the parsed JSON dict. Raises on network/parse errors
-        (caller is expected to handle).
-        """
-        response: Final = httpx.get(url, timeout=timeout)
-        response.raise_for_status()
-        return response.json()
-
 
 RETRYABLE_FETCH_STATUS_CODES: Final = frozenset({429, 500, 502, 503, 504})
 MODEL_COST_MAP_FETCH_MAX_ATTEMPTS: Final = 3
@@ -212,6 +201,13 @@ class _AsyncGetClient(Protocol):
     def get(self, url: str, *, timeout: float | None = None) -> Awaitable[httpx.Response]: ...
 
 
+class _SyncGetClient(Protocol):
+    def get(self, url: str, *, timeout: float | None = None) -> httpx.Response: ...
+
+
+_FetchAttemptOutcome = ModelCostMapReloaded | ModelCostMapReloadUnavailable | _FetchAttemptRetryable
+
+
 def _default_reload_client() -> _AsyncGetClient:
     from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
     from litellm.types.llms.custom_http import httpxSpecialProvider
@@ -219,13 +215,30 @@ def _default_reload_client() -> _AsyncGetClient:
     return get_async_httpx_client(llm_provider=httpxSpecialProvider.ModelCostMap)
 
 
-async def _attempt_fetch(
-    client: _AsyncGetClient, url: str, timeout: int
-) -> ModelCostMapReloaded | ModelCostMapReloadUnavailable | _FetchAttemptRetryable:
+def _classify_fetch_error(error: httpx.HTTPError | httpx.InvalidURL, url: str) -> _FetchAttemptOutcome:
+    reason: Final = f"{type(error).__name__} fetching {url}: {error}"
+    if isinstance(error, (httpx.InvalidURL, httpx.UnsupportedProtocol)):
+        return ModelCostMapReloadUnavailable(reason=reason)
+    return _FetchAttemptRetryable(reason=reason, retry_after_seconds=None)
+
+
+async def _attempt_fetch(client: _AsyncGetClient, url: str, timeout: int) -> _FetchAttemptOutcome:
     try:
         response: Final = await client.get(url, timeout=timeout)
-    except httpx.HTTPError as e:
-        return _FetchAttemptRetryable(reason=f"{type(e).__name__} fetching {url}: {e}", retry_after_seconds=None)
+    except (httpx.HTTPError, httpx.InvalidURL) as e:
+        return _classify_fetch_error(e, url)
+    return _classify_fetch_response(response, url)
+
+
+def _attempt_fetch_sync(client: _SyncGetClient, url: str, timeout: int) -> _FetchAttemptOutcome:
+    try:
+        response: Final = client.get(url, timeout=timeout)
+    except (httpx.HTTPError, httpx.InvalidURL) as e:
+        return _classify_fetch_error(e, url)
+    return _classify_fetch_response(response, url)
+
+
+def _classify_fetch_response(response: httpx.Response, url: str) -> _FetchAttemptOutcome:
     if response.status_code in RETRYABLE_FETCH_STATUS_CODES:
         return _FetchAttemptRetryable(
             reason=f"HTTP {response.status_code} from {url}",
@@ -242,6 +255,22 @@ async def _attempt_fetch(
     return ModelCostMapReloaded(model_cost_map=parsed)
 
 
+def _next_retry_wait(
+    outcome: _FetchAttemptRetryable, attempt: int, max_attempts: int, rng: random.Random
+) -> float | ModelCostMapReloadUnavailable:
+    if attempt == max_attempts:
+        return ModelCostMapReloadUnavailable(reason=f"{outcome.reason} (after {max_attempts} attempts)")
+    wait_seconds: Final = _retry_wait_seconds(outcome=outcome, attempt=attempt, rng=rng)
+    verbose_logger.warning(
+        "LiteLLM: model cost map fetch attempt %d/%d failed (%s); retrying in %.1fs",
+        attempt,
+        max_attempts,
+        outcome.reason,
+        wait_seconds,
+    )
+    return wait_seconds
+
+
 async def _fetch_remote_model_cost_map_with_retry(
     url: str,
     timeout: int,
@@ -254,20 +283,32 @@ async def _fetch_remote_model_cost_map_with_retry(
         outcome = await _attempt_fetch(client=client, url=url, timeout=timeout)
         if not isinstance(outcome, _FetchAttemptRetryable):
             return outcome
-        if attempt == max_attempts:
-            return ModelCostMapReloadUnavailable(reason=f"{outcome.reason} (after {max_attempts} attempts)")
-        wait_seconds = _retry_wait_seconds(outcome=outcome, attempt=attempt, rng=rng)
-        verbose_logger.warning(
-            "LiteLLM: model cost map fetch attempt %d/%d failed (%s); retrying in %.1fs",
-            attempt,
-            max_attempts,
-            outcome.reason,
-            wait_seconds,
-        )
+        wait_seconds = _next_retry_wait(outcome=outcome, attempt=attempt, max_attempts=max_attempts, rng=rng)
+        if isinstance(wait_seconds, ModelCostMapReloadUnavailable):
+            return wait_seconds
         await sleep(wait_seconds)
     return ModelCostMapReloadUnavailable(reason="model cost map fetch failed")
 
 
+def _fetch_remote_model_cost_map_with_retry_sync(
+    url: str,
+    timeout: int,
+    max_attempts: int,
+    sleep: Callable[[float], None],
+    rng: random.Random,
+    client: _SyncGetClient,
+) -> ModelCostMapReloadResult:
+    for attempt in range(1, max_attempts + 1):
+        outcome = _attempt_fetch_sync(client=client, url=url, timeout=timeout)
+        if not isinstance(outcome, _FetchAttemptRetryable):
+            return outcome
+        wait_seconds = _next_retry_wait(outcome=outcome, attempt=attempt, max_attempts=max_attempts, rng=rng)
+        if isinstance(wait_seconds, ModelCostMapReloadUnavailable):
+            return wait_seconds
+        sleep(wait_seconds)
+    return ModelCostMapReloadUnavailable(reason="model cost map fetch failed")
+
+
 async def refetch_model_cost_map(
     url: str,
     timeout: int = 5,
@@ -423,13 +464,21 @@ def _finalize_model_cost_map(model_cost: dict) -> dict:
     return _expand_model_aliases(model_cost)
 
 
-def get_model_cost_map(url: str) -> dict:
+def get_model_cost_map(
+    url: str,
+    timeout: int = 5,
+    max_attempts: int = MODEL_COST_MAP_FETCH_MAX_ATTEMPTS,
+    sleep: Callable[[float], None] = time.sleep,
+    rng: random.Random | None = None,
+    client: "_SyncGetClient | None" = None,
+) -> dict:
     """
     Public entry point — returns the model cost map dict.
 
     1. If ``LITELLM_LOCAL_MODEL_COST_MAP`` is set, uses the local backup only.
-    2. Otherwise fetches from ``url``, validates integrity, and falls back
-       to the local backup on any failure.
+    2. Otherwise fetches from ``url``, retrying transient HTTP errors
+       (429/5xx/transport) with Retry-After-aware backoff, validates
+       integrity, and falls back to the local backup on any failure.
 
     Only the backup model count is cached (a single int) for validation.
     The full backup dict is only parsed when it must be *returned* as a
@@ -448,17 +497,24 @@ def get_model_cost_map(url: str) -> dict:
     _cost_map_source_info.url = url
     _cost_map_source_info.is_env_forced = False
 
-    try:
-        content: Final = GetModelCostMap.fetch_remote_model_cost_map(url)
-    except Exception as e:
+    result: Final = _fetch_remote_model_cost_map_with_retry_sync(
+        url=url,
+        timeout=timeout,
+        max_attempts=max_attempts,
+        sleep=sleep,
+        rng=rng if rng is not None else random.Random(),
+        client=client if client is not None else httpx,
+    )
+    if isinstance(result, ModelCostMapReloadUnavailable):
         verbose_logger.warning(
             "LiteLLM: Failed to fetch remote model cost map from %s: %s. Falling back to local backup.",
             url,
-            str(e),
+            result.reason,
         )
         _cost_map_source_info.source = "local"
-        _cost_map_source_info.fallback_reason = f"Remote fetch failed: {e}"
+        _cost_map_source_info.fallback_reason = f"Remote fetch failed: {result.reason}"
         return _finalize_model_cost_map(GetModelCostMap.load_local_model_cost_map())
+    content: Final = result.model_cost_map
 
     # Validate using cached count (cheap int comparison, no file I/O)
     if not GetModelCostMap.validate_model_cost_map(
diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py
index e6402e8c1bd..ba59e3fa997 100644
--- a/litellm/litellm_core_utils/prompt_templates/factory.py
+++ b/litellm/litellm_core_utils/prompt_templates/factory.py
@@ -4957,10 +4957,13 @@ def make_valid_bedrock_tool_name(input_tool_name: str) -> str:
 
 
 def add_cache_point_tool_block(tool: dict, model: str | None = None) -> BedrockToolBlock | None:
-    from litellm.llms.bedrock.common_utils import is_claude_4_5_on_bedrock
+    from litellm.llms.bedrock.common_utils import (
+        bedrock_model_accepts_cache_points,
+        is_claude_4_5_on_bedrock,
+    )
 
     cache_control: Final = tool.get("cache_control", None)
-    if cache_control is not None:
+    if cache_control is not None and bedrock_model_accepts_cache_points(model):
         cache_point: Final = cache_control.get("type", "ephemeral")
         if cache_point == "ephemeral":
             cache_point_block: Final[CachePointBlock] = {"type": "default"}
diff --git a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
index 3978a01a5db..0e01577b20e 100644
--- a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
+++ b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
@@ -36,6 +36,8 @@ from litellm.types.utils import (
 from litellm.utils import print_verbose, token_counter
 
 if TYPE_CHECKING:
+    from openai.types.completion_usage import CompletionUsage
+
     from litellm.litellm_core_utils.litellm_logging import Logging
     from litellm.types.litellm_core_utils.streaming_chunk_builder_utils import (
         UsagePerChunk,
@@ -794,7 +796,7 @@ class ChunkProcessor:
 
     @staticmethod
     def _extract_usage_chunk(chunk: "_UsageBearingChunk | ModelResponse | ModelResponseStream") -> Usage | None:
-        usage_chunk: Usage | None = None
+        usage_chunk: Usage | CompletionUsage | None = None
         if hasattr(chunk, "usage") and chunk.usage is not None:
             usage_chunk = chunk.usage
         elif "usage" in chunk:
@@ -806,7 +808,9 @@ class ChunkProcessor:
 
         if isinstance(usage_chunk, dict):
             return Usage(**usage_chunk)
-        return usage_chunk
+        if usage_chunk is None or isinstance(usage_chunk, Usage):
+            return usage_chunk
+        return Usage(**usage_chunk.model_dump())
 
     def _calculate_usage_per_chunk(
         self,
diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py
index c60ebd844ba..d23690976ad 100644
--- a/litellm/llms/anthropic/common_utils.py
+++ b/litellm/llms/anthropic/common_utils.py
@@ -1378,31 +1378,38 @@ def process_anthropic_headers(headers: httpx.Headers | dict) -> dict:
     return additional_headers
 
 
-def _anthropic_model_entry(model: ModelInfoResponse, created_at: str) -> Mapping[str, object]:
+def _anthropic_model_entry(
+    model: ModelInfoResponse, created_at: str, display_names: Mapping[str, str]
+) -> Mapping[str, object]:
     return {  # mutable-ok: JSON response body, serialized by the route and never mutated
         "type": "model",
         "id": model["id"],
-        "display_name": model["id"],
+        "display_name": display_names.get(model["id"], model["id"]),
         "created_at": created_at,
         "max_input_tokens": model.get("max_input_tokens"),
         "max_tokens": model.get("max_output_tokens"),
     }
 
 
-def create_anthropic_model_list_response(models: Sequence[ModelInfoResponse]) -> Mapping[str, object]:
+def create_anthropic_model_list_response(
+    models: Sequence[ModelInfoResponse],
+    display_names: Mapping[str, str] = MappingProxyType({}),
+) -> Mapping[str, object]:
     """Build the Anthropic-native /v1/models envelope.
 
     Clients that send an anthropic-version header parse the Anthropic Models API
     shape (type/display_name/created_at plus has_more/first_id/last_id) and filter
     the list themselves, so every model is returned here. The token limits carry
     over from the OpenAI-shaped listing, named as the Messages API names them, and
-    are always present because the vendor shape declares them nullable, not optional
+    are always present because the vendor shape declares them nullable, not optional.
+    display_names maps a listed model id to a configured human-readable name; ids
+    without an entry fall back to the id itself, matching the vendor behavior
     """
     created_at: Final = (
         datetime.fromtimestamp(DEFAULT_MODEL_CREATED_AT_TIME, tz=timezone.utc).isoformat().replace("+00:00", "Z")
     )
     data: Final = [  # mutable-ok: JSON response body, serialized by the route and never mutated
-        _anthropic_model_entry(model, created_at) for model in models
+        _anthropic_model_entry(model, created_at, display_names) for model in models
     ]
     return {  # mutable-ok: JSON response body, serialized by the route and never mutated
         "data": data,
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
index 45c7825344b..66e36dab2ba 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
@@ -86,22 +86,41 @@ def _decoded_sse_data_line(line: bytes) -> object | None:
         return None
 
 
-def _anthropic_error_event_payload(chunk: object) -> Mapping[str, object] | None:
+def _anthropic_event_payload(chunk: object, event_type: str) -> Mapping[str, object] | None:
     if isinstance(chunk, dict):
-        return chunk if chunk.get("type") == "error" else None
+        return chunk if chunk.get("type") == event_type else None
     if isinstance(chunk, (bytes, bytearray)):
         decoded_lines: Final = (_decoded_sse_data_line(line) for line in chunk.splitlines())
         return next(
             (
                 candidate
                 for candidate in decoded_lines
-                if isinstance(candidate, dict) and candidate.get("type") == "error"
+                if isinstance(candidate, dict) and candidate.get("type") == event_type
             ),
             None,
         )
     return None
 
 
+def _anthropic_error_event_payload(chunk: object) -> Mapping[str, object] | None:
+    return _anthropic_event_payload(chunk, "error")
+
+
+def parse_anthropic_refusal_stop_details(chunk: object) -> Mapping[str, object] | None:
+    """
+    Return the ``stop_details`` object of an Anthropic SSE ``message_delta``
+    chunk whose delta carries ``stop_reason: "refusal"`` (a safeguard refusal:
+    https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback),
+    or None for any other chunk, a plain refusal without ``stop_details`` included.
+    """
+    payload: Final = _anthropic_event_payload(chunk, "message_delta")
+    delta: Final = payload.get("delta") if payload is not None else None
+    if not isinstance(delta, dict) or delta.get("stop_reason") != "refusal":
+        return None
+    stop_details: Final = delta.get("stop_details")
+    return stop_details if isinstance(stop_details, dict) else None
+
+
 def _anthropic_error_body(chunk: object) -> Mapping[str, object] | None:
     """Return the ``error`` object of an Anthropic SSE ``event: error`` chunk, or None."""
     payload: Final = _anthropic_error_event_payload(chunk)
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/utils.py b/litellm/llms/anthropic/experimental_pass_through/messages/utils.py
index 02d82887dde..9deff950724 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/utils.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/utils.py
@@ -1,11 +1,40 @@
+from collections.abc import Mapping
 from functools import lru_cache
-from typing import Any, Final, cast, get_type_hints
+from typing import TYPE_CHECKING, Any, Final, cast, get_type_hints
 
 from litellm.types.llms.anthropic import AnthropicMessagesRequestOptionalParams
 from litellm.types.llms.anthropic_messages.anthropic_response import (
     AnthropicMessagesResponse,
 )
 
+if TYPE_CHECKING:
+    from litellm.exceptions import ContentPolicyViolationError
+
+
+def get_safeguard_refusal_stop_details(response: object) -> Mapping[str, Any] | None:
+    """
+    Return the ``stop_details`` of an Anthropic Messages response refused by a
+    safeguard (``stop_reason: "refusal"`` carrying ``stop_details``:
+    https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback),
+    or None for any other response, a plain refusal without ``stop_details`` included.
+    """
+    if not isinstance(response, dict) or response.get("stop_reason") != "refusal":
+        return None
+    stop_details: Final = response.get("stop_details")
+    return stop_details if isinstance(stop_details, dict) else None
+
+
+def safeguard_refusal_error(model: str, stop_details: Mapping[str, object]) -> "ContentPolicyViolationError":
+    """The exception a safeguard-refused Anthropic response converts into so the
+    content-policy fallback chain can re-dispatch it."""
+    from litellm.exceptions import ContentPolicyViolationError
+
+    return ContentPolicyViolationError(
+        message=f"Anthropic safeguard refusal (category: {stop_details.get('category')}).",
+        model=model,
+        llm_provider="anthropic",
+    )
+
 
 @lru_cache(maxsize=1)
 def _anthropic_messages_optional_param_keys() -> frozenset[str]:
@@ -100,14 +129,12 @@ def mock_response(
             model=model,
         )
     return AnthropicMessagesResponse(
-        **{
-            "content": [{"text": mock_response, "type": "text"}],
-            "id": "msg_013Zva2CMHLNnXjNJJKqJ2EF",
-            "model": "claude-sonnet-4-20250514",
-            "role": "assistant",
-            "stop_reason": "end_turn",
-            "stop_sequence": None,
-            "type": "message",
-            "usage": {"input_tokens": 2095, "output_tokens": 503},
-        }
+        content=[{"text": mock_response, "type": "text"}],
+        id="msg_013Zva2CMHLNnXjNJJKqJ2EF",
+        model="claude-sonnet-4-20250514",
+        role="assistant",
+        stop_reason="end_turn",
+        stop_sequence=None,
+        type="message",
+        usage={"input_tokens": 2095, "output_tokens": 503},
     )
diff --git a/litellm/llms/azure_ai/vector_stores/transformation.py b/litellm/llms/azure_ai/vector_stores/transformation.py
index 044b8f5243c..db1a0fc89a3 100644
--- a/litellm/llms/azure_ai/vector_stores/transformation.py
+++ b/litellm/llms/azure_ai/vector_stores/transformation.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final
 
@@ -22,6 +24,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -118,10 +121,11 @@ class AzureAIVectorStoreConfig(BaseQueryEmbeddingVectorStoreConfig, BaseAzureLLM
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: Router | None = None,
         embedding_executor: VectorStoreEmbeddingExecutor | None = None,
     ) -> tuple[str, dict[str, object]]:
         query_text: Final = self.query_text(query)
-        query_vector: Final = self.embed_query(query_text, litellm_params, embedding_executor)
+        query_vector: Final = self.embed_query(query_text, litellm_params, embedding_executor, router)
         return self._search_request(
             vector_store_id,
             query_text,
@@ -141,10 +145,11 @@ class AzureAIVectorStoreConfig(BaseQueryEmbeddingVectorStoreConfig, BaseAzureLLM
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: Router | None = None,
         embedding_executor: VectorStoreEmbeddingExecutor | None = None,
     ) -> tuple[str, dict[str, object]]:
         query_text: Final = self.query_text(query)
-        query_vector: Final = await self.aembed_query(query_text, litellm_params, embedding_executor)
+        query_vector: Final = await self.aembed_query(query_text, litellm_params, embedding_executor, router)
         return self._search_request(
             vector_store_id,
             query_text,
diff --git a/litellm/llms/base_llm/guardrail_translation/base_translation.py b/litellm/llms/base_llm/guardrail_translation/base_translation.py
index b07a6b986d7..220fcedb0f8 100644
--- a/litellm/llms/base_llm/guardrail_translation/base_translation.py
+++ b/litellm/llms/base_llm/guardrail_translation/base_translation.py
@@ -155,8 +155,8 @@ class BaseTranslation(ABC):
         self,
         exc: "ModifyResponseException",
         stream_started: bool = False,
-        responses_so_far: list[Any] | None = None,
-    ) -> list[bytes] | None:
+        responses_so_far: Sequence[Any] | None = None,
+    ) -> Sequence[bytes] | None:
         """
         Build the streaming chunks that deliver a guardrail block message and
         cleanly terminate the stream in this provider's wire format.
diff --git a/litellm/llms/base_llm/guardrail_translation/utils.py b/litellm/llms/base_llm/guardrail_translation/utils.py
index f09ee210e6c..9b6f9c47105 100644
--- a/litellm/llms/base_llm/guardrail_translation/utils.py
+++ b/litellm/llms/base_llm/guardrail_translation/utils.py
@@ -124,6 +124,61 @@ def blocked_responses_api_usage(original_response: object) -> ResponseAPIUsage:
     )
 
 
+def stream_item_field(item: object, field: str) -> object | None:
+    if isinstance(item, dict):
+        return item.get(field)
+    return getattr(item, field, None)
+
+
+def blocked_chat_stream_usage(original_response: object) -> tuple[int, int]:
+    """
+    ``(prompt_tokens, completion_tokens)`` for a synthetic guardrail-blocked
+    chat completions stream.
+
+    A mid-stream block carries the chunks received so far as a list; real usage
+    rides on the final chunk when the upstream sent one
+    (``stream_options.include_usage``). Non-list originals defer to
+    ``blocked_response_usage``.
+    """
+    if not isinstance(original_response, list):
+        usage: Final = blocked_response_usage(original_response)
+        return usage.get("input_tokens", 0), usage.get("output_tokens", 0)
+    usage_obj: Final = next(
+        (
+            chunk_usage
+            for item in reversed(original_response)
+            if (chunk_usage := stream_item_field(item, "usage")) is not None
+        ),
+        None,
+    )
+    return (
+        _usage_tokens(usage_obj, "prompt_tokens", "input_tokens"),
+        _usage_tokens(usage_obj, "completion_tokens", "output_tokens"),
+    )
+
+
+def blocked_responses_stream_usage(original_response: object) -> ResponseAPIUsage:
+    """
+    ``ResponseAPIUsage`` for a synthetic guardrail-blocked /v1/responses stream.
+
+    A mid-stream block carries the events received so far as a list; real usage
+    rides on the ``response.completed`` event's response when the upstream sent
+    one. Non-list originals defer to ``blocked_responses_api_usage``.
+    """
+    if not isinstance(original_response, list):
+        return blocked_responses_api_usage(original_response)
+    completed: Final = next(
+        (
+            response
+            for item in reversed(original_response)
+            if stream_item_field(item, "type") == "response.completed"
+            and (response := stream_item_field(item, "response")) is not None
+        ),
+        None,
+    )
+    return blocked_responses_api_usage(completed)
+
+
 def effective_skip_system_message_for_guardrail(guardrail_to_apply: Any) -> bool:
     per: Final = getattr(guardrail_to_apply, "skip_system_message_in_guardrail", None)
     if per is not None:
diff --git a/litellm/llms/base_llm/vector_store/transformation.py b/litellm/llms/base_llm/vector_store/transformation.py
index 95863266bf7..e7c549b7358 100644
--- a/litellm/llms/base_llm/vector_store/transformation.py
+++ b/litellm/llms/base_llm/vector_store/transformation.py
@@ -137,6 +137,7 @@ class BaseVectorStoreConfig:
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: Router | None = None,
     ) -> tuple[str, dict]:
         pass
 
@@ -149,6 +150,7 @@ class BaseVectorStoreConfig:
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: Router | None = None,
     ) -> tuple[str, dict]:
         """
         Optional async version of transform_search_vector_store_request.
@@ -164,6 +166,7 @@ class BaseVectorStoreConfig:
             litellm_logging_obj=litellm_logging_obj,
             litellm_params=litellm_params,
             extra_body=extra_body,
+            router=router,
         )
 
     @abstractmethod
@@ -252,6 +255,7 @@ class BaseQueryEmbeddingVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: Router | None = None,
         embedding_executor: VectorStoreEmbeddingExecutor | None = None,
     ) -> tuple[str, dict[str, object]]:
         pass
@@ -265,6 +269,7 @@ class BaseQueryEmbeddingVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: Router | None = None,
         embedding_executor: VectorStoreEmbeddingExecutor | None = None,
     ) -> tuple[str, dict[str, object]]:
         return self.transform_search_vector_store_request(
@@ -275,6 +280,7 @@ class BaseQueryEmbeddingVectorStoreConfig(BaseVectorStoreConfig):
             litellm_logging_obj=litellm_logging_obj,
             litellm_params=litellm_params,
             extra_body=extra_body,
+            router=router,
             embedding_executor=embedding_executor,
         )
 
@@ -299,17 +305,27 @@ class BaseQueryEmbeddingVectorStoreConfig(BaseVectorStoreConfig):
             return {str(key): value for key, value in configuration.items()}  # pyright: ignore[reportUnknownVariableType, reportUnknownArgumentType]  # litellm_params is an untyped dict, keys are re-validated as str here
         return _EMPTY_EMBEDDING_CONFIGURATION
 
+    @staticmethod
+    def query_embedding_executor(
+        embedding_executor: VectorStoreEmbeddingExecutor | None,
+        router: Router | None,
+    ) -> VectorStoreEmbeddingExecutor:
+        if embedding_executor is not None:
+            return embedding_executor
+        if router is not None:
+            return RouterVectorStoreEmbeddingExecutor(router=router, metadata=MappingProxyType({}))
+        return LiteLLMVectorStoreEmbeddingExecutor()
+
     def embed_query(
         self,
         query_text: str,
         litellm_params: Mapping[str, object],
         embedding_executor: VectorStoreEmbeddingExecutor | None,
+        router: Router | None = None,
     ) -> Sequence[float]:
         model: Final = self.query_embedding_model(litellm_params)
         configuration: Final = self.query_embedding_configuration(litellm_params)
-        executor: Final = (
-            embedding_executor if embedding_executor is not None else LiteLLMVectorStoreEmbeddingExecutor()
-        )
+        executor: Final = self.query_embedding_executor(embedding_executor, router)
         try:
             response: Final = executor.embed(model, query_text, configuration)
         except Exception as e:
@@ -321,12 +337,11 @@ class BaseQueryEmbeddingVectorStoreConfig(BaseVectorStoreConfig):
         query_text: str,
         litellm_params: Mapping[str, object],
         embedding_executor: VectorStoreEmbeddingExecutor | None,
+        router: Router | None = None,
     ) -> Sequence[float]:
         model: Final = self.query_embedding_model(litellm_params)
         configuration: Final = self.query_embedding_configuration(litellm_params)
-        executor: Final = (
-            embedding_executor if embedding_executor is not None else LiteLLMVectorStoreEmbeddingExecutor()
-        )
+        executor: Final = self.query_embedding_executor(embedding_executor, router)
         try:
             response: Final = await executor.aembed(model, query_text, configuration)
         except Exception as e:
@@ -376,6 +391,7 @@ class BaseDirectVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: Router | None = None,
     ) -> NoReturn:
         raise NotImplementedError("Direct vector store providers execute the search themselves; no HTTP request shape")
 
diff --git a/litellm/llms/bedrock/base_aws_llm.py b/litellm/llms/bedrock/base_aws_llm.py
index 852cfaa24f2..1e634ced29b 100644
--- a/litellm/llms/bedrock/base_aws_llm.py
+++ b/litellm/llms/bedrock/base_aws_llm.py
@@ -1442,7 +1442,7 @@ class BaseAWSLLM:
     @tracer.wrap()
     def get_request_headers(
         self,
-        credentials: Credentials,
+        credentials: Credentials | None,
         aws_region_name: str,
         extra_headers: dict | None,
         endpoint_url: str,
@@ -1469,9 +1469,13 @@ class BaseAWSLLM:
             try:
                 from botocore.auth import SigV4Auth
                 from botocore.awsrequest import AWSRequest
+                from botocore.exceptions import NoCredentialsError
             except ImportError:
                 raise ImportError("Missing boto3 to call bedrock. Run 'pip install boto3'.")
 
+            if credentials is None:
+                raise NoCredentialsError()
+
             # Filter headers for AWS signature calculation
             # AWS SigV4 only includes specific headers in signature calculation
             aws_signature_headers: Final = self._filter_headers_for_aws_signature(headers)
diff --git a/litellm/llms/bedrock/chat/converse_handler.py b/litellm/llms/bedrock/chat/converse_handler.py
index ca5f1298360..7d5f99ca893 100644
--- a/litellm/llms/bedrock/chat/converse_handler.py
+++ b/litellm/llms/bedrock/chat/converse_handler.py
@@ -1,4 +1,6 @@
 import json
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import Any, Final
 
 import httpx
@@ -24,6 +26,22 @@ from ..common_utils import BedrockError, _get_all_bedrock_regions
 from .invoke_handler import AWSEventStreamDecoder, MockResponseIterator, make_call
 
 
+def _sigv4_principal(credentials: Credentials | None) -> Mapping[str, str]:
+    if credentials is None:
+        return MappingProxyType({})
+    return MappingProxyType(
+        {
+            key: value
+            for key, value in (
+                ("aws_access_key_id", credentials.access_key),
+                ("aws_secret_access_key", credentials.secret_key),
+                ("aws_session_token", credentials.token),
+            )
+            if value is not None
+        }
+    )
+
+
 def make_sync_call(
     client: HTTPHandler | None,
     api_base: str,
@@ -95,7 +113,7 @@ class BedrockConverseLLM(BaseAWSLLM):
         stream,
         optional_params: dict,
         litellm_params: dict,
-        credentials: Credentials,
+        credentials: Credentials | None,
         logger_fn=None,
         headers={},
         client: AsyncHTTPHandler | None = None,
@@ -167,7 +185,7 @@ class BedrockConverseLLM(BaseAWSLLM):
         stream,
         optional_params: dict,
         litellm_params: dict,
-        credentials: Credentials,
+        credentials: Credentials | None,
         logger_fn=None,
         headers: dict = {},
         client: AsyncHTTPHandler | None = None,
@@ -331,7 +349,7 @@ class BedrockConverseLLM(BaseAWSLLM):
 
         litellm_params["aws_region_name"] = aws_region_name  # [DO NOT DELETE] important for async calls
 
-        credentials: Final[Credentials] = self.get_credentials(
+        credentials: Final[Credentials | None] = self.get_credentials(
             aws_access_key_id=aws_access_key_id,
             aws_secret_access_key=aws_secret_access_key,
             aws_session_token=aws_session_token,
@@ -368,19 +386,13 @@ class BedrockConverseLLM(BaseAWSLLM):
         # The Rust core owns the whole call for the subset it accepts. Ask
         # before transforming so whichever path runs emits pre_call once, and
         # hand down the credentials, region and endpoint this handler already
-        # resolved so both paths sign as the same principal.
+        # resolved so both paths sign as the same principal. Bearer-token auth
+        # resolves no SigV4 principal at all, and each path reads that token
+        # itself.
         rust_optional_params: Final = {  # mutable-ok: json.dumps in the bridge rejects a mappingproxy
             **optional_params,
-            **{  # mutable-ok: merged into its mutable parent above
-                key: value
-                for key, value in (
-                    ("aws_access_key_id", credentials.access_key),
-                    ("aws_secret_access_key", credentials.secret_key),
-                    ("aws_session_token", credentials.token),
-                    ("aws_region_name", aws_region_name),
-                )
-                if value is not None
-            },
+            **_sigv4_principal(credentials),
+            "aws_region_name": aws_region_name,
         }
         serves_via_rust: Final = rust_chat_completions_accepts(
             model=model,
diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py
index 7fefeaeaf04..5363c3c0366 100644
--- a/litellm/llms/bedrock/chat/converse_transformation.py
+++ b/litellm/llms/bedrock/chat/converse_transformation.py
@@ -87,6 +87,7 @@ from ..common_utils import (
     BedrockError,
     BedrockModelInfo,
     bedrock_converse_supports_parallel_tool_use_config,
+    bedrock_model_accepts_cache_points,
     get_anthropic_beta_from_headers,
     get_bedrock_tool_name,
     is_bedrock_application_inference_profile_arn,
@@ -1149,7 +1150,7 @@ class AmazonConverseConfig(BaseConfig):
         model: str | None = None,
     ) -> SystemContentBlock | ContentBlock | None:
         cache_control: Final = message_block.get("cache_control", None)
-        if cache_control is None:
+        if cache_control is None or not bedrock_model_accepts_cache_points(model):
             return None
 
         cache_point: Final = self._build_cache_point_block(cache_control, model)
@@ -1613,7 +1614,7 @@ class AmazonConverseConfig(BaseConfig):
 
         # Append cachePoint to tools if cache_control_injection_points has tool_config
         cache_injection_points: Final = additional_request_params.pop("cache_control_injection_points", None)
-        if cache_injection_points and len(bedrock_tools) > 0:
+        if cache_injection_points and len(bedrock_tools) > 0 and bedrock_model_accepts_cache_points(model):
             for point in cache_injection_points:
                 if point.get("location") == "tool_config":
                     cache_point = self._build_cache_point_block(point.get("control"), model)
diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py
index 30a77d57f24..66ee5f10679 100644
--- a/litellm/llms/bedrock/common_utils.py
+++ b/litellm/llms/bedrock/common_utils.py
@@ -816,6 +816,30 @@ def bedrock_converse_supports_parallel_tool_use_config(model: str) -> bool:
     )
 
 
+def bedrock_model_accepts_cache_points(model: str | None) -> bool:
+    """
+    Whether Converse ``cachePoint`` blocks may be sent to this model.
+
+    Bedrock rejects requests carrying cachePoint blocks for models without prompt
+    caching support ("You invoked an unsupported model or your request did not allow
+    prompt caching"), so a model whose cost-map entry does not declare
+    ``supports_prompt_caching`` must not receive them. A model absent from the map
+    (an application inference profile ARN, a model newer than the map) keeps emitting
+    so existing caching setups never silently degrade. ``litellm.utils.supports_prompt_caching``
+    is not reusable here: it returns False for unmapped models, the opposite polarity.
+    """
+    if model is None:
+        return True
+    entries: Final = tuple(
+        entry
+        for candidate in (model, get_bedrock_base_model(model))
+        if (entry := litellm.model_cost.get(candidate)) is not None
+    )
+    if not entries:
+        return True
+    return any(entry.get("supports_prompt_caching") is True for entry in entries)
+
+
 def is_claude_4_5_on_bedrock(model: str) -> bool:
     """
     Check if the model supports Bedrock prompt caching with an extended '1h' TTL
diff --git a/litellm/llms/bedrock/vector_stores/transformation.py b/litellm/llms/bedrock/vector_stores/transformation.py
index 2d72db0cdba..bad17a2181d 100644
--- a/litellm/llms/bedrock/vector_stores/transformation.py
+++ b/litellm/llms/bedrock/vector_stores/transformation.py
@@ -27,6 +27,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -196,6 +197,7 @@ class BedrockVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         if isinstance(query, list):
             query = " ".join(query)
diff --git a/litellm/llms/custom_httpx/aiohttp_transport.py b/litellm/llms/custom_httpx/aiohttp_transport.py
index b6586481fd3..73adf9c7455 100644
--- a/litellm/llms/custom_httpx/aiohttp_transport.py
+++ b/litellm/llms/custom_httpx/aiohttp_transport.py
@@ -3,6 +3,7 @@ import concurrent.futures
 import contextlib
 import os
 import ssl
+import sys
 import typing
 import urllib.request
 from collections.abc import Callable, Generator
@@ -75,10 +76,22 @@ except ImportError:
     pass
 
 
+def _current_task_is_cancelling() -> bool:
+    task: Final = asyncio.current_task()
+    if task is None or sys.version_info < (3, 11):
+        return True
+    return task.cancelling() > 0
+
+
 @contextlib.contextmanager
 def map_aiohttp_exceptions() -> Generator[None, None, None]:
     try:
         yield
+    except asyncio.CancelledError as exc:
+        # a closing connector cancels its shielded DNS task; that surfaces here without the request task being cancelled
+        if _current_task_is_cancelling():
+            raise
+        raise httpx.ConnectError("aiohttp transport cancelled the request internally") from exc
     except Exception as exc:
         mapped_exc: type[Exception] | None = None
 
diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py
index c0ef7456680..fb4d2b3d671 100644
--- a/litellm/llms/custom_httpx/llm_http_handler.py
+++ b/litellm/llms/custom_httpx/llm_http_handler.py
@@ -180,6 +180,7 @@ if TYPE_CHECKING:
         AnthropicMessagesStreamingResponse,
     )
     from litellm.llms.base_llm.passthrough.transformation import BasePassthroughConfig
+    from litellm.router import Router
     from litellm.types.llms.openai_evals import (
         CancelEvalResponse,
         CancelRunResponse,
@@ -2925,7 +2926,7 @@ class BaseLLMHTTPHandler:
         final_response: Final = await self._call_agentic_completion_hooks(
             response=initial_response,
             model=model,
-            messages=(input if isinstance(input, list) else [{"role": "user", "content": input}]),
+            messages=(input if isinstance(input, list) else [{"role": "user", "content": input}]),  # pyright: ignore[reportArgumentType]  # pre-existing mismatch surfaced by the Router import; the hook accepts response input items at runtime
             anthropic_messages_provider_config=responses_api_provider_config,
             anthropic_messages_optional_request_params=response_api_optional_request_params,
             logging_obj=logging_obj,
@@ -5417,7 +5418,7 @@ class BaseLLMHTTPHandler:
         try:
             response: ResponsesAPIResponse | BaseResponsesAPIStreamingIterator = await litellm.aresponses(
                 model=patch.model or model,
-                input=patch.messages,
+                input=patch.messages,  # pyright: ignore[reportArgumentType]  # pre-existing mismatch surfaced by the Router import; patch messages are valid response input at runtime
                 **optional_params,
                 **kwargs_for_followup,
             )
@@ -9691,6 +9692,7 @@ class BaseLLMHTTPHandler:
         timeout: float | httpx.Timeout | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         _is_async: bool = False,
+        router: "Router | None" = None,
     ) -> VectorStoreSearchResponse:
         if isinstance(vector_store_provider_config, BaseDirectVectorStoreConfig):
             self._pre_call_direct_vector_store_search(
@@ -9741,6 +9743,7 @@ class BaseLLMHTTPHandler:
                 litellm_logging_obj=logging_obj,
                 litellm_params=dict(litellm_params),
                 extra_body=extra_body,
+                router=router,
                 embedding_executor=embedding_executor,
             )
         else:
@@ -9755,6 +9758,7 @@ class BaseLLMHTTPHandler:
                 litellm_logging_obj=logging_obj,
                 litellm_params=dict(litellm_params),
                 extra_body=extra_body,
+                router=router,
             )
         all_optional_params: Final[dict[str, object]] = dict(litellm_params)
         all_optional_params.update(vector_store_search_optional_params or {})
@@ -9807,6 +9811,7 @@ class BaseLLMHTTPHandler:
         timeout: float | httpx.Timeout | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         _is_async: bool = False,
+        router: "Router | None" = None,
     ) -> VectorStoreSearchResponse | Coroutine[object, object, VectorStoreSearchResponse]:
         if _is_async:
             return self.async_vector_store_search_handler(
@@ -9822,6 +9827,7 @@ class BaseLLMHTTPHandler:
                 extra_body=extra_body,
                 timeout=timeout,
                 client=client,
+                router=router,
             )
 
         if isinstance(vector_store_provider_config, BaseDirectVectorStoreConfig):
@@ -9870,6 +9876,7 @@ class BaseLLMHTTPHandler:
                 litellm_logging_obj=logging_obj,
                 litellm_params=dict(litellm_params),
                 extra_body=extra_body,
+                router=router,
                 embedding_executor=embedding_executor,
             )
         else:
@@ -9884,6 +9891,7 @@ class BaseLLMHTTPHandler:
                 litellm_logging_obj=logging_obj,
                 litellm_params=dict(litellm_params),
                 extra_body=extra_body,
+                router=router,
             )
 
         all_optional_params: Final[dict[str, object]] = dict(litellm_params)
diff --git a/litellm/llms/gemini/vector_stores/transformation.py b/litellm/llms/gemini/vector_stores/transformation.py
index f6525a449b6..82586b1f638 100644
--- a/litellm/llms/gemini/vector_stores/transformation.py
+++ b/litellm/llms/gemini/vector_stores/transformation.py
@@ -33,6 +33,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -168,6 +169,7 @@ class GeminiVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: Mapping[str, object] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """
         Transform search request to Gemini's generateContent format.
diff --git a/litellm/llms/langflow/a2a.py b/litellm/llms/langflow/a2a.py
index cae750d586e..060dc0a4d05 100644
--- a/litellm/llms/langflow/a2a.py
+++ b/litellm/llms/langflow/a2a.py
@@ -1,28 +1,9 @@
-import hashlib
 from typing import Any, Final
 
-
-def get_session_id_from_a2a_params(params: dict[str, Any]) -> str | None:
-    message: Final = params.get("message", {})
-    if isinstance(message, dict):
-        return message.get("contextId")
-    return getattr(message, "contextId", None)
-
-
-def scope_session_to_principal(session_id: str, principal: str | None) -> str:
-    """
-    Bind a client-supplied A2A contextId to the authenticated principal.
-
-    Without this, two distinct keys authorized for the same LangFlow agent could
-    set the same contextId and read/append to each other's LangFlow memory. The
-    principal is hashed (it is already a hashed token) so the raw value is never
-    sent to the LangFlow backend, while the original contextId is kept as a
-    suffix for operator-side correlation.
-    """
-    if not principal:
-        return session_id
-    principal_prefix: Final = hashlib.sha256(principal.encode("utf-8")).hexdigest()[:16]
-    return f"{principal_prefix}-{session_id}"
+from litellm.a2a_protocol.utils import (
+    get_session_id_from_a2a_params,
+    scope_session_to_principal,
+)
 
 
 def merge_a2a_session_into_litellm_params(
diff --git a/litellm/llms/milvus/vector_stores/transformation.py b/litellm/llms/milvus/vector_stores/transformation.py
index b0291c692d5..4f3c366d8c1 100644
--- a/litellm/llms/milvus/vector_stores/transformation.py
+++ b/litellm/llms/milvus/vector_stores/transformation.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final
 
@@ -22,6 +24,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -126,10 +129,11 @@ class MilvusVectorStoreConfig(BaseQueryEmbeddingVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: Router | None = None,
         embedding_executor: VectorStoreEmbeddingExecutor | None = None,
     ) -> tuple[str, dict[str, object]]:
         query_text: Final = self.query_text(query)
-        query_vector: Final = self.embed_query(query_text, litellm_params, embedding_executor)
+        query_vector: Final = self.embed_query(query_text, litellm_params, embedding_executor, router)
         return self._search_request(
             vector_store_id,
             query_text,
@@ -149,10 +153,11 @@ class MilvusVectorStoreConfig(BaseQueryEmbeddingVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: Router | None = None,
         embedding_executor: VectorStoreEmbeddingExecutor | None = None,
     ) -> tuple[str, dict[str, object]]:
         query_text: Final = self.query_text(query)
-        query_vector: Final = await self.aembed_query(query_text, litellm_params, embedding_executor)
+        query_vector: Final = await self.aembed_query(query_text, litellm_params, embedding_executor, router)
         return self._search_request(
             vector_store_id,
             query_text,
diff --git a/litellm/llms/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py
index ed628f55350..96a5ed663fc 100644
--- a/litellm/llms/openai/chat/guardrail_translation/handler.py
+++ b/litellm/llms/openai/chat/guardrail_translation/handler.py
@@ -14,9 +14,14 @@ Pattern Overview:
 This pattern can be replicated for other message formats (e.g., Anthropic).
 """
 
+import json
+import time
+import uuid
 from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Final, Union, cast
 
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
 import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm.llms.base_llm.guardrail_translation.base_translation import (
@@ -24,6 +29,7 @@ from litellm.llms.base_llm.guardrail_translation.base_translation import (
     StreamTransformSink,
 )
 from litellm.llms.base_llm.guardrail_translation.utils import (
+    blocked_chat_stream_usage,
     effective_scan_only_tool_results_for_guardrail,
     effective_skip_system_message_for_guardrail,
     effective_skip_tool_message_for_guardrail,
@@ -32,6 +38,7 @@ from litellm.llms.base_llm.guardrail_translation.utils import (
     openai_tool_name,
     role_out_of_guardrail_scope,
     scoped_structured_message_indices,
+    stream_item_field,
 )
 from litellm.main import stream_chunk_builder
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolParam
@@ -49,7 +56,10 @@ from litellm.types.utils import (
 if TYPE_CHECKING:
     from fastapi import HTTPException
 
-    from litellm.integrations.custom_guardrail import CustomGuardrail
+    from litellm.integrations.custom_guardrail import (
+        CustomGuardrail,
+        ModifyResponseException,
+    )
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
     from litellm.proxy._types import UserAPIKeyAuth
 
@@ -1005,3 +1015,129 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
                                 else:
                                     # Subsequent chunks - clear the text
                                     content_item["text"] = ""
+
+    def _check_streaming_has_ended(self, responses_so_far: Sequence[object]) -> bool:
+        """
+        True once any relayed chunk carries a non-null ``finish_reason``.
+
+        The unified guardrail's ``end_of_stream_only`` streaming path probes
+        this via ``hasattr`` to withhold the terminal chunks until
+        end-of-stream moderation runs, so a block can replace the finish
+        instead of trailing after a ``finish_reason`` the client already saw.
+        """
+        return any(
+            stream_item_field(choice, "finish_reason") is not None
+            for item in responses_so_far
+            for choice in _stream_chunk_choices(item)
+        )
+
+    def build_block_sse_chunks(
+        self,
+        exc: "ModifyResponseException",
+        stream_started: bool = False,
+        responses_so_far: Sequence[object] | None = None,
+    ) -> Sequence[bytes]:
+        """
+        Build OpenAI chat-completions SSE chunks that deliver the guardrail
+        block message and terminate the stream cleanly, mirroring the
+        non-streaming block response: ``finish_reason`` ``content_filter`` plus
+        the real usage the upstream call consumed.
+
+        - ``stream_started`` False (buffered / pre-stream): nothing has been
+          sent, so open a standalone completion with a ``role`` delta.
+        - ``stream_started`` True (sampling / mid-stream): chunks already
+          reached the client, so continue the in-progress completion (reuse its
+          id/created/model, content-only delta).
+
+        The proxy's data generator appends ``data: [DONE]`` itself.
+        """
+        chunk_id, created, model = _blocked_stream_identity(exc, responses_so_far or ())
+        prompt_tokens, completion_tokens = blocked_chat_stream_usage(exc.original_response)
+        continuation_delta: Final[_BlockedChunkDelta] = {"content": exc.message}
+        standalone_delta: Final[_BlockedChunkDelta] = {"role": "assistant", "content": exc.message}
+        message_chunk: Final[_BlockedChunk] = {
+            "id": chunk_id,
+            "object": "chat.completion.chunk",
+            "created": created,
+            "model": model,
+            "choices": (
+                {
+                    "index": 0,
+                    "delta": continuation_delta if stream_started else standalone_delta,
+                    "finish_reason": None,
+                },
+            ),
+        }
+        final_chunk: Final[_BlockedChunk] = {
+            "id": chunk_id,
+            "object": "chat.completion.chunk",
+            "created": created,
+            "model": model,
+            "choices": ({"index": 0, "delta": {}, "finish_reason": "content_filter"},),
+            "usage": {
+                "prompt_tokens": prompt_tokens,
+                "completion_tokens": completion_tokens,
+                "total_tokens": prompt_tokens + completion_tokens,
+            },
+        }
+        return _chat_sse_chunk(message_chunk), _chat_sse_chunk(final_chunk)
+
+
+class _BlockedChunkDelta(TypedDict, total=False):
+    role: ReadOnly[str]
+    content: ReadOnly[str]
+
+
+class _BlockedChunkChoice(TypedDict):
+    index: ReadOnly[int]
+    delta: ReadOnly[_BlockedChunkDelta]
+    finish_reason: ReadOnly[str | None]
+
+
+class _BlockedChunkUsage(TypedDict):
+    prompt_tokens: ReadOnly[int]
+    completion_tokens: ReadOnly[int]
+    total_tokens: ReadOnly[int]
+
+
+class _BlockedChunk(TypedDict):
+    id: ReadOnly[str]
+    object: ReadOnly[str]
+    created: ReadOnly[int]
+    model: ReadOnly[str]
+    choices: ReadOnly[tuple[_BlockedChunkChoice, ...]]
+    usage: NotRequired[ReadOnly[_BlockedChunkUsage]]
+
+
+def _chat_sse_chunk(payload: _BlockedChunk) -> bytes:
+    return f"data: {json.dumps(payload)}\n\n".encode()
+
+
+def _stream_chunk_choices(item: object) -> Sequence[object]:
+    choices: Final = stream_item_field(item, "choices")
+    if isinstance(choices, Sequence) and not isinstance(choices, (str, bytes)):
+        return choices
+    return ()
+
+
+def _blocked_stream_identity(
+    exc: "ModifyResponseException", responses_so_far: Sequence[object]
+) -> tuple[str, int, str]:
+    identified: Final = next(
+        (
+            (chunk_id, item)
+            for item in responses_so_far
+            if isinstance(chunk_id := stream_item_field(item, "id"), str) and chunk_id
+        ),
+        None,
+    )
+    if identified is None:
+        return f"chatcmpl-{uuid.uuid4()}", int(time.time()), exc.model
+    chunk_id, source = identified
+    created: Final = stream_item_field(source, "created")
+    model: Final = stream_item_field(source, "model")
+    return (
+        chunk_id,
+        created if isinstance(created, int) else int(time.time()),
+        model if isinstance(model, str) and model else exc.model,
+    )
diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index ec70fe0d795..1530c154e93 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -28,12 +28,16 @@ Output: response.output is List[GenericResponseOutputItem] where each has:
     - text: str
 """
 
-from collections.abc import Sequence
+import time
+import uuid
+from collections.abc import Mapping, Sequence
+from dataclasses import dataclass
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Union, cast
 
 from openai.types.responses.response_function_tool_call import ResponseFunctionToolCall
 from openai.types.responses.tool_param import FunctionToolParam
-from pydantic import BaseModel
+from pydantic import BaseModel, TypeAdapter
 from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
@@ -41,17 +45,33 @@ from litellm.completion_extras.litellm_responses_transformation.transformation i
     OpenAiResponsesToChatCompletionStreamIterator,
 )
 from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
+from litellm.llms.base_llm.guardrail_translation.utils import (
+    blocked_responses_stream_usage,
+    stream_item_field,
+)
 from litellm.responses.litellm_completion_transformation.transformation import (
     LiteLLMCompletionResponsesConfig,
 )
 from litellm.types.llms.openai import (
     AllMessageValues,
+    BaseLiteLLMOpenAIResponseObject,
     ChatCompletionToolCallChunk,
     ChatCompletionToolParam,
+    ContentPartAddedEvent,
+    ContentPartDoneEvent,
+    ContentPartDonePartOutputText,
     ErrorEvent,
     ErrorEventError,
     OpenAIMcpServerTool,
+    OutputItemAddedEvent,
+    OutputItemDoneEvent,
+    OutputTextDeltaEvent,
+    OutputTextDoneEvent,
+    ResponseAPIUsage,
+    ResponseCompletedEvent,
+    ResponsesAPIResponse,
     ResponsesAPIStreamEvents,
+    ResponsesAPIStreamingResponse,
 )
 from litellm.types.responses.main import (
     GenericResponseOutputItem,
@@ -63,11 +83,13 @@ from litellm.types.utils import GenericGuardrailAPIInputs
 if TYPE_CHECKING:
     from fastapi import HTTPException
 
-    from litellm.integrations.custom_guardrail import CustomGuardrail
+    from litellm.integrations.custom_guardrail import (
+        CustomGuardrail,
+        ModifyResponseException,
+    )
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
     from litellm.proxy._types import UserAPIKeyAuth
     from litellm.types.llms.openai import ResponseInputParam
-    from litellm.types.utils import ResponsesAPIResponse
 
 
 class ResponseOutputEnvelope(TypedDict, total=False):
@@ -865,3 +887,331 @@ class OpenAIResponsesHandler(BaseTranslation):
                         content[content_idx]["text"] = guardrail_response
                     elif hasattr(content[content_idx], "text"):
                         content[content_idx].text = guardrail_response
+
+    def build_block_sse_chunks(
+        self,
+        exc: "ModifyResponseException",
+        stream_started: bool = False,
+        responses_so_far: Sequence[object] | None = None,
+    ) -> Sequence[bytes]:
+        """
+        Build Responses API SSE events that deliver the guardrail block message
+        and terminate the stream cleanly, mirroring the non-streaming block
+        response: a completed response whose only output is the violation text,
+        with the real usage the upstream call consumed.
+
+        - ``stream_started`` False (buffered / pre-stream): nothing has been
+          sent, so emit the full synthetic sequence (``response.created``
+          through ``response.completed``).
+        - ``stream_started`` True (sampling / mid-stream): events already
+          reached the client, so continue the in-progress response: close the
+          output item still open on the wire, deliver the block message as a
+          new output item under the same response id, and close with a
+          ``response.completed`` carrying only the replacement item.
+
+        The proxy's data generator appends ``data: [DONE]`` itself.
+        """
+        events: Final = (
+            self._block_continuation_events(exc, responses_so_far or ())
+            if stream_started
+            else self._standalone_block_events(exc)
+        )
+        return tuple(
+            f"data: {event.model_dump_json(exclude_none=True, exclude_unset=True, serialize_as_any=True)}\n\n".encode()
+            for event in events
+        )
+
+    @staticmethod
+    def _standalone_block_events(exc: "ModifyResponseException") -> Sequence[ResponsesAPIStreamingResponse]:
+        from litellm.responses.streaming_iterator import build_synthetic_response_events
+
+        return build_synthetic_response_events(
+            transformed=_blocked_response(exc, response_id=f"resp_{uuid.uuid4()}", model=exc.model),
+            logging_obj=None,
+            chunk_size=max(len(exc.message), 1),
+        )
+
+    @staticmethod
+    def _block_continuation_events(
+        exc: "ModifyResponseException", responses_so_far: Sequence[object]
+    ) -> Sequence[ResponsesAPIStreamingResponse]:
+        response_id, model, output_index = _continuation_identity(exc, responses_so_far)
+        item: Final = _blocked_output_item(exc)
+        item_id: Final = item.id
+        part: Final[_BlockedContentPart] = {"type": "output_text", "text": exc.message, "annotations": ()}
+        done_part: Final[_BlockedDoneContentPart] = {
+            "type": "output_text",
+            "text": exc.message,
+            "annotations": (),
+            "logprobs": None,
+        }
+        return (
+            *_open_item_closing_events(responses_so_far),
+            OutputItemAddedEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED,
+                output_index=output_index,
+                item=item,
+            ),
+            ContentPartAddedEvent(
+                type=ResponsesAPIStreamEvents.CONTENT_PART_ADDED,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                part=BaseLiteLLMOpenAIResponseObject.model_validate(part),
+            ),
+            OutputTextDeltaEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                delta=exc.message,
+            ),
+            OutputTextDoneEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                text=exc.message,
+            ),
+            ContentPartDoneEvent(
+                type=ResponsesAPIStreamEvents.CONTENT_PART_DONE,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                part=ContentPartDonePartOutputText.model_validate(done_part),
+            ),
+            OutputItemDoneEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE,
+                output_index=output_index,
+                item=item,
+            ),
+            ResponseCompletedEvent(
+                type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
+                response=_blocked_response(exc, response_id=response_id, model=model, output_item=item),
+            ),
+        )
+
+
+class _BlockedContentPart(TypedDict):
+    type: ReadOnly[str]
+    text: ReadOnly[str]
+    annotations: ReadOnly[tuple[object, ...]]
+
+
+class _BlockedDoneContentPart(TypedDict):
+    type: ReadOnly[str]
+    text: ReadOnly[str]
+    annotations: ReadOnly[tuple[object, ...]]
+    logprobs: ReadOnly[None]
+
+
+class _BlockedItemPayload(TypedDict):
+    type: ReadOnly[str]
+    id: ReadOnly[str]
+    status: ReadOnly[str]
+    role: ReadOnly[str]
+    content: ReadOnly[tuple[_BlockedContentPart, ...]]
+
+
+class _BlockedResponsePayload(TypedDict):
+    id: ReadOnly[str]
+    object: ReadOnly[str]
+    created_at: ReadOnly[int]
+    model: ReadOnly[str]
+    output: ReadOnly[tuple[GenericResponseOutputItem, ...]]
+    status: ReadOnly[str]
+    usage: ReadOnly[ResponseAPIUsage]
+
+
+def _blocked_output_item(exc: "ModifyResponseException") -> GenericResponseOutputItem:
+    payload: Final[_BlockedItemPayload] = {
+        "type": "message",
+        "id": f"msg_{uuid.uuid4()}",
+        "status": "completed",
+        "role": "assistant",
+        "content": ({"type": "output_text", "text": exc.message, "annotations": ()},),
+    }
+    return GenericResponseOutputItem.model_validate(payload)
+
+
+def _blocked_response(
+    exc: "ModifyResponseException",
+    response_id: str,
+    model: str,
+    output_item: GenericResponseOutputItem | None = None,
+) -> ResponsesAPIResponse:
+    payload: Final[_BlockedResponsePayload] = {
+        "id": response_id,
+        "object": "response",
+        "created_at": int(time.time()),
+        "model": model,
+        "output": (output_item if output_item is not None else _blocked_output_item(exc),),
+        "status": "completed",
+        "usage": blocked_responses_stream_usage(exc.original_response),
+    }
+    return ResponsesAPIResponse.model_validate(payload)
+
+
+def _continuation_identity(exc: "ModifyResponseException", responses_so_far: Sequence[object]) -> tuple[str, str, int]:
+    responses: Final = tuple(
+        response for item in responses_so_far if (response := stream_item_field(item, "response")) is not None
+    )
+    response_id: Final = next(
+        (rid for response in responses if isinstance(rid := stream_item_field(response, "id"), str) and rid),
+        f"resp_{uuid.uuid4()}",
+    )
+    model: Final = next(
+        (m for response in responses if isinstance(m := stream_item_field(response, "model"), str) and m),
+        exc.model,
+    )
+    indices: Final = tuple(
+        index for item in responses_so_far if isinstance(index := stream_item_field(item, "output_index"), int)
+    )
+    return response_id, model, max(indices) + 1 if indices else 0
+
+
+@dataclass(frozen=True, slots=True)
+class _OpenItemState:
+    item_id: str
+    item_type: str
+    role: str
+    output_index: int
+    content_index: int
+    text: str
+    part_open: bool
+    payload: object
+
+
+def _open_item_state(responses_so_far: Sequence[object]) -> _OpenItemState | None:
+    typed: Final = tuple((stream_item_field(event, "type"), event) for event in responses_so_far)
+    added: Final = tuple(
+        (added_index, stream_item_field(event, "item"))
+        for event_type, event in typed
+        if event_type == "response.output_item.added"
+        and isinstance(added_index := stream_item_field(event, "output_index"), int)
+    )
+    done_indices: Final = frozenset(
+        done_index
+        for event_type, event in typed
+        if event_type == "response.output_item.done"
+        and isinstance(done_index := stream_item_field(event, "output_index"), int)
+    )
+    open_added: Final = tuple((index, payload) for index, payload in added if index not in done_indices)
+    if not open_added:
+        return None
+    output_index, item_payload = open_added[-1]
+    if item_payload is None:
+        return None
+    item_id: Final = stream_item_field(item_payload, "id")
+    if not isinstance(item_id, str) or not item_id:
+        return None
+    raw_type: Final = stream_item_field(item_payload, "type")
+    raw_role: Final = stream_item_field(item_payload, "role")
+    part_added: Final = tuple(
+        part_index
+        for event_type, event in typed
+        if event_type == "response.content_part.added"
+        and stream_item_field(event, "item_id") == item_id
+        and isinstance(part_index := stream_item_field(event, "content_index"), int)
+    )
+    part_done: Final = frozenset(
+        part_done_index
+        for event_type, event in typed
+        if event_type == "response.content_part.done"
+        and stream_item_field(event, "item_id") == item_id
+        and isinstance(part_done_index := stream_item_field(event, "content_index"), int)
+    )
+    open_parts: Final = tuple(index for index in part_added if index not in part_done)
+    text: Final = "".join(
+        delta
+        for event_type, event in typed
+        if event_type == "response.output_text.delta"
+        and stream_item_field(event, "item_id") == item_id
+        and isinstance(delta := stream_item_field(event, "delta"), str)
+    )
+    return _OpenItemState(
+        item_id=item_id,
+        item_type=raw_type if isinstance(raw_type, str) and raw_type else "message",
+        role=raw_role if isinstance(raw_role, str) and raw_role else "assistant",
+        output_index=output_index,
+        content_index=open_parts[-1] if open_parts else 0,
+        text=text,
+        part_open=bool(open_parts),
+        payload=item_payload,
+    )
+
+
+_item_fields_adapter: Final = TypeAdapter(Mapping[str, object])
+_no_item_fields: Final[Mapping[str, object]] = MappingProxyType({})
+
+
+def _incomplete_item_fields(payload: object) -> Mapping[str, object]:
+    raw: Final = payload.model_dump() if isinstance(payload, BaseModel) else payload
+    if not isinstance(raw, dict):
+        return _no_item_fields
+    return _item_fields_adapter.validate_python(raw)
+
+
+def _open_item_closing_events(responses_so_far: Sequence[object]) -> Sequence[ResponsesAPIStreamingResponse]:
+    """Close the output item still in progress on the relayed stream before the
+    block item is appended: strict Responses clients reject a
+    ``response.completed`` that arrives while an earlier ``output_item.added``
+    was never closed. A message item closes ``completed`` with exactly the text
+    the client has received so far; any other item type (a function call the
+    guardrail rejected, for instance) closes ``incomplete`` so the synthetic
+    done event can never authorize acting on it."""
+    open_item: Final = _open_item_state(responses_so_far)
+    if open_item is None:
+        return ()
+    if open_item.item_type != "message":
+        return (
+            OutputItemDoneEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE,
+                output_index=open_item.output_index,
+                item=BaseLiteLLMOpenAIResponseObject.model_validate(
+                    MappingProxyType({**_incomplete_item_fields(open_item.payload), "status": "incomplete"})
+                ),
+            ),
+        )
+    partial_part: Final[_BlockedContentPart] = {
+        "type": "output_text",
+        "text": open_item.text,
+        "annotations": (),
+    }
+    closed_payload: Final[_BlockedItemPayload] = {
+        "type": open_item.item_type,
+        "id": open_item.item_id,
+        "status": "completed",
+        "role": open_item.role,
+        "content": (partial_part,),
+    }
+    item_done: Final = OutputItemDoneEvent(
+        type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE,
+        output_index=open_item.output_index,
+        item=GenericResponseOutputItem.model_validate(closed_payload),
+    )
+    if not open_item.part_open:
+        return (item_done,)
+    partial_done_part: Final[_BlockedDoneContentPart] = {
+        "type": "output_text",
+        "text": open_item.text,
+        "annotations": (),
+        "logprobs": None,
+    }
+    return (
+        OutputTextDoneEvent(
+            type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE,
+            item_id=open_item.item_id,
+            output_index=open_item.output_index,
+            content_index=open_item.content_index,
+            text=open_item.text,
+        ),
+        ContentPartDoneEvent(
+            type=ResponsesAPIStreamEvents.CONTENT_PART_DONE,
+            item_id=open_item.item_id,
+            output_index=open_item.output_index,
+            content_index=open_item.content_index,
+            part=ContentPartDonePartOutputText.model_validate(partial_done_part),
+        ),
+        item_done,
+    )
diff --git a/litellm/llms/openai/vector_stores/transformation.py b/litellm/llms/openai/vector_stores/transformation.py
index f6c093f2e2a..4e925494039 100644
--- a/litellm/llms/openai/vector_stores/transformation.py
+++ b/litellm/llms/openai/vector_stores/transformation.py
@@ -21,6 +21,7 @@ from litellm.utils import add_openai_metadata
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -99,6 +100,7 @@ class OpenAIVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
         url: Final = f"{api_base}/{encoded_vector_store_id}/search"
diff --git a/litellm/llms/parallel_ai/search/cost_calculator.py b/litellm/llms/parallel_ai/search/cost_calculator.py
new file mode 100644
index 00000000000..809cd280cc8
--- /dev/null
+++ b/litellm/llms/parallel_ai/search/cost_calculator.py
@@ -0,0 +1,90 @@
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
+from typing import Final
+
+from pydantic import TypeAdapter, ValidationError
+
+from litellm.utils import get_model_info
+
+PARALLEL_AI_DEFAULT_RESULTS: Final = 10
+PARALLEL_AI_ADDITIONAL_RESULT_COST: Final = 0.001
+PARALLEL_AI_USAGE_PARAM: Final = "_parallel_ai_usage"
+PARALLEL_AI_STANDARD_SEARCH_MODEL: Final = "parallel_ai/search"
+PARALLEL_AI_FAST_SEARCH_MODEL: Final = "parallel_ai/search-fast"
+PARALLEL_AI_TURBO_SEARCH_MODEL: Final = "parallel_ai/search-turbo"
+PARALLEL_AI_PRICING_MODEL_BY_MODE: Final[Mapping[str, str]] = MappingProxyType(
+    {
+        "fast": PARALLEL_AI_FAST_SEARCH_MODEL,
+        "turbo": PARALLEL_AI_TURBO_SEARCH_MODEL,
+    }
+)
+ADVANCED_SETTINGS_ADAPTER: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object])
+
+
+def _non_negative_int(value: object) -> int | None:
+    if isinstance(value, bool) or not isinstance(value, int) or value < 0:
+        return None
+    return value
+
+
+def _usage_count(usage: Sequence[Mapping[str, object]], sku: str) -> int | None:
+    counts: Final = tuple(
+        count
+        for item in usage
+        if item.get("name") == sku
+        if (count := _non_negative_int(item.get("count"))) is not None
+    )
+    return sum(counts) if counts else None
+
+
+def _effective_mode(optional_params: Mapping[str, object]) -> str:
+    mode: Final = optional_params.get("mode")
+    if isinstance(mode, str):
+        return mode
+
+    processor: Final = optional_params.get("processor")
+    if processor == "pro":
+        return "advanced"
+    return "basic"
+
+
+def _effective_max_results(optional_params: Mapping[str, object]) -> int:
+    try:
+        advanced_settings: Final = ADVANCED_SETTINGS_ADAPTER.validate_python(optional_params.get("advanced_settings"))
+        advanced_max_results: Final = _non_negative_int(advanced_settings.get("max_results"))
+        if advanced_max_results is not None:
+            return advanced_max_results
+    except ValidationError:
+        pass
+
+    max_results: Final = _non_negative_int(optional_params.get("max_results"))
+    return max_results if max_results is not None else PARALLEL_AI_DEFAULT_RESULTS
+
+
+def _request_cost(mode: str) -> float:
+    pricing_model: Final = PARALLEL_AI_PRICING_MODEL_BY_MODE.get(mode, PARALLEL_AI_STANDARD_SEARCH_MODEL)
+    model_info: Final = get_model_info(model=pricing_model, custom_llm_provider="parallel_ai")
+    return float(model_info.get("input_cost_per_query") or 0.0)
+
+
+def _additional_results(
+    optional_params: Mapping[str, object],
+    usage: Sequence[Mapping[str, object]] | None,
+) -> int:
+    usage_count: Final = _usage_count(usage, "sku_search_additional_results") if usage is not None else None
+    if usage_count is not None:
+        return usage_count
+    if usage is not None:
+        return 0
+    return max(_effective_max_results(optional_params) - PARALLEL_AI_DEFAULT_RESULTS, 0)
+
+
+def parallel_ai_search_cost(
+    optional_params: Mapping[str, object],
+    usage: Sequence[Mapping[str, object]] | None,
+) -> float:
+    request_cost: Final = _request_cost(_effective_mode(optional_params))
+    request_count_from_usage: Final = _usage_count(usage, "sku_search") if usage is not None else None
+    request_count: Final = request_count_from_usage if request_count_from_usage is not None else 1
+    additional_results: Final = _additional_results(optional_params, usage)
+    return request_count * request_cost + additional_results * PARALLEL_AI_ADDITIONAL_RESULT_COST
diff --git a/litellm/llms/parallel_ai/search/transformation.py b/litellm/llms/parallel_ai/search/transformation.py
index ea21d1153fe..bde7b7b86db 100644
--- a/litellm/llms/parallel_ai/search/transformation.py
+++ b/litellm/llms/parallel_ai/search/transformation.py
@@ -4,9 +4,13 @@ Calls Parallel AI's /v1/search endpoint to search the web.
 Parallel AI API Reference: https://docs.parallel.ai/api-reference/search/search
 """
 
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
 from typing import Final, TypedDict
 
 import httpx
+from pydantic import BaseModel, ConfigDict
+from typing_extensions import ReadOnly
 
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.base_llm.search.transformation import (
@@ -14,9 +18,29 @@ from litellm.llms.base_llm.search.transformation import (
     SearchResponse,
     SearchResult,
 )
+from litellm.llms.parallel_ai.search.cost_calculator import PARALLEL_AI_USAGE_PARAM
 from litellm.secret_managers.main import get_secret_str
 
 
+class _ParallelAIV1SearchResult(BaseModel):
+    model_config = ConfigDict(extra="ignore")
+
+    url: str | None = None
+    title: str | None = None
+    publish_date: str | None = None
+    excerpts: Sequence[str] | None = None
+
+
+class _ParallelAIV1SearchResponse(BaseModel):
+    model_config = ConfigDict(extra="ignore")
+
+    search_id: str | None = None
+    session_id: str | None = None
+    results: Sequence[_ParallelAIV1SearchResult] = ()
+    usage: Sequence[Mapping[str, object]] | None = None
+    warnings: Sequence[Mapping[str, object]] | None = None
+
+
 class _ParallelAISourcePolicy(TypedDict, total=False):
     include_domains: list[str]
     exclude_domains: list[str]
@@ -27,10 +51,16 @@ class _ParallelAIExcerptSettings(TypedDict, total=False):
     max_chars_per_result: int
 
 
+class _ParallelAIFetchPolicy(TypedDict, total=False):
+    max_age_seconds: ReadOnly[int]
+    timeout_seconds: ReadOnly[float]
+    disable_cache_fallback: ReadOnly[bool]
+
+
 class _ParallelAIAdvancedSettings(TypedDict, total=False):
     source_policy: _ParallelAISourcePolicy
     excerpt_settings: _ParallelAIExcerptSettings
-    fetch_policy: dict
+    fetch_policy: _ParallelAIFetchPolicy
     location: str
     max_results: int
 
@@ -43,14 +73,14 @@ class ParallelAISearchRequest(TypedDict, total=False):
 
     search_queries: list[str]  # Required - at least one keyword search query
     objective: str  # Optional - natural-language description of search goal
-    mode: str  # Optional - 'turbo', 'basic', or 'advanced' (default 'advanced')
+    mode: str  # Optional - 'turbo', 'fast', 'basic', or 'advanced' (default 'advanced')
     max_chars_total: int  # Optional - upper bound on total excerpt characters
     session_id: str  # Optional - tracks calls across search/extract requests
     client_model: str  # Optional - model consuming the results
     advanced_settings: _ParallelAIAdvancedSettings
 
 
-LEGACY_PROCESSOR_TO_MODE: Final = {"base": "basic", "pro": "advanced"}
+LEGACY_PROCESSOR_TO_MODE: Final = MappingProxyType({"base": "basic", "pro": "advanced"})
 
 
 class ParallelAISearchConfig(BaseSearchConfig):
@@ -67,16 +97,16 @@ class ParallelAISearchConfig(BaseSearchConfig):
         api_base: str | None = None,
         **kwargs,
     ) -> dict:
-        api_key = self.resolve_server_api_key(
+        resolved_api_key: Final = self.resolve_server_api_key(
             caller_api_key=api_key,
             caller_api_base=api_base,
             key_env_vars=("PARALLEL_AI_API_KEY", "PARALLEL_API_KEY"),
             base_env_var="PARALLEL_AI_API_BASE",
             default_api_base=self.PARALLEL_AI_API_BASE,
         )
-        if not api_key:
+        if not resolved_api_key:
             raise ValueError("PARALLEL_API_KEY is not set. Set `PARALLEL_API_KEY` environment variable.")
-        headers["x-api-key"] = api_key
+        headers["x-api-key"] = resolved_api_key
         headers["Content-Type"] = "application/json"
         return headers
 
@@ -87,13 +117,12 @@ class ParallelAISearchConfig(BaseSearchConfig):
         data: dict | list[dict] | None = None,
         **kwargs,
     ) -> str:
-        api_base = api_base or get_secret_str("PARALLEL_AI_API_BASE") or self.PARALLEL_AI_API_BASE
+        resolved_api_base: Final = api_base or get_secret_str("PARALLEL_AI_API_BASE") or self.PARALLEL_AI_API_BASE
 
-        api_base = api_base.rstrip("/")
-        if not api_base.endswith("/v1/search"):
-            api_base = f"{api_base.removesuffix('/v1')}/v1/search"
-
-        return api_base
+        trimmed: Final = resolved_api_base.rstrip("/")
+        if trimmed.endswith("/v1/search"):
+            return trimmed
+        return f"{trimmed.removesuffix('/v1')}/v1/search"
 
     def transform_search_request(
         self,
@@ -109,14 +138,17 @@ class ParallelAISearchConfig(BaseSearchConfig):
                 - If string: maps to `search_queries` (single item) and `objective`
                 - If list: maps to `search_queries` (keyword queries)
             optional_params: Optional parameters for the request
-                - mode: Search mode ('turbo', 'basic', 'advanced'); defaults to 'basic'
+                - mode: Search mode ('turbo', 'fast', 'basic', 'advanced'); defaults to 'basic'
                 - processor: Legacy v1beta param; 'base' maps to mode 'basic', 'pro' to 'advanced'
                 - max_results: Maximum number of search results -> `advanced_settings.max_results`
-                - search_domain_filter: Domains to include -> `advanced_settings.source_policy.include_domains`
+                - search_domain_filter / include_domains: Domains to include -> `advanced_settings.source_policy.include_domains`
                 - exclude_domains: Domains to exclude -> `advanced_settings.source_policy.exclude_domains`
-                - country: ISO 3166-1 alpha-2 code -> `advanced_settings.location`
+                - after_date: RFC 3339 date (YYYY-MM-DD) -> `advanced_settings.source_policy.after_date`
+                - country / location: ISO 3166-1 alpha-2 code -> `advanced_settings.location`
                 - max_chars_per_result: -> `advanced_settings.excerpt_settings.max_chars_per_result`
-                - Any other params are passed through to the request body as-is
+                - fetch_policy: Cache vs live-fetch policy -> `advanced_settings.fetch_policy`
+                - Any other params (objective, max_chars_total, session_id, client_model, ...)
+                  are passed through to the request body as-is
 
         Returns:
             Dict with request data following the v1 search request spec
@@ -137,7 +169,7 @@ class ParallelAISearchConfig(BaseSearchConfig):
             mode = LEGACY_PROCESSOR_TO_MODE.get(processor, processor)
         # the v1 API defaults to 'advanced' when mode is omitted; default to 'basic'
         # instead to keep v1beta's default tier (processor 'base') and litellm's
-        # $0.004/query cost map entry for `parallel_ai/search` accurate
+        # cost map entry for `parallel_ai/search` accurate
         request_data["mode"] = mode or "basic"
 
         advanced_settings: Final[_ParallelAIAdvancedSettings] = {}
@@ -148,17 +180,29 @@ class ParallelAISearchConfig(BaseSearchConfig):
         if "country" in params:
             advanced_settings["location"] = params.pop("country")
 
+        if "location" in params:
+            advanced_settings["location"] = params.pop("location")
+
         if "max_chars_per_result" in params:
             advanced_settings["excerpt_settings"] = {"max_chars_per_result": params.pop("max_chars_per_result")}
 
+        if "fetch_policy" in params:
+            advanced_settings["fetch_policy"] = params.pop("fetch_policy")
+
         source_policy: Final[_ParallelAISourcePolicy] = {}
 
         if "search_domain_filter" in params:
             source_policy["include_domains"] = params.pop("search_domain_filter")
 
+        if "include_domains" in params:
+            source_policy["include_domains"] = params.pop("include_domains")
+
         if "exclude_domains" in params:
             source_policy["exclude_domains"] = params.pop("exclude_domains")
 
+        if "after_date" in params:
+            source_policy["after_date"] = params.pop("after_date")
+
         if source_policy:
             advanced_settings["source_policy"] = source_policy
 
@@ -170,9 +214,11 @@ class ParallelAISearchConfig(BaseSearchConfig):
         # unified-spec param with no v1 equivalent
         params.pop("max_tokens_per_page", None)
 
-        result_data: Final[dict] = dict(request_data)
-        result_data.update(params)
-        return result_data
+        # reserved for the provider's own reported usage, which prices the request;
+        # a caller-supplied value would otherwise set its own cost
+        params.pop(PARALLEL_AI_USAGE_PARAM, None)
+
+        return {**request_data, **params}
 
     def transform_search_response(
         self,
@@ -186,26 +232,49 @@ class ParallelAISearchConfig(BaseSearchConfig):
         Parallel AI -> LiteLLM mappings:
         - results[].title -> SearchResult.title
         - results[].url -> SearchResult.url
-        - results[].excerpts (array) -> SearchResult.snippet (joined string)
+        - results[].excerpts (array) -> SearchResult.snippet (joined string); the raw
+          array is preserved as an extra `excerpts` field on each result
         - results[].publish_date -> SearchResult.date
+        - search_id / session_id / warnings are preserved as extra fields on the
+          response; usage is preserved as `parallel_usage` (the `usage` name is
+          reserved for LiteLLM's token-usage object)
         """
-        response_json: Final = raw_response.json()
+        parsed: Final = _ParallelAIV1SearchResponse.model_validate(raw_response.json())
 
-        results: Final = []
-        for result in response_json.get("results", []):
-            excerpts = result.get("excerpts") or []
-            snippet = " ... ".join(excerpts) if excerpts else ""
+        # written unconditionally: leaving a caller-supplied value in place when the
+        # provider reports no usage would let the caller price its own request
+        logging_obj.optional_params = {
+            **logging_obj.optional_params,
+            PARALLEL_AI_USAGE_PARAM: parsed.usage,
+        }
 
-            search_result = SearchResult(
-                title=result.get("title") or "",
-                url=result.get("url") or "",
-                snippet=snippet,
-                date=result.get("publish_date"),
-                last_updated=None,
+        results: Final = tuple(
+            SearchResult.model_validate(
+                MappingProxyType(
+                    {
+                        "title": result.title or "",
+                        "url": result.url or "",
+                        "snippet": " ... ".join(result.excerpts or ()),
+                        "date": result.publish_date,
+                        "last_updated": None,
+                        "excerpts": result.excerpts or (),
+                    }
+                )
             )
-            results.append(search_result)
-
-        return SearchResponse(
-            results=results,
-            object="search",
+            for result in parsed.results
         )
+
+        extra_fields: Final = MappingProxyType(
+            {
+                key: value
+                for key, value in (
+                    ("search_id", parsed.search_id),
+                    ("session_id", parsed.session_id),
+                    ("parallel_usage", parsed.usage),
+                    ("warnings", parsed.warnings),
+                )
+                if value is not None
+            }
+        )
+
+        return SearchResponse.model_validate(MappingProxyType({"results": results, "object": "search", **extra_fields}))
diff --git a/litellm/llms/pg_vector/vector_stores/transformation.py b/litellm/llms/pg_vector/vector_stores/transformation.py
index e4b06c36bf4..9de1f589ae4 100644
--- a/litellm/llms/pg_vector/vector_stores/transformation.py
+++ b/litellm/llms/pg_vector/vector_stores/transformation.py
@@ -8,6 +8,7 @@ from litellm.types.vector_stores import VectorStoreSearchOptionalRequestParams
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -80,6 +81,7 @@ class PGVectorStoreConfig(OpenAIVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
         url: Final = f"{api_base}/{encoded_vector_store_id}/search"
diff --git a/litellm/llms/ragflow/vector_stores/transformation.py b/litellm/llms/ragflow/vector_stores/transformation.py
index 282cb7a92a7..ffa6c9e1076 100644
--- a/litellm/llms/ragflow/vector_stores/transformation.py
+++ b/litellm/llms/ragflow/vector_stores/transformation.py
@@ -17,6 +17,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -92,6 +93,7 @@ class RAGFlowVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """RAGFlow vector stores are management-only, search is not supported."""
         raise NotImplementedError("RAGFlow vector stores support dataset management only, not search/retrieval")
diff --git a/litellm/llms/s3_vectors/vector_stores/transformation.py b/litellm/llms/s3_vectors/vector_stores/transformation.py
index 5be35ae4148..733358381fe 100644
--- a/litellm/llms/s3_vectors/vector_stores/transformation.py
+++ b/litellm/llms/s3_vectors/vector_stores/transformation.py
@@ -1,8 +1,8 @@
-import re
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
 
+from litellm.caching._embedding_router import resolve_embedding_router
 from litellm.llms.base_llm.vector_store.transformation import BaseVectorStoreConfig
 from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
 from litellm.types.router import GenericLiteLLMParams
@@ -18,6 +18,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -58,13 +59,20 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         return headers
 
     def get_complete_url(self, api_base: str | None, litellm_params: dict) -> str:
-        aws_region_name: Final = litellm_params.get("aws_region_name")
-        if not aws_region_name:
-            raise ValueError("aws_region_name is required for S3 Vectors")
-        if not re.match(r"^[a-z][a-z0-9-]*$", aws_region_name):
-            raise ValueError("Invalid aws_region_name format")
+        # Resolve region the same way the ingestion path does:
+        # dynamic param -> AWS_REGION_NAME -> AWS_REGION -> default (us-west-2)
+        aws_region_name: Final = self.get_aws_region_name_for_non_llm_api_calls(litellm_params.get("aws_region_name"))
         return f"https://s3vectors.{aws_region_name}.api.aws"
 
+    def _resolve_query_embedding_router(self, embedding_model: str, router: "Router | None") -> "Router | None":
+        """Return the router iff it serves ``embedding_model`` as a deployment."""
+        if router is None:
+            return None
+        model_list: Final = [
+            dict(m) for m in (router.get_model_list() or ())
+        ]  # mutable-ok: resolve_embedding_router requires list[dict]
+        return resolve_embedding_router(embedding_model=embedding_model, llm_router=router, llm_model_list=model_list)
+
     def transform_search_vector_store_request(
         self,
         vector_store_id: str,
@@ -74,6 +82,7 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """Sync version - generates embedding synchronously."""
         # For S3 Vectors, vector_store_id should be in format: bucket_name:index_name
@@ -99,10 +108,16 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
 
         # Generate embedding for the query
         embedding_model: Final = litellm_params.get("embedding_model", "text-embedding-3-small")
+        embedding_router: Final = self._resolve_query_embedding_router(embedding_model=embedding_model, router=router)
 
         import litellm as litellm_module
 
-        embedding_response: Final = litellm_module.embedding(model=embedding_model, input=[query])
+        embedding_input: Final = [query]  # mutable-ok: the embedding API takes list input
+        embedding_response: Final = (
+            embedding_router.embedding(model=embedding_model, input=embedding_input)
+            if embedding_router is not None
+            else litellm_module.embedding(model=embedding_model, input=embedding_input)
+        )
         query_embedding: Final = embedding_response.data[0]["embedding"]
 
         url: Final = f"{api_base}/QueryVectors"
@@ -128,6 +143,7 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """Async version - generates embedding asynchronously."""
         # For S3 Vectors, vector_store_id should be in format: bucket_name:index_name
@@ -153,10 +169,16 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
 
         # Generate embedding for the query asynchronously
         embedding_model: Final = litellm_params.get("embedding_model", "text-embedding-3-small")
+        embedding_router: Final = self._resolve_query_embedding_router(embedding_model=embedding_model, router=router)
 
         import litellm as litellm_module
 
-        embedding_response: Final = await litellm_module.aembedding(model=embedding_model, input=[query])
+        embedding_input: Final = [query]  # mutable-ok: the embedding API takes list input
+        embedding_response: Final = (
+            await embedding_router.aembedding(model=embedding_model, input=embedding_input)
+            if embedding_router is not None
+            else await litellm_module.aembedding(model=embedding_model, input=embedding_input)
+        )
         query_embedding: Final = embedding_response.data[0]["embedding"]
 
         url: Final = f"{api_base}/QueryVectors"
diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
index d8b1e7ba17c..69fe5678de9 100644
--- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
+++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
@@ -949,7 +949,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
         # For Gemini 3+ models, use thinkingLevel instead of thinkingBudget
         if model and VertexGeminiConfig._is_gemini_3_or_newer(model):
             if thinking_enabled:
-                if thinking_budget is None or thinking_budget == 0:
+                if thinking_budget == 0:
                     params["includeThoughts"] = False
                 else:
                     params["includeThoughts"] = True
diff --git a/litellm/llms/vertex_ai/ocr/deepseek_transformation.py b/litellm/llms/vertex_ai/ocr/deepseek_transformation.py
index 2603552152d..b57a87c3325 100644
--- a/litellm/llms/vertex_ai/ocr/deepseek_transformation.py
+++ b/litellm/llms/vertex_ai/ocr/deepseek_transformation.py
@@ -177,8 +177,9 @@ class VertexAIDeepSeekOCRConfig(BaseOCRConfig):
             content_item = {"type": "image_url", "image_url": document_url}
 
         # Build DeepSeek OCR request
+        provider_model: Final = model if model.startswith("deepseek-ai/") else f"deepseek-ai/{model}"
         data: Final = {
-            "model": "deepseek-ai/" + model,
+            "model": provider_model,
             "messages": [{"role": "user", "content": [content_item]}],
         }
 
diff --git a/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py b/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py
index 5c250fc1a7e..36b57e7c995 100644
--- a/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py
+++ b/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py
@@ -21,6 +21,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -161,6 +162,7 @@ class VertexVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: Mapping[str, object] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict[str, object]]:
         """
         Transform search request for Vertex AI RAG API
diff --git a/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py b/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py
index 0bcf16ee06f..f0812e3ed9f 100644
--- a/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py
+++ b/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py
@@ -25,6 +25,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -245,6 +246,7 @@ class VertexSearchAPIVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: Mapping[str, object] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict[str, object]]:
         """
         Transform a search request for the Vertex AI Search (Discovery Engine) API.
diff --git a/litellm/main.py b/litellm/main.py
index c4c5bbefc4f..01c106adc7c 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -8637,6 +8637,16 @@ def _set_stream_builder_response_cost(response: ModelResponse, logging_obj: Opti
     hidden_params["response_cost"] = response_cost
 
 
+def _stamp_streaming_usage_cost(usage: Usage, response: ModelResponse, logging_obj: Optional["Logging"]) -> None:
+    if logging_obj is None:
+        return
+    if isinstance(getattr(usage, "cost", None), (int, float)):
+        return
+    computed_cost: Final = logging_obj._response_cost_calculator(result=response)
+    if isinstance(computed_cost, (int, float)) and computed_cost > 0:
+        setattr(usage, "cost", computed_cost)
+
+
 def stream_chunk_builder(
     chunks: list,
     messages: list | None = None,
@@ -8731,12 +8741,7 @@ def stream_chunk_builder(
                     )
                     break
 
-            if litellm.include_cost_in_streaming_usage and logging_obj is not None:
-                setattr(
-                    usage,
-                    "cost",
-                    logging_obj._response_cost_calculator(result=response),
-                )
+            _stamp_streaming_usage_cost(usage, response, logging_obj)
             _set_stream_builder_response_cost(response, logging_obj)
 
             processor.apply_provider_assembled_streaming_metadata(response, chunks, logging_obj)
@@ -8915,10 +8920,7 @@ def stream_chunk_builder(
                 )
                 break
 
-        # Add cost to usage object if include_cost_in_streaming_usage is True
-        if litellm.include_cost_in_streaming_usage and logging_obj is not None:
-            setattr(usage, "cost", logging_obj._response_cost_calculator(result=response))
-
+        _stamp_streaming_usage_cost(usage, response, logging_obj)
         _set_stream_builder_response_cost(response, logging_obj)
 
         processor.apply_provider_assembled_streaming_metadata(response, chunks, logging_obj)
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 55618d9f772..2846d12db6e 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -9643,7 +9643,8 @@
         "supported_endpoints": [
             "/v1/images/generations",
             "/v1/images/edits"
-        ]
+        ],
+        "deprecation_date": "2026-10-01"
     },
     "azure_ai/MAI-Image-2.5-Flash": {
         "input_cost_per_image_token": 1.75e-06,
@@ -9656,7 +9657,8 @@
         "supported_endpoints": [
             "/v1/images/generations",
             "/v1/images/edits"
-        ]
+        ],
+        "deprecation_date": "2026-10-01"
     },
     "azure_ai/MAI-Image-2e": {
         "deprecation_date": "2026-08-15",
@@ -10155,7 +10157,9 @@
         "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
         "supports_function_calling": true,
         "supports_reasoning": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "cache_read_input_token_cost": 1.45e-07,
+        "supports_prompt_caching": true
     },
     "azure_ai/deepseek-v4-flash": {
         "deprecation_date": "2028-02-20",
@@ -10169,18 +10173,20 @@
         "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
         "supports_function_calling": true,
         "supports_reasoning": true,
-        "supports_tool_choice": true
-    },
-    "azure_ai/deepseek-v4-flash-0731": {
+        "supports_tool_choice": true,
         "cache_read_input_token_cost": 2.8e-08,
+        "supports_prompt_caching": true
+    },
+    "azure_ai/DeepSeek-V4-Flash-0731": {
+        "cache_read_input_token_cost": 1.4e-08,
         "deprecation_date": "2026-12-03",
-        "input_cost_per_token": 1.9e-07,
+        "input_cost_per_token": 4.4e-07,
         "litellm_provider": "azure_ai",
         "max_input_tokens": 1000000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "mode": "chat",
-        "output_cost_per_token": 5.1e-07,
+        "output_cost_per_token": 1.32e-06,
         "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
         "supports_function_calling": true,
         "supports_prompt_caching": true,
@@ -10400,11 +10406,13 @@
         "max_tokens": 262144,
         "mode": "chat",
         "output_cost_per_token": 3e-06,
-        "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/kimi-k2-5-now-in-microsoft-foundry/4492321",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
         "supports_function_calling": true,
         "supports_tool_choice": true,
         "supports_video_input": true,
-        "supports_vision": true
+        "supports_vision": true,
+        "cache_read_input_token_cost": 1e-07,
+        "supports_prompt_caching": true
     },
     "azure_ai/kimi-k2.6": {
         "deprecation_date": "2027-04-16",
@@ -10415,7 +10423,7 @@
         "max_tokens": 262144,
         "mode": "chat",
         "output_cost_per_token": 4e-06,
-        "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-kimi-k2-6-in-microsoft-foundry/4513125",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
         "supported_modalities": [
             "text",
             "image"
@@ -10426,7 +10434,9 @@
         "supports_function_calling": true,
         "supports_reasoning": true,
         "supports_tool_choice": true,
-        "supports_vision": true
+        "supports_vision": true,
+        "cache_read_input_token_cost": 1.6e-07,
+        "supports_prompt_caching": true
     },
     "azure_ai/ministral-3b": {
         "input_cost_per_token": 4e-08,
@@ -12110,7 +12120,7 @@
         "max_output_tokens": 2048,
         "max_tokens": 2048,
         "mode": "chat",
-        "output_cost_per_token": 2.65e-06,
+        "output_cost_per_token": 6e-07,
         "supports_pdf_input": true
     },
     "bedrock/us-west-1/meta.llama3-70b-instruct-v1:0": {
@@ -23514,6 +23524,63 @@
         "web_search_billing_unit": "per_query",
         "google_maps_grounding_cost_per_query": 0.014
     },
+    "vertex_ai/gemini-3.8-flash": {
+        "prompt_cache_min_tokens": 4096,
+        "cache_read_input_token_cost": 7.5e-08,
+        "cache_read_input_token_cost_flex": 3.75e-08,
+        "input_cost_per_token": 7.5e-07,
+        "input_cost_per_token_batches": 3.75e-07,
+        "input_cost_per_token_flex": 3.75e-07,
+        "litellm_provider": "vertex_ai",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 3.75e-06,
+        "output_cost_per_token": 3.75e-06,
+        "output_cost_per_token_batches": 1.875e-06,
+        "output_cost_per_token_flex": 1.875e-06,
+        "regional_endpoint_uplift_multiplier": 1.1,
+        "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/completions",
+            "/v1/batch"
+        ],
+        "supported_modalities": [
+            "text",
+            "image",
+            "audio",
+            "video"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_audio_input": true,
+        "supports_function_calling": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_url_context": true,
+        "supports_video_input": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_native_streaming": true,
+        "input_cost_per_token_priority": 1.35e-06,
+        "output_cost_per_token_priority": 6.75e-06,
+        "cache_read_input_token_cost_priority": 1.35e-07,
+        "search_context_cost_per_query": {
+            "search_context_size_low": 0.014,
+            "search_context_size_medium": 0.014,
+            "search_context_size_high": 0.014
+        },
+        "web_search_billing_unit": "per_query",
+        "google_maps_grounding_cost_per_query": 0.014
+    },
     "vertex_ai/gemini-3.1-pro-preview": {
         "prompt_cache_min_tokens": 4096,
         "cache_read_input_token_cost": 2e-07,
@@ -25351,6 +25418,65 @@
         "web_search_billing_unit": "per_query",
         "google_maps_grounding_cost_per_query": 0.014
     },
+    "gemini/gemini-3.8-flash": {
+        "prompt_cache_min_tokens": 4096,
+        "cache_read_input_token_cost": 7.5e-08,
+        "cache_read_input_token_cost_flex": 3.75e-08,
+        "input_cost_per_token": 7.5e-07,
+        "input_cost_per_token_batches": 3.75e-07,
+        "input_cost_per_token_flex": 3.75e-07,
+        "litellm_provider": "gemini",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 3.75e-06,
+        "output_cost_per_token": 3.75e-06,
+        "output_cost_per_token_batches": 1.875e-06,
+        "output_cost_per_token_flex": 1.875e-06,
+        "rpm": 2000,
+        "source": "https://ai.google.dev/gemini-api/docs/pricing",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/completions",
+            "/v1/batch"
+        ],
+        "supported_modalities": [
+            "text",
+            "image",
+            "audio",
+            "video"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_audio_output": false,
+        "supports_audio_input": true,
+        "supports_function_calling": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_url_context": true,
+        "supports_video_input": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_native_streaming": true,
+        "tpm": 800000,
+        "input_cost_per_token_priority": 1.35e-06,
+        "output_cost_per_token_priority": 6.75e-06,
+        "cache_read_input_token_cost_priority": 1.35e-07,
+        "search_context_cost_per_query": {
+            "search_context_size_low": 0.014,
+            "search_context_size_medium": 0.014,
+            "search_context_size_high": 0.014
+        },
+        "web_search_billing_unit": "per_query",
+        "google_maps_grounding_cost_per_query": 0.014
+    },
     "gemini/gemini-omni-flash-preview": {
         "input_cost_per_audio_token": 1.5e-06,
         "input_cost_per_token": 1.5e-06,
@@ -25759,6 +25885,63 @@
         "web_search_billing_unit": "per_query",
         "google_maps_grounding_cost_per_query": 0.014
     },
+    "gemini-3.8-flash": {
+        "prompt_cache_min_tokens": 4096,
+        "cache_read_input_token_cost": 7.5e-08,
+        "cache_read_input_token_cost_flex": 3.75e-08,
+        "input_cost_per_token": 7.5e-07,
+        "input_cost_per_token_batches": 3.75e-07,
+        "input_cost_per_token_flex": 3.75e-07,
+        "litellm_provider": "vertex_ai-language-models",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 3.75e-06,
+        "output_cost_per_token": 3.75e-06,
+        "output_cost_per_token_batches": 1.875e-06,
+        "output_cost_per_token_flex": 1.875e-06,
+        "source": "https://ai.google.dev/gemini-api/docs/pricing",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/completions",
+            "/v1/batch"
+        ],
+        "supported_modalities": [
+            "text",
+            "image",
+            "audio",
+            "video"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_audio_output": false,
+        "supports_audio_input": true,
+        "supports_function_calling": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_url_context": true,
+        "supports_video_input": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_native_streaming": true,
+        "input_cost_per_token_priority": 1.35e-06,
+        "output_cost_per_token_priority": 6.75e-06,
+        "cache_read_input_token_cost_priority": 1.35e-07,
+        "search_context_cost_per_query": {
+            "search_context_size_low": 0.014,
+            "search_context_size_medium": 0.014,
+            "search_context_size_high": 0.014
+        },
+        "web_search_billing_unit": "per_query",
+        "google_maps_grounding_cost_per_query": 0.014
+    },
     "gemini/gemini-2.5-pro-preview-tts": {
         "cache_read_input_token_cost": 1.25e-07,
         "input_cost_per_audio_token": 7e-07,
@@ -29098,16 +29281,19 @@
         "cache_creation_input_token_cost": 5e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1e-05,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 5e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
         "cache_creation_input_token_cost_flex": 2.5e-06,
         "cache_creation_input_token_cost_priority": 1e-05,
         "cache_read_input_token_cost": 4e-07,
         "cache_read_input_token_cost_above_272k_tokens": 8e-07,
         "cache_read_input_token_cost_above_272k_tokens_flex": 4e-07,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
         "cache_read_input_token_cost_flex": 2e-07,
         "cache_read_input_token_cost_priority": 8e-07,
         "input_cost_per_token": 4e-06,
         "input_cost_per_token_above_272k_tokens": 8e-06,
         "input_cost_per_token_above_272k_tokens_flex": 4e-06,
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
         "input_cost_per_token_batches": 2e-06,
         "input_cost_per_token_flex": 2e-06,
         "input_cost_per_token_priority": 8e-06,
@@ -29119,6 +29305,7 @@
         "output_cost_per_token": 2e-05,
         "output_cost_per_token_above_272k_tokens": 3e-05,
         "output_cost_per_token_above_272k_tokens_flex": 1.5e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
         "output_cost_per_token_batches": 1e-05,
         "output_cost_per_token_flex": 1e-05,
         "output_cost_per_token_priority": 4e-05,
@@ -29161,16 +29348,19 @@
         "cache_creation_input_token_cost": 5e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1e-05,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 5e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
         "cache_creation_input_token_cost_flex": 2.5e-06,
         "cache_creation_input_token_cost_priority": 1e-05,
         "cache_read_input_token_cost": 4e-07,
         "cache_read_input_token_cost_above_272k_tokens": 8e-07,
         "cache_read_input_token_cost_above_272k_tokens_flex": 4e-07,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
         "cache_read_input_token_cost_flex": 2e-07,
         "cache_read_input_token_cost_priority": 8e-07,
         "input_cost_per_token": 4e-06,
         "input_cost_per_token_above_272k_tokens": 8e-06,
         "input_cost_per_token_above_272k_tokens_flex": 4e-06,
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
         "input_cost_per_token_batches": 2e-06,
         "input_cost_per_token_flex": 2e-06,
         "input_cost_per_token_priority": 8e-06,
@@ -29182,6 +29372,7 @@
         "output_cost_per_token": 2e-05,
         "output_cost_per_token_above_272k_tokens": 3e-05,
         "output_cost_per_token_above_272k_tokens_flex": 1.5e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
         "output_cost_per_token_batches": 1e-05,
         "output_cost_per_token_flex": 1e-05,
         "output_cost_per_token_priority": 4e-05,
@@ -29225,16 +29416,19 @@
         "cache_creation_input_token_cost": 2.5e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 5e-06,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-05,
         "cache_creation_input_token_cost_flex": 1.25e-06,
         "cache_creation_input_token_cost_priority": 5e-06,
         "cache_read_input_token_cost": 2e-07,
         "cache_read_input_token_cost_above_272k_tokens": 4e-07,
         "cache_read_input_token_cost_above_272k_tokens_flex": 2e-07,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07,
         "cache_read_input_token_cost_flex": 1e-07,
         "cache_read_input_token_cost_priority": 4e-07,
         "input_cost_per_token": 2e-06,
         "input_cost_per_token_above_272k_tokens": 4e-06,
         "input_cost_per_token_above_272k_tokens_flex": 2e-06,
+        "input_cost_per_token_above_272k_tokens_priority": 8e-06,
         "input_cost_per_token_batches": 1e-06,
         "input_cost_per_token_flex": 1e-06,
         "input_cost_per_token_priority": 4e-06,
@@ -29246,6 +29440,7 @@
         "output_cost_per_token": 1.2e-05,
         "output_cost_per_token_above_272k_tokens": 1.8e-05,
         "output_cost_per_token_above_272k_tokens_flex": 9e-06,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-05,
         "output_cost_per_token_batches": 6e-06,
         "output_cost_per_token_flex": 6e-06,
         "output_cost_per_token_priority": 2.4e-05,
@@ -29288,16 +29483,19 @@
         "cache_creation_input_token_cost": 2.5e-07,
         "cache_creation_input_token_cost_above_272k_tokens": 5e-07,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-07,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-06,
         "cache_creation_input_token_cost_flex": 1.25e-07,
         "cache_creation_input_token_cost_priority": 5e-07,
         "cache_read_input_token_cost": 2e-08,
         "cache_read_input_token_cost_above_272k_tokens": 4e-08,
         "cache_read_input_token_cost_above_272k_tokens_flex": 2e-08,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08,
         "cache_read_input_token_cost_flex": 1e-08,
         "cache_read_input_token_cost_priority": 4e-08,
         "input_cost_per_token": 2e-07,
         "input_cost_per_token_above_272k_tokens": 4e-07,
         "input_cost_per_token_above_272k_tokens_flex": 2e-07,
+        "input_cost_per_token_above_272k_tokens_priority": 8e-07,
         "input_cost_per_token_batches": 1e-07,
         "input_cost_per_token_flex": 1e-07,
         "input_cost_per_token_priority": 4e-07,
@@ -29309,6 +29507,7 @@
         "output_cost_per_token": 1.2e-06,
         "output_cost_per_token_above_272k_tokens": 1.8e-06,
         "output_cost_per_token_above_272k_tokens_flex": 9e-07,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-06,
         "output_cost_per_token_batches": 6e-07,
         "output_cost_per_token_flex": 6e-07,
         "output_cost_per_token_priority": 2.4e-06,
@@ -29548,7 +29747,10 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": false
+        "supports_minimal_reasoning_effort": false,
+        "input_cost_per_token_above_272k_tokens_flex": 5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 2.25e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07
     },
     "gpt-5.5-2026-04-23": {
         "cache_read_input_token_cost": 5e-07,
@@ -29602,7 +29804,10 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": false
+        "supports_minimal_reasoning_effort": false,
+        "input_cost_per_token_above_272k_tokens_flex": 5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 2.25e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07
     },
     "gpt-5.5-pro": {
         "cache_read_input_token_cost": 3e-06,
@@ -29751,7 +29956,10 @@
         "supports_none_reasoning_effort": true,
         "default_reasoning_effort": "none",
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 2.5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 1.125e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07
     },
     "gpt-5.4-2026-03-05": {
         "cache_read_input_token_cost": 2.5e-07,
@@ -29800,7 +30008,10 @@
         "supports_none_reasoning_effort": true,
         "default_reasoning_effort": "none",
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 2.5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 1.125e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07
     },
     "gpt-5.4-pro": {
         "cache_read_input_token_cost": 3e-06,
@@ -29849,7 +30060,9 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": false,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 3e-05,
+        "output_cost_per_token_above_272k_tokens_flex": 0.000135
     },
     "gpt-5.4-pro-2026-03-05": {
         "cache_read_input_token_cost": 3e-06,
@@ -29898,7 +30111,9 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": false,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 3e-05,
+        "output_cost_per_token_above_272k_tokens_flex": 0.000135
     },
     "gpt-5.4-mini": {
         "cache_read_input_token_cost": 7.5e-08,
@@ -30834,17 +31049,18 @@
     },
     "gpt-realtime-2": {
         "cache_creation_input_audio_token_cost": 4e-07,
+        "cache_read_input_audio_token_cost": 4e-07,
         "cache_read_input_token_cost": 4e-07,
         "input_cost_per_audio_token": 3.2e-05,
         "input_cost_per_image": 5e-06,
         "input_cost_per_token": 4e-06,
         "litellm_provider": "openai",
-        "max_input_tokens": 32000,
-        "max_output_tokens": 4096,
-        "max_tokens": 4096,
+        "max_input_tokens": 128000,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
         "mode": "realtime",
         "output_cost_per_audio_token": 6.4e-05,
-        "output_cost_per_token": 1.6e-05,
+        "output_cost_per_token": 2.4e-05,
         "supported_endpoints": [
             "/v1/realtime"
         ],
@@ -30908,8 +31124,8 @@
         "input_cost_per_token": 6e-07,
         "litellm_provider": "openai",
         "max_input_tokens": 128000,
-        "max_output_tokens": 4096,
-        "max_tokens": 4096,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
         "mode": "realtime",
         "output_cost_per_audio_token": 2e-05,
         "output_cost_per_token": 2.4e-06,
@@ -30941,7 +31157,7 @@
         "input_cost_per_audio_token": 1e-05,
         "input_cost_per_token": 6e-07,
         "litellm_provider": "openai",
-        "max_input_tokens": 128000,
+        "max_input_tokens": 32000,
         "max_output_tokens": 4096,
         "max_tokens": 4096,
         "mode": "realtime",
@@ -33705,19 +33921,21 @@
         "source": "https://mistral.ai/pricing#api-pricing"
     },
     "mistral/magistral-medium-latest": {
-        "input_cost_per_token": 2e-06,
+        "cache_read_input_token_cost": 1.5e-07,
+        "input_cost_per_token": 1.5e-06,
         "litellm_provider": "mistral",
-        "max_input_tokens": 40000,
-        "max_output_tokens": 40000,
-        "max_tokens": 40000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
-        "output_cost_per_token": 5e-06,
-        "source": "https://mistral.ai/news/magistral",
+        "output_cost_per_token": 7.5e-06,
+        "source": "https://docs.mistral.ai/models/model-cards/mistral-medium-3-5-26-04",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
         "supports_reasoning": true,
         "supports_response_schema": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "supports_vision": true
     },
     "mistral/magistral-small-2506": {
         "deprecation_date": "2025-11-30",
@@ -33736,19 +33954,21 @@
         "supports_tool_choice": true
     },
     "mistral/magistral-small-latest": {
-        "input_cost_per_token": 5e-07,
+        "cache_read_input_token_cost": 1.5e-08,
+        "input_cost_per_token": 1.5e-07,
         "litellm_provider": "mistral",
-        "max_input_tokens": 40000,
-        "max_output_tokens": 40000,
-        "max_tokens": 40000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
-        "output_cost_per_token": 1.5e-06,
-        "source": "https://mistral.ai/pricing#api-pricing",
+        "output_cost_per_token": 6e-07,
+        "source": "https://docs.mistral.ai/models/model-cards/mistral-small-4-0-26-03",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
         "supports_reasoning": true,
         "supports_response_schema": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "supports_vision": true
     },
     "mistral/magistral-small-1-2-2509": {
         "deprecation_date": "2026-07-31",
@@ -33880,16 +34100,21 @@
         "supports_vision": true
     },
     "mistral/mistral-medium": {
-        "input_cost_per_token": 2.7e-06,
+        "cache_read_input_token_cost": 1.5e-07,
+        "input_cost_per_token": 1.5e-06,
         "litellm_provider": "mistral",
-        "max_input_tokens": 32000,
-        "max_output_tokens": 8191,
-        "max_tokens": 8191,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
-        "output_cost_per_token": 8.1e-06,
+        "output_cost_per_token": 7.5e-06,
+        "source": "https://docs.mistral.ai/models/model-cards/mistral-medium-3-5-26-04",
         "supports_assistant_prefill": true,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
         "supports_response_schema": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "supports_vision": true
     },
     "mistral/mistral-medium-2312": {
         "deprecation_date": "2025-06-16",
@@ -38556,12 +38781,22 @@
         "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
     },
     "parallel_ai/search": {
-        "input_cost_per_query": 0.004,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-fast": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
     "parallel_ai/search-pro": {
-        "input_cost_per_query": 0.009,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-turbo": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
@@ -41330,13 +41565,13 @@
         "source": "https://docs.together.ai/docs/serverless-models"
     },
     "together_ai/Qwen/Qwen3.8-2.4T-A95B": {
-        "cache_read_input_token_cost": 5e-07,
-        "input_cost_per_token": 2.5e-06,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 2e-06,
         "litellm_provider": "together_ai",
         "max_input_tokens": 1010000,
         "max_tokens": 1010000,
         "mode": "chat",
-        "output_cost_per_token": 6.25e-06,
+        "output_cost_per_token": 6e-06,
         "source": "https://docs.together.ai/docs/serverless-models",
         "supports_prompt_caching": true
     },
@@ -41946,6 +42181,70 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 1024
     },
+    "us-gov.anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "us-gov.anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
     "au.anthropic.claude-haiku-4-5-20251001-v1:0": {
         "cache_creation_input_token_cost": 1.375e-06,
         "cache_creation_input_token_cost_above_1hr": 2.2e-06,
@@ -45839,6 +46138,26 @@
         "mode": "rerank",
         "output_cost_per_token": 0.0
     },
+    "voyage/rerank-3": {
+        "input_cost_per_token": 5e-08,
+        "litellm_provider": "voyage",
+        "max_input_tokens": 32000,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
+        "mode": "rerank",
+        "output_cost_per_token": 0.0,
+        "source": "https://docs.voyageai.com/docs/pricing"
+    },
+    "voyage/rerank-3-lite": {
+        "input_cost_per_token": 2e-08,
+        "litellm_provider": "voyage",
+        "max_input_tokens": 32000,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
+        "mode": "rerank",
+        "output_cost_per_token": 0.0,
+        "source": "https://docs.voyageai.com/docs/pricing"
+    },
     "voyage/voyage-2": {
         "input_cost_per_token": 1e-07,
         "litellm_provider": "voyage",
@@ -47090,6 +47409,27 @@
         "supports_vision": true,
         "supports_web_search": true
     },
+    "xai/grok-build-latest": {
+        "cache_read_input_token_cost": 3e-07,
+        "cache_read_input_token_cost_above_200k_tokens": 6e-07,
+        "input_cost_per_token": 2e-06,
+        "input_cost_per_token_above_200k_tokens": 4e-06,
+        "litellm_provider": "xai",
+        "max_input_tokens": 500000,
+        "max_output_tokens": 500000,
+        "max_tokens": 500000,
+        "mode": "chat",
+        "output_cost_per_token": 6e-06,
+        "output_cost_per_token_above_200k_tokens": 1.2e-05,
+        "source": "https://docs.x.ai/developers/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true
+    },
     "xai/grok-4.6": {
         "cache_read_input_token_cost": 5e-07,
         "cache_read_input_token_cost_above_200k_tokens": 1e-06,
@@ -57410,6 +57750,34 @@
         "supports_tool_choice": true,
         "supports_vision": false
     },
+    "fireworks_ai/accounts/fireworks/models/glm-5p3-flash": {
+        "cache_read_input_token_cost": 3e-08,
+        "input_cost_per_token": 1.5e-07,
+        "litellm_provider": "fireworks_ai",
+        "max_input_tokens": 1048576,
+        "max_tokens": 1048576,
+        "mode": "chat",
+        "output_cost_per_token": 5e-07,
+        "source": "https://docs.fireworks.ai/serverless/pricing",
+        "supports_function_calling": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "fireworks_ai/accounts/fireworks/models/inkling": {
+        "cache_read_input_token_cost": 1.7e-07,
+        "input_cost_per_token": 1e-06,
+        "litellm_provider": "fireworks_ai",
+        "max_input_tokens": 1048576,
+        "max_tokens": 1048576,
+        "mode": "chat",
+        "output_cost_per_token": 4.05e-06,
+        "source": "https://fireworks.ai/models/fireworks/inkling",
+        "supports_function_calling": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "fireworks_ai/accounts/fireworks/models/qwen3-embedding-8b": {
         "input_cost_per_token": 1e-07,
         "output_cost_per_token": 0.0,
@@ -57469,5 +57837,542 @@
         "supported_endpoints": [
             "/v1/audio/transcriptions"
         ]
+    },
+    "scaleway/glm-5.2": {
+        "input_cost_per_token": 1.8e-06,
+        "litellm_provider": "scaleway",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-06,
+        "source": "https://www.scaleway.com/en/pricing/model-as-a-service/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_vision": false
+    },
+    "scaleway/deepseek-v4-flash-0731": {
+        "cache_read_input_token_cost": 8e-08,
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "scaleway",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 8e-07,
+        "source": "https://www.scaleway.com/en/pricing/model-as-a-service/",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_vision": false
+    },
+    "azure_ai/kimi-k2.7-code": {
+        "cache_read_input_token_cost": 1.9e-07,
+        "deprecation_date": "2026-10-03",
+        "input_cost_per_token": 9.5e-07,
+        "litellm_provider": "azure_ai",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
+        "mode": "chat",
+        "output_cost_per_token": 4e-06,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-nano-3-30b": {
+        "input_cost_per_token": 7.2e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.88e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2": {
+        "input_cost_per_token": 2.4e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_system_messages": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 7.8e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0": {
+        "input_cost_per_token": 8.4e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3.6e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-west-1/anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b": {
+        "input_cost_per_token": 7.2e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.88e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-nano-12b-v2": {
+        "input_cost_per_token": 2.4e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_system_messages": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 7.8e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/openai.gpt-oss-20b-1:0": {
+        "input_cost_per_token": 8.4e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3.6e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/openai.gpt-oss-120b-1:0": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-east-1/anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-terra": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 2.64e-06,
+        "input_cost_per_token_above_272k_tokens": 5.28e-06,
+        "cache_creation_input_token_cost": 3.3e-06,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-06,
+        "cache_read_input_token_cost": 2.64e-07,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-07,
+        "output_cost_per_token": 1.584e-05,
+        "output_cost_per_token_above_272k_tokens": 2.376e-05
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-luna": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 2.64e-07,
+        "input_cost_per_token_above_272k_tokens": 5.28e-07,
+        "cache_creation_input_token_cost": 3.3e-07,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-07,
+        "cache_read_input_token_cost": 2.64e-08,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-08,
+        "output_cost_per_token": 1.584e-06,
+        "output_cost_per_token_above_272k_tokens": 2.376e-06
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.4": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 3.3e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "output_cost_per_token": 1.98e-05
+    },
+    "bedrock_mantle/us-gov-west-1/xai.grok-4.3": {
+        "use_openai_responses_path": true,
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "input_cost_per_token": 1.5e-06,
+        "output_cost_per_token": 3e-06,
+        "cache_read_input_token_cost": 2.4e-07
+    },
+    "bedrock_mantle/us-gov-east-1/openai.gpt-5.4": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 3.3e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "output_cost_per_token": 1.98e-05
+    },
+    "azure/us-gov/gpt-5.1": {
+        "cache_read_input_token_cost": 1.71875e-07,
+        "default_reasoning_effort": "none",
+        "input_cost_per_token": 1.71875e-06,
+        "litellm_provider": "azure",
+        "max_input_tokens": 272000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.375e-05,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/batch",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text",
+            "image"
+        ],
+        "supports_function_calling": true,
+        "supports_native_streaming": true,
+        "supports_none_reasoning_effort": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "azure/us-gov/o3-mini": {
+        "cache_read_input_token_cost": 7.57e-07,
+        "input_cost_per_token": 1.513e-06,
+        "litellm_provider": "azure",
+        "max_input_tokens": 200000,
+        "max_output_tokens": 100000,
+        "max_tokens": 100000,
+        "mode": "chat",
+        "output_cost_per_token": 6.05e-06,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": false
+    },
+    "azure/us-gov/text-embedding-3-large": {
+        "input_cost_per_token": 1.63e-07,
+        "litellm_provider": "azure",
+        "max_input_tokens": 8191,
+        "max_tokens": 8191,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0
+    },
+    "azure/us-gov/text-embedding-3-small": {
+        "input_cost_per_token": 2.5e-08,
+        "litellm_provider": "azure",
+        "max_input_tokens": 8191,
+        "max_tokens": 8191,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0
+    },
+    "cloudflare/@cf/openai/whisper": {
+        "input_cost_per_second": 7.5e-06,
+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper/",
+        "supported_endpoints": [
+            "/v1/audio/transcriptions"
+        ]
+    },
+    "cloudflare/@cf/openai/whisper-large-v3-turbo": {
+        "input_cost_per_second": 8.5e-06,
+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper-large-v3-turbo/",
+        "supported_endpoints": [
+            "/v1/audio/transcriptions"
+        ]
     }
 }
diff --git a/litellm/models/user.py b/litellm/models/user.py
index 259c3440d87..82f78c28078 100644
--- a/litellm/models/user.py
+++ b/litellm/models/user.py
@@ -7,7 +7,7 @@ Canonical definition for ``litellm_usertable``. Re-exported from
 
 from datetime import datetime
 
-from pydantic import ConfigDict, Field, model_validator
+from pydantic import BaseModel, ConfigDict, Field, model_validator
 
 from litellm.models.object_permission import LiteLLM_ObjectPermissionTable
 from litellm.models.organization_membership import (
@@ -67,3 +67,11 @@ class LiteLLM_UserTable(LiteLLMPydanticObjectBase):
         if not self.models:
             return True
         return model_name in self.models
+
+
+class SCIMPlaceholder(BaseModel):
+    """A user row keyed by a value that names another account by SSO identity or email."""
+
+    placeholder_user_id: str
+    resolved_user_ids: tuple[str, ...]
+    team_ids: tuple[str, ...]
diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index 2b89dba0e4f..d1ef73a15cd 100644
--- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
@@ -1,7 +1,8 @@
 import asyncio
 import importlib
-from collections.abc import Awaitable, Callable, Mapping
+from collections.abc import Awaitable, Callable, Mapping, Sequence
 from datetime import datetime
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Literal
 
 import anyio
@@ -20,8 +21,11 @@ from litellm.proxy._experimental.mcp_server.exceptions import (
     MCPUpstreamAuthError,
 )
 from litellm.proxy._experimental.mcp_server.faults.list_outcomes import (
+    ServerListOk,
+    ServerOutcome,
     classify_list_exception,
     list_fault_http_status,
+    outcome_wire_value,
 )
 from litellm.proxy._experimental.mcp_server.ui_session_utils import (
     acting_user_auth,
@@ -99,6 +103,7 @@ if MCP_AVAILABLE:
         ListMCPToolsRestAPIResponseObject,
         MCPInfo,
         MCPServer,
+        _aggregate_server_key,  # pyright: ignore[reportPrivateUsage]  # same per-server key as the tools/list _meta outcomes
         _apply_toolset_scope,
         _fire_mcp_tool_call_logging,
         execute_mcp_tool,
@@ -803,9 +808,6 @@ if MCP_AVAILABLE:
                 list(allowed_server_ids_set), _rest_client_ip
             )
 
-            list_tools_result: Final = []
-            error_message = None
-
             # If server_id is specified, only query that specific server
             if server_id:
                 return await _list_tools_for_single_server(
@@ -849,22 +851,19 @@ if MCP_AVAILABLE:
                     else {}
                 )
 
-                # Query all servers the user has access to
-                errors: Final = []
-                for allowed_server_id in allowed_server_ids:
-                    server = global_mcp_server_manager.get_mcp_server_by_id(allowed_server_id)
-                    if server is None:
-                        continue
-
-                    server_auth_header = _get_server_auth_header(server, mcp_server_auth_headers, mcp_auth_header)
-                    user_oauth_extra_headers = await _get_user_oauth_extra_headers(
+                async def list_server(
+                    server: MCPServer,
+                ) -> tuple[Sequence[ListMCPToolsRestAPIResponseObject], ServerOutcome]:
+                    server_auth_header: Final = _get_server_auth_header(
+                        server, mcp_server_auth_headers, mcp_auth_header
+                    )
+                    user_oauth_extra_headers: Final = await _get_user_oauth_extra_headers(
                         server,
                         user_api_key_dict,
                         prefetched_creds=prefetched_oauth_creds,
                     )
-
                     try:
-                        tools_result = await _get_tools_for_single_server(
+                        tools_result: Final = await _get_tools_for_single_server(
                             server,
                             server_auth_header,
                             raw_headers_from_request,
@@ -872,24 +871,36 @@ if MCP_AVAILABLE:
                             extra_headers=user_oauth_extra_headers,
                             apply_tool_filters=apply_tool_filters,
                         )
-                        list_tools_result.extend(tools_result)
                     except Exception as e:
                         verbose_logger.exception("Error getting tools from %s: %s", server.name, e)
-                        errors.append(
-                            f"{get_server_prefix(server)}: {classify_list_exception(e).tag}"
-                            if isinstance(e, (MCPServerListError, MCPUpstreamAuthError))
-                            else f"{get_server_prefix(server)}: {e}"
-                        )
-                        continue
+                        return (), classify_list_exception(e)
+                    return tools_result, ServerListOk(tool_count=len(tools_result))
 
-                if errors and not list_tools_result:
-                    error_message = "Failed to get tools from servers: " + "; ".join(errors)
-
-            return {
-                "tools": list_tools_result,
-                "error": "partial_failure" if error_message else None,
-                "message": (error_message if error_message else "Successfully retrieved tools"),
-            }
+                # Query all servers the user has access to
+                queried_servers: Final = tuple(
+                    server
+                    for server in map(global_mcp_server_manager.get_mcp_server_by_id, allowed_server_ids)
+                    if server is not None
+                )
+                listings: Final = tuple([await list_server(server) for server in queried_servers])
+                list_tools_result: Final = [tool for tools, _ in listings for tool in tools]
+                server_outcomes: Final = MappingProxyType(
+                    {_aggregate_server_key(server): outcome for server, (_, outcome) in zip(queried_servers, listings)}
+                )
+                errors: Final = tuple(
+                    f"{key}: {outcome.tag}" for key, outcome in server_outcomes.items() if outcome.tag != "ok"
+                )
+                error_message: Final = (
+                    "Failed to get tools from servers: " + "; ".join(errors)
+                    if errors and not list_tools_result
+                    else None
+                )
+                return {
+                    "tools": list_tools_result,
+                    "error": "partial_failure" if error_message else None,
+                    "message": (error_message if error_message else "Successfully retrieved tools"),
+                    "server_outcomes": {key: outcome_wire_value(outcome) for key, outcome in server_outcomes.items()},
+                }
 
         except MCPUpstreamAuthError as e:
             # Surface upstream pass-through 401/403 challenges to the client so
diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json
index 5af45b29226..13c7a4c7cfa 100644
--- a/litellm/proxy/_lazy_openapi_snapshot.json
+++ b/litellm/proxy/_lazy_openapi_snapshot.json
@@ -32002,6 +32002,62 @@
           "title": "SCIMPatchOperation",
           "type": "object"
         },
+        "SCIMPlaceholder": {
+          "description": "A user row keyed by a value that names another account by SSO identity or email.",
+          "properties": {
+            "placeholder_user_id": {
+              "title": "Placeholder User Id",
+              "type": "string"
+            },
+            "resolved_user_ids": {
+              "items": {
+                "type": "string"
+              },
+              "title": "Resolved User Ids",
+              "type": "array"
+            },
+            "team_ids": {
+              "items": {
+                "type": "string"
+              },
+              "title": "Team Ids",
+              "type": "array"
+            }
+          },
+          "required": [
+            "placeholder_user_id",
+            "resolved_user_ids",
+            "team_ids"
+          ],
+          "title": "SCIMPlaceholder",
+          "type": "object"
+        },
+        "SCIMPlaceholderMergeResult": {
+          "properties": {
+            "merged_into_user_id": {
+              "title": "Merged Into User Id",
+              "type": "string"
+            },
+            "placeholder_user_id": {
+              "title": "Placeholder User Id",
+              "type": "string"
+            },
+            "team_ids": {
+              "items": {
+                "type": "string"
+              },
+              "title": "Team Ids",
+              "type": "array"
+            }
+          },
+          "required": [
+            "placeholder_user_id",
+            "merged_into_user_id",
+            "team_ids"
+          ],
+          "title": "SCIMPlaceholderMergeResult",
+          "type": "object"
+        },
         "SCIMServiceProviderConfig": {
           "properties": {
             "authenticationSchemes": {
@@ -33641,6 +33697,129 @@
             "scim"
           ]
         }
+      },
+      "/scim/v2/placeholders": {
+        "get": {
+          "description": "List user rows whose id is another account's SSO identity or email.\n\nAn earlier release provisioned a group member it could not match as a user keyed\nby the raw member value, and that row now shadows the account the value really\nnames, so every push of that member is refused. This lists those rows so an\noperator can fold each one into the account it shadows with\n``POST /scim/v2/placeholders/{user_id}/merge``. A row that has an SSO identity of\nits own or owns virtual keys is left out: someone uses that account.",
+          "operationId": "list_placeholders_scim_v2_placeholders_get",
+          "parameters": [
+            {
+              "in": "query",
+              "name": "feature",
+              "required": false,
+              "schema": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "type": "null"
+                  }
+                ],
+                "title": "Feature"
+              }
+            }
+          ],
+          "responses": {
+            "200": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "items": {
+                      "$ref": "#/components/schemas/SCIMPlaceholder"
+                    },
+                    "title": "Response List Placeholders Scim V2 Placeholders Get",
+                    "type": "array"
+                  }
+                }
+              },
+              "description": "Successful Response"
+            },
+            "422": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "$ref": "#/components/schemas/HTTPValidationError"
+                  }
+                }
+              },
+              "description": "Validation Error"
+            }
+          },
+          "security": [
+            {
+              "APIKeyHeader": []
+            }
+          ],
+          "summary": "List Placeholders",
+          "tags": [
+            "scim"
+          ]
+        }
+      },
+      "/scim/v2/placeholders/{user_id}/merge": {
+        "post": {
+          "description": "Fold a placeholder user into the one account its id names by SSO identity or email.\n\nThe account is added to every team the placeholder is on, then the placeholder is\ndeleted the way ``DELETE /scim/v2/Users/{id}`` deletes a user, so the next group\npush resolves the member value to the real account. Refused with 409 when the row\nhas an SSO identity of its own, owns virtual keys, or names no account or several.",
+          "operationId": "merge_placeholder_scim_v2_placeholders__user_id__merge_post",
+          "parameters": [
+            {
+              "in": "path",
+              "name": "user_id",
+              "required": true,
+              "schema": {
+                "title": "User ID",
+                "type": "string"
+              }
+            },
+            {
+              "in": "query",
+              "name": "feature",
+              "required": false,
+              "schema": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "type": "null"
+                  }
+                ],
+                "title": "Feature"
+              }
+            }
+          ],
+          "responses": {
+            "200": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "$ref": "#/components/schemas/SCIMPlaceholderMergeResult"
+                  }
+                }
+              },
+              "description": "Successful Response"
+            },
+            "422": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "$ref": "#/components/schemas/HTTPValidationError"
+                  }
+                }
+              },
+              "description": "Validation Error"
+            }
+          },
+          "security": [
+            {
+              "APIKeyHeader": []
+            }
+          ],
+          "summary": "Merge Placeholder",
+          "tags": [
+            "scim"
+          ]
+        }
       }
     }
   },
diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py
index e0a2097919b..18714256a8f 100644
--- a/litellm/proxy/_types.py
+++ b/litellm/proxy/_types.py
@@ -1216,6 +1216,13 @@ class GenerateKeyRequest(KeyRequestBase):
     organization_id: str | None = None
     project_id: str | None = None
 
+    @field_validator("team_id", mode="before")
+    @classmethod
+    def treat_cleared_team_id_as_unset(cls, v: object) -> object:
+        if v == "":
+            return None
+        return v
+
 
 class GenerateKeyResponse(KeyRequestBase):
     key: str
diff --git a/litellm/proxy/agent_endpoints/a2a_endpoints.py b/litellm/proxy/agent_endpoints/a2a_endpoints.py
index 31b05320cd3..28882484db4 100644
--- a/litellm/proxy/agent_endpoints/a2a_endpoints.py
+++ b/litellm/proxy/agent_endpoints/a2a_endpoints.py
@@ -1019,4 +1019,6 @@ async def invoke_agent_a2a(
             )
         except Exception:
             pass
+        if isinstance(e, litellm.BadRequestError):
+            return _jsonrpc_error(body.get("id"), -32602, e.message, 400)
         return _jsonrpc_error(body.get("id"), -32603, f"Internal error: {e}", 500)
diff --git a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
new file mode 100644
index 00000000000..7da5e5099fc
--- /dev/null
+++ b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
@@ -0,0 +1,174 @@
+"""
+Restamp the public ``model`` on the Anthropic Messages ``message_start`` event, the only
+stream event carrying a model, so streamed responses report the requested model like
+non-streaming ones do.
+
+Chunks reach the serializer either as already-encoded SSE frames (``bytes``/``str``, the
+provider passthrough path) or as event dicts (fake-stream and agentic paths).
+"""
+
+import json
+import re
+from collections.abc import Mapping
+from typing import Final
+
+from pydantic import TypeAdapter, ValidationError
+
+_MESSAGE_START_EVENT: Final = "message_start"
+_MESSAGE_START_MARKER: Final = b"message_start"
+_SSE_DATA_FIELD: Final = "data:"
+_SSE_FRAME_END_PATTERN: Final = re.compile(rb"\r\n\r\n|\r\r|\n\n")
+_MAX_HELD_BYTES: Final = 65536
+_PING_MARKERS: Final = (b"event: ping", b'"type": "ping"', b'"type":"ping"')
+
+_EVENT_ADAPTER: Final = TypeAdapter(Mapping[str, object])
+
+
+def _restamped_event(event: Mapping[str, object], requested_model: str) -> Mapping[str, object] | None:
+    message: Final = event.get("message")
+    if event.get("type") != _MESSAGE_START_EVENT or not isinstance(message, dict):
+        return None
+    if message.get("model") == requested_model:
+        return None
+    return {**event, "message": {**message, "model": requested_model}}  # mutable-ok: SSE payload, re-serialized as is
+
+
+def _restamped_data_line(line: str, requested_model: str) -> str | None:
+    stripped: Final = line.strip()
+    if not stripped.startswith(_SSE_DATA_FIELD):
+        return None
+    payload: Final = stripped[len(_SSE_DATA_FIELD) :].strip()
+    if not payload or payload == "[DONE]":
+        return None
+    try:
+        event: Final = _EVENT_ADAPTER.validate_json(payload)
+    except ValidationError:
+        return None
+    restamped: Final = _restamped_event(event, requested_model)
+    if restamped is None:
+        return None
+    terminator: Final = line[len(line.rstrip("\r\n")) :]
+    return f"data: {json.dumps(restamped, separators=(',', ':'))}{terminator}"
+
+
+def _restamped_frame(frame: str, requested_model: str) -> str | None:
+    lines: Final = frame.splitlines(keepends=True)
+    restamped: Final = tuple(_restamped_data_line(line, requested_model) for line in lines)
+    if all(line is None for line in restamped):
+        return None
+    return "".join(new if new is not None else old for new, old in zip(restamped, lines))
+
+
+def restamp_anthropic_stream_chunk_model(chunk: object, requested_model: str) -> object:
+    """
+    Return ``chunk`` with the ``message_start`` model replaced by ``requested_model``.
+
+    Chunks that carry no model are returned unchanged.
+    """
+    if isinstance(chunk, dict):
+        try:
+            event: Final = _EVENT_ADAPTER.validate_python(chunk)
+        except ValidationError:
+            return chunk
+        return _restamped_event(event, requested_model) or chunk
+
+    if isinstance(chunk, (bytes, bytearray)):
+        if _MESSAGE_START_EVENT.encode() not in chunk:
+            return chunk
+        restamped_bytes: Final = _restamped_frame(chunk.decode("utf-8", errors="ignore"), requested_model)
+        return chunk if restamped_bytes is None else restamped_bytes.encode("utf-8")
+
+    if isinstance(chunk, str):
+        if _MESSAGE_START_EVENT not in chunk:
+            return chunk
+        restamped_text: Final = _restamped_frame(chunk, requested_model)
+        return chunk if restamped_text is None else restamped_text
+
+    return chunk
+
+
+def _is_ping_frame(frame: bytes) -> bool:
+    return any(marker in frame for marker in _PING_MARKERS)
+
+
+class AnthropicStreamModelRestamper:
+    """
+    Per-stream restamper for the encoded passthrough path, where chunks are raw
+    transport reads: the ``message_start`` SSE frame can arrive split across
+    chunks or coalesced with later frames. Complete frames (``\\n\\n``,
+    ``\\r\\n\\r\\n``, or ``\\r\\r`` terminated) are emitted as their terminator
+    closes them and an incomplete tail is held until it completes, so the
+    restamp never misses a torn frame; ``flush`` returns whatever is still held
+    when the stream ends so no bytes are swallowed. Once ``message_start`` has
+    been handled, or the first real event proves the stream carries none, every
+    later chunk passes through untouched.
+    """
+
+    def __init__(self, requested_model: str) -> None:
+        self._requested_model: Final = requested_model
+        self._held = b""
+        self._armed = True
+
+    def process(self, chunk: object) -> object:
+        if not self._armed:
+            return chunk
+        if isinstance(chunk, (bytes, bytearray)):
+            return self._process_encoded(bytes(chunk))
+        if isinstance(chunk, str):
+            return self._process_encoded(chunk.encode("utf-8"))
+        restamped: Final = restamp_anthropic_stream_chunk_model(chunk, self._requested_model)
+        if isinstance(chunk, dict) and chunk.get("type") not in (None, "ping"):
+            self._armed = False
+        return restamped
+
+    def flush(self) -> bytes:
+        held: Final = self._held
+        self._held = b""
+        self._armed = False
+        if not held:
+            return b""
+        restamped: Final = restamp_anthropic_stream_chunk_model(held, self._requested_model)
+        return restamped if isinstance(restamped, bytes) else held
+
+    def _process_encoded(self, data: bytes) -> bytes:
+        combined: Final = self._held + data
+        boundaries: Final = tuple(match.end() for match in _SSE_FRAME_END_PATTERN.finditer(combined))
+        if not boundaries:
+            if len(combined) > _MAX_HELD_BYTES:
+                self._held = b""
+                self._armed = False
+                return combined
+            self._held = combined
+            return b""
+        emitted: Final = self._restamped_closed_block(combined[: boundaries[-1]])
+        tail: Final = combined[boundaries[-1] :]
+        if not self._armed:
+            self._held = b""
+            return emitted + tail
+        self._held = tail
+        return emitted
+
+    def _restamped_closed_block(self, closed: bytes) -> bytes:
+        boundaries: Final = tuple(match.end() for match in _SSE_FRAME_END_PATTERN.finditer(closed))
+        frames: Final = tuple(closed[start:end] for start, end in zip((0, *boundaries[:-1]), boundaries))
+        decider: Final = next(
+            (
+                index
+                for index, frame in enumerate(frames)
+                if _MESSAGE_START_MARKER in frame or (b"data:" in frame and not _is_ping_frame(frame))
+            ),
+            None,
+        )
+        if decider is None:
+            return closed
+        self._armed = False
+        if _MESSAGE_START_MARKER not in frames[decider]:
+            return closed
+        restamped_text: Final = _restamped_frame(
+            frames[decider].decode("utf-8", errors="ignore"), self._requested_model
+        )
+        if restamped_text is None:
+            return closed
+        return b"".join(
+            restamped_text.encode("utf-8") if index == decider else frame for index, frame in enumerate(frames)
+        )
diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py
index 1d860b02875..05ddef822f1 100644
--- a/litellm/proxy/common_request_processing.py
+++ b/litellm/proxy/common_request_processing.py
@@ -176,6 +176,9 @@ if TYPE_CHECKING:
     ProxyConfig = _ProxyConfig
 else:
     ProxyConfig = Any
+from litellm.proxy.anthropic_endpoints.streaming_model_restamp import (
+    AnthropicStreamModelRestamper,
+)
 from litellm.proxy.litellm_pre_call_utils import (
     add_litellm_data_to_request,
     refresh_proxy_server_request_body_snapshot,
@@ -2490,6 +2493,9 @@ class ProxyBaseLLMRequestProcessing:
                             request_data=self.data,
                             proxy_logging_obj=proxy_logging_obj,
                             request=request,
+                            restamp_model=(
+                                None if _should_return_raw_model_name(self.data) else requested_model_from_client
+                            ),
                         )
                         return await create_response(
                             generator=wrap_sse_stream_with_keepalive_pings(
@@ -3442,6 +3448,16 @@ class ProxyBaseLLMRequestProcessing:
         else:
             return chunk
 
+    @staticmethod
+    def _sse_chunk_serializer(restamper: AnthropicStreamModelRestamper | None) -> StreamChunkSerializer:
+        if restamper is None:
+            return ProxyBaseLLMRequestProcessing.return_sse_chunk
+
+        def serialize(chunk: object) -> str:
+            return ProxyBaseLLMRequestProcessing.return_sse_chunk(restamper.process(chunk))
+
+        return serialize
+
     @staticmethod
     async def _finalize_streaming_generator_cleanup(
         request: Request | None,
@@ -3502,11 +3518,16 @@ class ProxyBaseLLMRequestProcessing:
         serialize_chunk: StreamChunkSerializer,
         serialize_error: StreamErrorSerializer,
         request: Request | None = None,
+        flush_tail: Callable[[], bytes] | None = None,
     ) -> AsyncGenerator[str, None]:
         """
         Shared streaming data generator: runs proxy iterator hook, per-chunk hook,
         cost injection, then yields chunks via serialize_chunk; on exception runs
         failure hook and yields via serialize_error. Use for SSE or NDJSON.
+
+        ``flush_tail`` runs once after the upstream iterator completes cleanly and
+        its non-empty result is yielded, so a serializer that buffers bytes across
+        chunks can emit anything still held at end of stream.
         """
         verbose_proxy_logger.debug("inside generator")
         # Resolve per-stream (not per-chunk) whether the heavy per-chunk path
@@ -3569,6 +3590,9 @@ class ProxyBaseLLMRequestProcessing:
                 # so it must not suppress that refund.
                 delivered_chunk = delivered_chunk or chunk != STREAM_SSE_KEEPALIVE_PING_BYTES
                 yield serialize_chunk(chunk)
+            held_tail: Final = flush_tail() if flush_tail is not None else b""
+            if held_tail:
+                yield serialize_chunk(held_tail)
             stream_completed = True
         except (asyncio.CancelledError, GeneratorExit):
             # Client disconnected mid-stream. CancelledError / GeneratorExit
@@ -3579,8 +3603,7 @@ class ProxyBaseLLMRequestProcessing:
             # billing and release exactly once. This is the outermost generator
             # Starlette closes on disconnect, so the nested iterator hook (which
             # only sees GeneratorExit on GC) cannot own the refund.
-            if not stream_completed:
-                client_disconnected = True
+            client_disconnected = not stream_completed
             if not delivered_chunk and not _withheld_provider_output(response):
                 from litellm.proxy.spend_tracking.budget_reservation import (
                     release_budget_reservation_on_cancel,
@@ -3634,6 +3657,7 @@ class ProxyBaseLLMRequestProcessing:
         request_data: dict,
         proxy_logging_obj: ProxyLogging,
         request: Request | None = None,
+        restamp_model: str | None = None,
     ) -> AsyncGenerator[str, None]:
         """
         Anthropic /messages and Google /generateContent streaming data generator require SSE events.
@@ -3642,17 +3666,23 @@ class ProxyBaseLLMRequestProcessing:
         SSE serializers directly (rather than re-wrapping it in another
         ``async for: yield`` trampoline), so a streamed chunk traverses one
         fewer async-generator layer / coroutine resume on the hot path.
+
+        ``restamp_model`` publishes that name on the Anthropic ``message_start``
+        event in place of the provider's model, matching what the non-streaming
+        response reports.
         """
+        restamper: Final = AnthropicStreamModelRestamper(restamp_model) if restamp_model else None
         return ProxyBaseLLMRequestProcessing.async_streaming_data_generator(
             response=response,
             user_api_key_dict=user_api_key_dict,
             request_data=request_data,
             proxy_logging_obj=proxy_logging_obj,
-            serialize_chunk=ProxyBaseLLMRequestProcessing.return_sse_chunk,
+            serialize_chunk=ProxyBaseLLMRequestProcessing._sse_chunk_serializer(restamper),
             serialize_error=lambda proxy_exc: (
                 f"{STREAM_SSE_DATA_PREFIX}{json.dumps({'error': proxy_exc.to_dict()})}\n\n"
             ),
             request=request,
+            flush_tail=None if restamper is None else restamper.flush,
         )
 
     @overload
diff --git a/litellm/proxy/common_utils/model_listing_utils.py b/litellm/proxy/common_utils/model_listing_utils.py
index 9fd24162f7e..213a697b3dd 100644
--- a/litellm/proxy/common_utils/model_listing_utils.py
+++ b/litellm/proxy/common_utils/model_listing_utils.py
@@ -10,13 +10,36 @@ legacy internal names with `general_settings.use_team_public_model_name: false`.
 
 from __future__ import annotations
 
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Final, cast
 
 if TYPE_CHECKING:
     from litellm.router import Router
 
 
+def configured_display_names(
+    entries: Sequence[tuple[str, str]],
+    llm_router: Router | None,
+) -> Mapping[str, str]:
+    """response_id -> configured `model_info.display_name` for the listing entries
+    that have one.
+
+    Metadata is looked up by each entry's internal lookup id (so team-scoped rows
+    resolve), while the returned map is keyed by the public response id the
+    Anthropic-shaped listing is built from. Entries without a configured name are
+    omitted so the listing falls back to the id itself.
+    """
+    if llm_router is None:
+        return MappingProxyType({})
+    resolved: Final = (
+        (response_id, llm_router.get_configured_display_name(lookup_id)) for response_id, lookup_id in entries
+    )
+    return MappingProxyType(
+        {response_id: display_name for response_id, display_name in resolved if display_name is not None}
+    )
+
+
 class TeamModelNameTranslator:
     """Translates internal team routing keys to their public names for the model
     listing/retrieve responses. Stateless; the live router and general_settings
diff --git a/litellm/proxy/container_endpoints/endpoints.py b/litellm/proxy/container_endpoints/endpoints.py
index 4a088140725..eaa3db336a9 100644
--- a/litellm/proxy/container_endpoints/endpoints.py
+++ b/litellm/proxy/container_endpoints/endpoints.py
@@ -208,7 +208,7 @@ async def list_containers(
 
     # Read query parameters
     query_params: Final = dict(request.query_params)
-    data: Final[dict[str, Any]] = {"query_params": query_params}
+    data: Final[dict[str, Any]] = {"query_params": query_params, "model": query_params.get("model")}
 
     # Extract custom_llm_provider using priority chain
     custom_llm_provider: Final = (
diff --git a/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py b/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py
index d8c8c2f4974..fc881a60f43 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py
@@ -10,6 +10,7 @@ from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, TypeGuard
 import httpx
 from fastapi import HTTPException
 from httpx import Response as HttpxResponse
+from pydantic import TypeAdapter
 
 import litellm
 from litellm._logging import verbose_proxy_logger
@@ -52,6 +53,10 @@ BYPASS_HEADER: Final = "x-headroom-bypass"
 HEADROOM_RETRIEVE_TOOL_NAME: Final = "headroom_retrieve"
 _HASH_PATTERN: Final = re.compile(r"hash=([a-f0-9]{24})")
 _HASH_CACHE_TTL_SECONDS: Final = 15 * 60
+# Narrows the base class's bare-dict ``request_data`` at the boundary so its
+# untranslated messages can be read with concrete types (values pass through by
+# reference, so this is a shallow top-level reconstruction).
+_REQUEST_DATA_ADAPTER: Final = TypeAdapter(dict[str, object])
 
 
 def _is_str_object_dict(value: object) -> TypeGuard[dict[str, object]]:  # guard-ok: isinstance narrows correctly; predicate is trivially correct  # fmt: skip
@@ -116,16 +121,119 @@ def _restore_content_shapes(
     return restored
 
 
-def _protected_indices(messages: Sequence[Mapping[str, object]]) -> frozenset[int]:
+def _tool_call_name(tool_call: Mapping[str, object]) -> str | None:
+    function: Final = tool_call.get("function")
+    if not _is_str_object_dict(function):
+        return None
+    name: Final = function.get("name")
+    return name if isinstance(name, str) else None
+
+
+def _is_retrieve_tool_name(name: str | None) -> bool:
+    """Match the retrieve tool whether called directly or via the MCP gateway.
+
+    Server-side the tool is ``headroom_retrieve``; exposed through LiteLLM's MCP
+    gateway a client calls it as ``mcp__<server>__headroom_retrieve``.
+    """
+    return name is not None and (
+        name == HEADROOM_RETRIEVE_TOOL_NAME or name.endswith(f"__{HEADROOM_RETRIEVE_TOOL_NAME}")
+    )
+
+
+def _retrieve_call_ids_in_message(message: Mapping[str, object]) -> frozenset[str]:
+    if message.get("role") != "assistant":
+        return frozenset()
+    tool_calls: Final = message.get("tool_calls")
+    if not _is_object_list(tool_calls):
+        return frozenset()
+    return frozenset(
+        str(tool_call["id"])
+        for tool_call in tool_calls
+        if _is_str_object_dict(tool_call) and tool_call.get("id") and _is_retrieve_tool_name(_tool_call_name(tool_call))
+    )
+
+
+def _anthropic_tool_use_retrieve_id(block: object) -> str | None:
+    if not _is_str_object_dict(block) or block.get("type") != "tool_use":
+        return None
+    name: Final = block.get("name")
+    call_id: Final = block.get("id")
+    if isinstance(name, str) and call_id is not None and _is_retrieve_tool_name(name):
+        return str(call_id)
+    return None
+
+
+def _anthropic_retrieve_ids_in_message(message: Mapping[str, object]) -> frozenset[str]:
+    content: Final = message.get("content")
+    if not _is_object_list(content):
+        return frozenset()
+    return frozenset(call_id for block in content if (call_id := _anthropic_tool_use_retrieve_id(block)) is not None)
+
+
+def _raw_retrieve_call_ids(messages: object) -> frozenset[str]:
+    """Retrieve-tool call ids read from the request's own, untranslated messages.
+
+    The guardrail otherwise scans an OpenAI-translated view where a tool name
+    over 64 chars is truncated to ``{prefix}_{hash}``, which drops the
+    ``__headroom_retrieve`` suffix a long ``mcp__<server>__`` prefix pushes past
+    the limit. Tool-call ids are never truncated, so pairing the tool result to
+    an id read from the original request keeps the match intact. Both wire
+    shapes are handled: OpenAI ``tool_calls`` and Anthropic ``tool_use`` blocks.
+    """
+    if not _is_object_list(messages):
+        return frozenset()
+    return frozenset(
+        call_id
+        for message in messages
+        if _is_str_object_dict(message)
+        for call_id in _retrieve_call_ids_in_message(message) | _anthropic_retrieve_ids_in_message(message)
+    )
+
+
+def _retrieval_result_indices(
+    messages: Sequence[Mapping[str, object]], extra_retrieve_call_ids: frozenset[str] = frozenset()
+) -> frozenset[int]:
+    """Indices of tool-result rows that carry ``headroom_retrieve`` output.
+
+    When the retrieve tool is exposed to a client that runs its own tool loop
+    (the LiteLLM MCP gateway path), the client executes the call and sends the
+    recovered original content back as a tool result on the next turn. That
+    content is exactly what a prior compression stubbed, so compressing it again
+    re-derives the identical content hash: a no-op that strands the model on the
+    marker and loops the agent. Hold those rows back so the expansion survives.
+
+    ``extra_retrieve_call_ids`` carries ids recovered from the untruncated
+    request so the pairing survives tool-name truncation (see
+    ``_raw_retrieve_call_ids``).
+    """
+    retrieve_call_ids: Final = extra_retrieve_call_ids | frozenset(
+        call_id for message in messages for call_id in _retrieve_call_ids_in_message(message)
+    )
+    if not retrieve_call_ids:
+        return frozenset()
+    return frozenset(
+        index
+        for index, message in enumerate(messages)
+        if message.get("role") in ("tool", "function") and str(message.get("tool_call_id")) in retrieve_call_ids
+    )
+
+
+def _protected_indices(
+    messages: Sequence[Mapping[str, object]], extra_retrieve_call_ids: frozenset[str] = frozenset()
+) -> frozenset[int]:
     """Indices headroom must not send to the compression service.
 
     ``get_protected_indices`` is litellm's own compression policy: the system
-    rows, the last user row, the last assistant row. It is expanded over whole
+    rows, the last user row, the last assistant row. Rows carrying just-retrieved
+    ``headroom_retrieve`` output are added so re-compression can't collapse them
+    back to the marker they were expanded from. The union is expanded over whole
     tool exchanges the way ``compress()`` expands it, so a protected assistant
     tool call cannot end up answered by a marker standing in for the result the
     model just asked for.
     """
-    protected: Final = frozenset(get_protected_indices(messages))
+    protected: Final = frozenset(get_protected_indices(messages)) | _retrieval_result_indices(
+        messages, extra_retrieve_call_ids
+    )
     return protected | frozenset(
         index
         for group in group_tool_exchanges(messages)
@@ -634,7 +742,11 @@ class HeadroomGuardrail(CustomGuardrail):
         # /v1/compress grows a field for sending the live turn as the retrieval
         # query without compressing it: query-aware compression reads the newest
         # user message, so it is withheld here at some cost to history ranking.
-        protected_indices: Final = _protected_indices(messages)
+        # request_data is a bare dict on the base signature; narrow it before
+        # reading the untranslated messages so long tool names can be recovered.
+        raw_messages: Final = _REQUEST_DATA_ADAPTER.validate_python(request_data).get("messages")
+        raw_retrieve_call_ids: Final = _raw_retrieve_call_ids(raw_messages)
+        protected_indices: Final = _protected_indices(messages, raw_retrieve_call_ids)
         compressible: Final = [m for i, m in enumerate(messages) if i not in protected_indices]
         if not compressible:
             return inputs
diff --git a/litellm/proxy/hooks/model_max_budget_limiter.py b/litellm/proxy/hooks/model_max_budget_limiter.py
index c5d10b2749b..efaaab277a9 100644
--- a/litellm/proxy/hooks/model_max_budget_limiter.py
+++ b/litellm/proxy/hooks/model_max_budget_limiter.py
@@ -1,6 +1,6 @@
 import json
 import time
-from collections.abc import Iterable, Mapping
+from collections.abc import Iterable, Mapping, Sequence
 from dataclasses import dataclass
 from types import MappingProxyType
 from typing import Final
@@ -199,18 +199,10 @@ async def build_model_max_budget_usage(
         )
         for budget_model, budget_config in budgets
     )
-    batched: Final = await cache.async_batch_get_cache(
-        keys=list(spend_keys)  # mutable-ok: async_batch_get_cache annotates keys as list, so one must exist here
-    )
-    # async_batch_get_cache returns None if it fails internally, and its result is
-    # index-aligned with `keys` otherwise. An unusable result reads as a miss,
-    # which is what a never-written counter already reads as.
-    current_spends: Final = (
-        tuple(batched) if isinstance(batched, list) and len(batched) == len(budgets) else (None,) * len(budgets)
-    )
+    current_spends: Final = await _current_window_spends(cache=cache, spend_keys=spend_keys)
     return {
         budget_model: {
-            "current_spend": round(_as_spend(current_spend), 4),
+            "current_spend": round(current_spend, 4),
             "budget_limit": budget_config.max_budget,
             "time_period": budget_config.budget_duration,
         }
@@ -218,6 +210,22 @@ async def build_model_max_budget_usage(
     }
 
 
+async def _current_window_spends(cache: DualCache, spend_keys: Sequence[str]) -> tuple[float, ...]:
+    """Redis holds the window total across replicas; the in-memory copy is one replica's share."""
+    keys: Final = list(spend_keys)  # mutable-ok: both batch readers annotate their key argument as list
+    redis_cache: Final = cache.redis_cache
+    if redis_cache is not None:
+        shared: Final = await redis_cache.async_batch_get_cache(key_list=keys)
+        return tuple(_as_spend(shared.get(key)) for key in keys)
+    # async_batch_get_cache returns None if it fails internally, and its result is
+    # index-aligned with `keys` otherwise. An unusable result reads as a miss,
+    # which is what a never-written counter already reads as.
+    batched: Final = await cache.async_batch_get_cache(keys=keys)
+    if not isinstance(batched, list) or len(batched) != len(keys):
+        return (0.0,) * len(keys)
+    return tuple(_as_spend(current_spend) for current_spend in batched)
+
+
 def _usable_budget_config(raw_budget_config: object) -> BudgetConfig | None:
     try:
         budget_config: Final = BudgetConfig.model_validate(raw_budget_config)
@@ -404,7 +412,10 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting):
         return current_spend + _as_spend(await self._cached_spend(legacy_spend_key))
 
     async def _cached_spend(self, spend_key: str) -> float | None:
-        return await self.dual_cache.async_get_cache(key=spend_key)
+        redis_cache: Final = self.dual_cache.redis_cache
+        if redis_cache is None:
+            return await self.dual_cache.async_get_cache(key=spend_key)
+        return await redis_cache.async_get_cache(key=spend_key)
 
     async def async_filter_deployments(
         self,
diff --git a/litellm/proxy/management_endpoints/scim/scim_v2.py b/litellm/proxy/management_endpoints/scim/scim_v2.py
index ded57815e91..069f86c852c 100644
--- a/litellm/proxy/management_endpoints/scim/scim_v2.py
+++ b/litellm/proxy/management_endpoints/scim/scim_v2.py
@@ -29,6 +29,7 @@ import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm._uuid import uuid
 from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+from litellm.models.user import SCIMPlaceholder
 from litellm.proxy._types import (
     LiteLLM_TeamTable,
     LiteLLM_UserTable,
@@ -585,6 +586,37 @@ async def _users_named_by_member_value(
     return tuple(dict.fromkeys(row.user_id for row in rows))
 
 
+async def _accounts_named_by_member_value(value: str, prisma_client: PrismaClient) -> tuple[str, ...]:
+    """Every user id this member value names, by user id, SSO identity or email.
+
+    Classification needs to know whether the value is one account's ``user_id`` and
+    whether it names any other account, so all three fields are read in one pass. The
+    id is compared exactly and unstripped, as a primary key lookup would; the
+    identities compare as ``_users_named_by_member_value`` describes. Two rows are
+    enough to tell one account from several, so the read stops there. Only a full
+    read that lacks the row keyed by the value leaves that row's existence open, and
+    only then is the id read on its own.
+    """
+    subject: Final = value.strip()
+    email: Final[_CaseInsensitiveMatch] = {"equals": subject, "mode": "insensitive"}
+    users: Final = _table(UserRepository(prisma_client))
+    rows: Final = await users.find_many(
+        where={  # mutable-ok: Prisma filter
+            "OR": [  # mutable-ok: Prisma filter
+                {"user_id": value},  # mutable-ok: Prisma filter
+                {"sso_user_id": subject},  # mutable-ok: Prisma filter
+                {"user_email": email},  # mutable-ok: Prisma filter
+            ],
+        },
+        take=2,
+    )
+    named: Final = tuple(dict.fromkeys(row.user_id for row in rows))
+    if len(named) < 2 or value in named:
+        return named
+    keyed: Final = await users.find_unique(where={"user_id": value})
+    return named if keyed is None else (value, *named)
+
+
 async def _classify_group_member(member: SCIMMember, prisma_client: PrismaClient) -> _ClassifiedGroupMember:
     """
     Decide what a single SCIM group member refers to.
@@ -627,11 +659,9 @@ async def _classify_group_member(member: SCIMMember, prisma_client: PrismaClient
     if member_type == "group":
         return _SkippedGroupMember(value=value, reason="nested_group")
 
-    user: Final = await _table(UserRepository(prisma_client)).find_unique(where={"user_id": value})
-    if user is not None:
-        shared_with: Final = tuple(
-            other for other in await _users_named_by_member_value(value, prisma_client) if other != value
-        )
+    named: Final = await _accounts_named_by_member_value(value, prisma_client)
+    if value in named:
+        shared_with: Final = tuple(other for other in named if other != value)
         if shared_with:
             verbose_proxy_logger.warning(
                 "SCIM: group member '%s' is one account's user id and is also account '%s' by SSO identity or email, "
@@ -651,7 +681,6 @@ async def _classify_group_member(member: SCIMMember, prisma_client: PrismaClient
         if team is not None and _team_metadata_has_scim_provenance(team.metadata):
             return _SkippedGroupMember(value=value, reason="existing_team")
 
-    named: Final = await _users_named_by_member_value(value, prisma_client)
     if len(named) == 1:
         verbose_proxy_logger.info(
             "SCIM: group member '%s' matched user_id '%s' by SSO identity or email",
@@ -1834,6 +1863,89 @@ async def delete_user(
         raise handle_exception_on_proxy(e)
 
 
+@scim_router.get(
+    "/placeholders",
+    response_model=tuple[SCIMPlaceholder, ...],
+    dependencies=(Depends(user_api_key_auth),),
+)
+async def list_placeholders() -> tuple[SCIMPlaceholder, ...]:
+    """
+    List user rows whose id is another account's SSO identity or email.
+
+    An earlier release provisioned a group member it could not match as a user keyed
+    by the raw member value, and that row now shadows the account the value really
+    names, so every push of that member is refused. This lists those rows so an
+    operator can fold each one into the account it shadows with
+    ``POST /scim/v2/placeholders/{user_id}/merge``. A row that has an SSO identity of
+    its own or owns virtual keys is left out: someone uses that account.
+    """
+    try:
+        prisma_client: Final = await _get_prisma_client_or_raise_exception()
+        async with prisma_client.tx() as tx:
+            return await UserRepository(prisma_client).find_shadowing_placeholders(tx)
+    except Exception as e:
+        raise handle_exception_on_proxy(e)
+
+
+def _placeholder_rejection(placeholder: LiteLLM_UserTable, resolved: tuple[str, ...], key_count: int) -> str | None:
+    if placeholder.sso_user_id is not None:
+        return f"User '{placeholder.user_id}' has an SSO identity of its own, so it is an account someone signs in to"
+    if key_count:
+        return f"User '{placeholder.user_id}' owns {key_count} virtual keys. Move or delete them before merging it"
+    if not resolved:
+        return f"User '{placeholder.user_id}' shadows no account: no other user has that id as SSO identity or email"
+    if len(resolved) > 1:
+        return (
+            f"User '{placeholder.user_id}' names {len(resolved)} accounts ({', '.join(resolved)}). Resolve that first"
+        )
+    return None
+
+
+@scim_router.post(
+    "/placeholders/{user_id}/merge",
+    response_model=SCIMPlaceholderMergeResult,
+    dependencies=(Depends(user_api_key_auth),),
+)
+async def merge_placeholder(
+    user_id: str = Path(..., title="User ID"),
+) -> SCIMPlaceholderMergeResult:
+    """
+    Fold a placeholder user into the one account its id names by SSO identity or email.
+
+    The account is added to every team the placeholder is on, then the placeholder is
+    deleted the way ``DELETE /scim/v2/Users/{id}`` deletes a user, so the next group
+    push resolves the member value to the real account. Refused with 409 when the row
+    has an SSO identity of its own, owns virtual keys, or names no account or several.
+    """
+    try:
+        prisma_client: Final = await _get_prisma_client_or_raise_exception()
+        placeholder: Final = await _check_user_exists(user_id)
+        resolved: Final = tuple(
+            other for other in await _users_named_by_member_value(user_id, prisma_client, take=None) if other != user_id
+        )
+        owned_keys: Final[_UserIdWhere] = {"user_id": user_id}
+        keys: Final = await _table(VerificationTokenRepository(prisma_client)).find_many(where=owned_keys)
+        rejection: Final = _placeholder_rejection(placeholder, resolved, len(keys))
+        if rejection is not None:
+            detail: Final[_ScimErrorDetail] = {"error": rejection}
+            raise HTTPException(status_code=409, detail=detail)
+
+        target_user_id: Final = resolved[0]
+        team_ids: Final = tuple(placeholder.teams)
+        for team_id in team_ids:
+            await _add_user_to_team(user_id=target_user_id, team_id=team_id)
+        await delete_user(user_id=user_id)
+        await _recompute_scim_member_roles(prisma_client, (target_user_id,))
+        verbose_proxy_logger.info(
+            "SCIM: merged placeholder user '%s' into '%s', moving teams %s", user_id, target_user_id, team_ids
+        )
+        return SCIMPlaceholderMergeResult(
+            placeholder_user_id=user_id, merged_into_user_id=target_user_id, team_ids=team_ids
+        )
+    except Exception as e:
+        raise handle_exception_on_proxy(e)
+
+
 def _parse_member_entry(entry: object) -> SCIMMember | None:
     """Parse one entry of a SCIM patch value, or None when it carries no id."""
     if isinstance(entry, str):
diff --git a/litellm/proxy/management_helpers/access_group_key_sync.py b/litellm/proxy/management_helpers/access_group_key_sync.py
index 5d43cb29978..c9f93fae0d9 100644
--- a/litellm/proxy/management_helpers/access_group_key_sync.py
+++ b/litellm/proxy/management_helpers/access_group_key_sync.py
@@ -38,6 +38,7 @@ from litellm.proxy._types import (
 from litellm.proxy.auth.auth_checks import (
     _delete_cache_access_object,  # pyright: ignore[reportPrivateUsage]  # the access-group endpoints reach for this same cache primitive
 )
+from litellm.proxy.db.routing_prisma_wrapper import WriterPinnedClient
 from litellm.repositories.table_repositories import AccessGroupRepository
 
 
@@ -72,8 +73,9 @@ _REPOINT_KEY_SQL: Final = (
 
 
 def _raw_executor(prisma_client: object) -> _RawExecutor:
-    """Narrow the untyped Prisma client down to the raw-query call this module makes."""
-    return AccessGroupRepository(prisma_client).prisma_client.db  # pyright: ignore[reportAny]  # untyped Prisma client
+    """Narrow the untyped Prisma client down to the raw-query call this module makes, pinned to the writer."""
+    db: Final = AccessGroupRepository(prisma_client).prisma_client.db  # pyright: ignore[reportAny]  # untyped Prisma client
+    return WriterPinnedClient(db).db  # pyright: ignore[reportAny, reportReturnType]  # untyped Prisma client behind the pin
 
 
 async def _invalidate_access_group_cache(access_group_id: str) -> None:
diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
index ff306eb65f1..79d5d0a016f 100644
--- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
+++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
@@ -812,6 +812,8 @@ def _resolve_team_callback_wiring(
         else {  # mutable-ok: Logging arg
             **callback_vars,
             TRUSTED_CALLBACK_VARS_FIELD: callback_vars,
+            "metadata": {},  # mutable-ok: Logging arg
+            "model_info": {},  # mutable-ok: Logging arg
         }
     )
     return _TeamCallbackWiring(
diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 77a80ea0052..d52f05f6166 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -39,7 +39,7 @@ from typing import (
 import anyio
 import websockets
 import websockets.exceptions
-from pydantic import BaseModel, Json, JsonValue, ValidationError
+from pydantic import BaseModel, Json, JsonValue, TypeAdapter, ValidationError
 from typing_extensions import NotRequired, ReadOnly, assert_never
 
 from litellm._uuid import uuid
@@ -60,6 +60,7 @@ from litellm.constants import (
     LITELLM_SETTINGS_SAFE_DB_OVERRIDES,
     LITELLM_UI_ALLOW_HEADERS,
     LITELLM_UI_SESSION_DURATION,
+    RUNTIME_UPDATABLE_ROUTER_SETTINGS,
 )
 from litellm.litellm_core_utils.litellm_logging import (
     _init_custom_logger_compatible_class,
@@ -253,6 +254,7 @@ from litellm.constants import (
     PROXY_BUDGET_RESCHEDULER_MAX_TIME,
     PROXY_BUDGET_RESCHEDULER_MIN_TIME,
     PROXY_CONFIG_RELOAD_INTERVAL_SECONDS,
+    ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG,
     USER_SPEND_ALERTS_JOB_ID,
     WEEKLY_SPEND_REPORT_JOB_ID,
 )
@@ -352,7 +354,10 @@ from litellm.proxy.common_utils.load_config_utils import (
     get_file_contents_from_s3,
 )
 from litellm.proxy.common_utils.model_deprecation import collect_model_deprecations
-from litellm.proxy.common_utils.model_listing_utils import TeamModelNameTranslator
+from litellm.proxy.common_utils.model_listing_utils import (
+    TeamModelNameTranslator,
+    configured_display_names,
+)
 from litellm.proxy.common_utils.openai_endpoint_utils import (
     remove_sensitive_info_from_deployment,
 )
@@ -2275,7 +2280,7 @@ user_api_key_cache: UserApiKeyCache = UserApiKeyCache(
 )
 spend_counter_cache: Final = DualCache(default_in_memory_ttl=UserAPIKeyCacheTTLEnum.in_memory_cache_ttl.value)
 cli_sso_session_cache: Final = DualCache(default_in_memory_ttl=CLI_SSO_SESSION_TTL_SECONDS)
-model_max_budget_limiter: Final = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=user_api_key_cache)
+model_max_budget_limiter: Final = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=spend_counter_cache)
 litellm.logging_callback_manager.add_litellm_callback(model_max_budget_limiter)
 redis_usage_cache: RedisCache | None = None  # redis cache used for tracking spend, tpm/rpm limits
 polling_via_cache_enabled: Literal["all"] | list[str] | bool = False
@@ -5710,13 +5715,9 @@ class ProxyConfig:
         router_settings: Final = config.get("router_settings", None)
 
         if router_settings and isinstance(router_settings, dict):
-            # model list and search_tools already set
-            exclude_args: Final = {
-                "model_list",
-                "search_tools",
-            }
-
-            available_args: Final = [x for x in litellm.Router.get_valid_args() if x not in exclude_args]
+            available_args: Final = [
+                x for x in litellm.Router.get_valid_args() if x not in ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG
+            ]
 
             for k, v in router_settings.items():
                 if k in available_args:
@@ -10223,7 +10224,8 @@ async def model_list(
         # The internal routing key drives the metadata/fallback lookup, while the
         # public name is what the client sees as the model id.
         model_data = []
-        for response_id, lookup_id in TeamModelNameTranslator.listing_entries(all_models, llm_router, settings):
+        admin_entries: Final = TeamModelNameTranslator.listing_entries(all_models, llm_router, settings)
+        for response_id, lookup_id in admin_entries:
             model_info = create_model_info_response(
                 model_id=lookup_id,
                 provider="openai",
@@ -10236,7 +10238,10 @@ async def model_list(
 
         if wants_anthropic_format:
             admin_listing: Final = cast(Sequence[ModelInfoResponse], model_data)  # cast-ok: rows built above
-            return create_anthropic_model_list_response(admin_listing)
+            return create_anthropic_model_list_response(
+                admin_listing,
+                display_names=configured_display_names(admin_entries, llm_router),
+            )
 
         return dict(
             data=model_data,
@@ -10267,7 +10272,8 @@ async def model_list(
     # The internal routing key drives the metadata/fallback lookup, while the
     # public name is what the client sees as the model id.
     model_data = []
-    for response_id, lookup_id in TeamModelNameTranslator.listing_entries(all_models, llm_router, settings):
+    entries: Final = TeamModelNameTranslator.listing_entries(all_models, llm_router, settings)
+    for response_id, lookup_id in entries:
         model_info = create_model_info_response(
             model_id=lookup_id,
             provider="openai",
@@ -10280,7 +10286,10 @@ async def model_list(
 
     if wants_anthropic_format:
         listing: Final = cast(Sequence[ModelInfoResponse], model_data)  # cast-ok: rows built above
-        return create_anthropic_model_list_response(listing)
+        return create_anthropic_model_list_response(
+            listing,
+            display_names=configured_display_names(entries, llm_router),
+        )
 
     return dict(
         data=model_data,
@@ -16207,6 +16216,7 @@ async def invitation_delete(
 )
 async def update_config(
     config_info: ConfigYAML,
+    request: Request,
     user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
 ):
     """
@@ -16222,6 +16232,26 @@ async def update_config(
         if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN:
             raise HTTPException(status_code=403, detail="Only proxy admins can update config")
 
+        request_body: Final[Mapping[str, JsonValue]] = TypeAdapter(Mapping[str, JsonValue]).validate_python(
+            await request.json()
+        )
+        raw_router_settings: Final = request_body.get("router_settings")
+        if isinstance(raw_router_settings, dict):
+            supported_router_settings: Final = RUNTIME_UPDATABLE_ROUTER_SETTINGS | (
+                frozenset(litellm.Router.get_valid_args()) - ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG
+            )
+            unsupported_router_settings: Final = sorted(set(raw_router_settings) - supported_router_settings)
+            if unsupported_router_settings:
+                raise HTTPException(
+                    status_code=400,
+                    detail={
+                        "error": (
+                            f"Unsupported router settings: {', '.join(unsupported_router_settings)} "
+                            "are not valid router settings"
+                        )
+                    },
+                )
+
         if prisma_client is None:
             raise Exception("No DB Connected")
 
@@ -16323,11 +16353,19 @@ async def update_config(
             )
 
         # router_settings: merge existing + request, request wins.
-        if config_info.router_settings is not None:
+        if isinstance(raw_router_settings, dict):
             existing = await _read_section("router_settings")
             before_router_settings: Final = copy.deepcopy(existing)
-            updates = config_info.router_settings.dict(exclude_none=True)
-            new_router_settings: Final = {**existing, **updates}
+            typed_router_settings: Final = (
+                config_info.router_settings.dict(exclude_none=True) if config_info.router_settings is not None else {}
+            )
+            raw_router_settings_without_none: Final = {
+                key: value
+                for key, value in raw_router_settings.items()
+                if key not in typed_router_settings and value is not None
+            }
+            router_settings_updates: Final = {**typed_router_settings, **raw_router_settings_without_none}
+            new_router_settings: Final = {**existing, **router_settings_updates}
             await _upsert_section("router_settings", new_router_settings)
             asyncio.create_task(
                 create_config_audit_log(
diff --git a/litellm/proxy/public_endpoints/agent_create_fields.json b/litellm/proxy/public_endpoints/agent_create_fields.json
index 36484cc1065..cc2fc17d759 100644
--- a/litellm/proxy/public_endpoints/agent_create_fields.json
+++ b/litellm/proxy/public_endpoints/agent_create_fields.json
@@ -107,7 +107,9 @@
         "required": true,
         "field_type": "text",
         "default_value": null,
-        "include_in_litellm_params": false
+        "include_in_litellm_params": false,
+        "validation_pattern": "^arn:aws[a-zA-Z0-9-]*:bedrock-agentcore:[a-z0-9-]+:[0-9]{12}:runtime/.+$",
+        "validation_message": "Enter the complete Bedrock AgentCore runtime ARN, including the runtime ID after \"runtime/\" (e.g. arn:aws:bedrock-agentcore:us-west-2:123456789012:runtime/my-agent-runtime)."
       }
     ],
     "litellm_params_template": {
diff --git a/litellm/proxy/rag_endpoints/endpoints.py b/litellm/proxy/rag_endpoints/endpoints.py
index db574f859b3..e144ff965ae 100644
--- a/litellm/proxy/rag_endpoints/endpoints.py
+++ b/litellm/proxy/rag_endpoints/endpoints.py
@@ -9,6 +9,7 @@ Provides:
 import base64
 import json
 from collections.abc import Mapping
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final
 
 import orjson
@@ -19,6 +20,9 @@ from starlette.datastructures import UploadFile
 import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
+from litellm.integrations.vector_store_integrations.vector_store_pre_call_hook import (
+    LiteLLM_ManagedVectorStore,
+)
 from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
 from litellm.proxy._types import *
 from litellm.proxy.auth.auth_utils import is_request_body_safe
@@ -36,6 +40,10 @@ from litellm.proxy.rag_endpoints.upload_security import (
     RejectedUpload,
     validate_upload,
 )
+from litellm.proxy.vector_store_endpoints.endpoints import (
+    build_request_data_from_managed_vector_store,
+    reject_caller_embedding_selection_params,
+)
 from litellm.proxy.vector_store_endpoints.utils import (
     assert_user_can_access_vector_store_id,
 )
@@ -120,12 +128,21 @@ def _collect_vector_store_ids_from_payload(payload: object) -> set[str]:
 async def _authorize_nested_vector_store_ids(
     payload: object,
     user_api_key_dict: UserAPIKeyAuth,
-) -> None:
-    for vector_store_id in sorted(_collect_vector_store_ids_from_payload(payload)):
-        await assert_user_can_access_vector_store_id(
-            vector_store_id=vector_store_id,
-            user_api_key_dict=user_api_key_dict,
-        )
+) -> Mapping[str, LiteLLM_ManagedVectorStore]:
+    """Authorize every nested vector store id and return the managed stores it resolved."""
+    return MappingProxyType(
+        {
+            vector_store_id: store
+            for vector_store_id in sorted(_collect_vector_store_ids_from_payload(payload))
+            if (
+                store := await assert_user_can_access_vector_store_id(
+                    vector_store_id=vector_store_id,
+                    user_api_key_dict=user_api_key_dict,
+                )
+            )
+            is not None
+        }
+    )
 
 
 def _build_file_metadata_entry(
@@ -700,11 +717,27 @@ async def rag_query(
                 status_code=400,
                 detail={"error": "retrieval_config must contain 'vector_store_id'"},
             )
-        await _authorize_nested_vector_store_ids(
+        reject_caller_embedding_selection_params(payload=retrieval_config, source="retrieval_config")
+        resolved_stores: Final = await _authorize_nested_vector_store_ids(
             payload=retrieval_config,
             user_api_key_dict=user_api_key_dict,
         )
 
+        # Merge litellm-managed vector store params (provider, region, embedding
+        # model, credentials, ...) from the registry: the same source the direct
+        # /vector_stores/{id}/search endpoint uses. Store-managed keys win on
+        # conflict so callers cannot override the store's provider or credentials.
+        managed_store: Final = resolved_stores.get(retrieval_config["vector_store_id"])
+        store_data: Final = (
+            build_request_data_from_managed_vector_store(managed_store)
+            if managed_store is not None
+            else MappingProxyType({})
+        )
+        merged_retrieval_config: Final = {
+            **retrieval_config,
+            **store_data,
+        }  # mutable-ok: litellm.aquery requires a plain dict payload
+
         # Add litellm data
         request_data: dict[str, object] = {}
         request_data = await add_litellm_data_to_request(
@@ -716,13 +749,18 @@ async def rag_query(
             proxy_config=proxy_config,
         )
 
-        verbose_proxy_logger.debug("RAG Query - model: %s, retrieval_config: %s", model, retrieval_config)
+        verbose_proxy_logger.debug(
+            "RAG Query - model: %s, vector_store_id: %s, custom_llm_provider: %s",
+            model,
+            retrieval_config["vector_store_id"],
+            merged_retrieval_config.get("custom_llm_provider"),
+        )
 
         # Call query
         response: Final = await litellm.aquery(
             model=model,
             messages=messages,
-            retrieval_config=retrieval_config,
+            retrieval_config=merged_retrieval_config,
             rerank=rerank,
             stream=stream,
             router=llm_router,
diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py
index f4d8fd7d906..91d2ece7a51 100644
--- a/litellm/proxy/spend_tracking/budget_reservation.py
+++ b/litellm/proxy/spend_tracking/budget_reservation.py
@@ -120,13 +120,15 @@ async def _apply_over_budget_reservation_policy(
     applied_entries: list[dict[str, float | str]],
     reservation_cost: float,
     current_spend: float,
+    fail_closed_budget_enforcement: bool = False,
 ) -> float:
     """
     Decide what to do when a counter is over budget, and return the reservation
     cost to carry into the next counter. Three outcomes: an over-budget key that
     opted into throttling releases its own reservation (the rate limiter slows
     it) and keeps the cost; a partially-remaining budget resizes the reservation
-    down to what is left; anything else hard-blocks by raising.
+    down to what is left, unless strict enforcement is on, because the known
+    estimate already does not fit; anything else hard-blocks by raising.
     """
     if _key_reservation_should_release_for_throttle(counter.counter_key, valid_token):
         await _release_applied_entries_best_effort(entries=[entry], default_reserved_cost=reservation_cost)
@@ -134,21 +136,36 @@ async def _apply_over_budget_reservation_policy(
         return reservation_cost
 
     remaining_before_reservation: Final = counter.max_budget - (current_spend - reservation_cost)
-    if remaining_before_reservation > 1e-12:
-        await _resize_applied_reservation(
-            entries=applied_entries,
-            current_reserved_cost=reservation_cost,
-            new_reserved_cost=remaining_before_reservation,
+    if remaining_before_reservation <= 1e-12:
+        _raise_counter_budget_exceeded(counter=counter, current_cost=current_spend)
+    if fail_closed_budget_enforcement and current_spend - counter.max_budget > 1e-12:
+        _raise_counter_budget_exceeded(
+            counter=counter,
+            current_cost=current_spend - reservation_cost,
+            estimated_cost=reservation_cost,
         )
-        return remaining_before_reservation
+    await _resize_applied_reservation(
+        entries=applied_entries,
+        current_reserved_cost=reservation_cost,
+        new_reserved_cost=remaining_before_reservation,
+    )
+    return remaining_before_reservation
 
+
+def _raise_counter_budget_exceeded(
+    counter: _BudgetCounter,
+    current_cost: float,
+    estimated_cost: float | None = None,
+) -> NoReturn:
+    estimate_detail: Final = "" if estimated_cost is None else f"Estimated request cost: {estimated_cost}, "
     raise litellm.BudgetExceededError(
-        current_cost=current_spend,
+        current_cost=current_cost,
         max_budget=counter.max_budget,
         message=(
             "Budget has been exceeded! "
             f"{counter.entity_type}={counter.entity_id} "
-            f"Current cost: {current_spend}, "
+            f"Current cost: {current_cost}, "
+            f"{estimate_detail}"
             f"Max budget: {counter.max_budget}"
         ),
         entity_type=_COUNTER_ENTITY_TYPES.get(counter.entity_type),
@@ -258,6 +275,7 @@ async def reserve_budget_for_request(
                     applied_entries=applied_entries,
                     reservation_cost=reservation_cost,
                     current_spend=current_spend,
+                    fail_closed_budget_enforcement=fail_closed_budget_enforcement,
                 )
                 continue
     except Exception:
diff --git a/litellm/proxy/vector_store_endpoints/endpoints.py b/litellm/proxy/vector_store_endpoints/endpoints.py
index 3fc67181d5b..1feda0b0bb5 100644
--- a/litellm/proxy/vector_store_endpoints/endpoints.py
+++ b/litellm/proxy/vector_store_endpoints/endpoints.py
@@ -1,3 +1,5 @@
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import (
     Annotated,
     Any,  # noqa: TID251  # jsonify_object in proxy/utils.py is annotated with a bare dict
@@ -24,11 +26,48 @@ from litellm.types.vector_stores import IndexCreateRequest, IndexListResponse
 from litellm.vector_stores.vector_store_registry import VectorStoreIndexRegistry
 
 router: Final = APIRouter()
+
+BLOCKED_QUERY_EMBEDDING_SELECTION_PARAMS: Final = frozenset(
+    {
+        "embedding_model",
+        "litellm_embedding_model",
+        "litellm_embedding_config",
+        "litellm_credential_name",
+    }
+)
+
+
+def reject_caller_embedding_selection_params(payload: Mapping[str, object], source: str) -> None:
+    blocked: Final = sorted(BLOCKED_QUERY_EMBEDDING_SELECTION_PARAMS & payload.keys())
+    if blocked:
+        raise HTTPException(
+            status_code=400,
+            detail={
+                "error": f"'{blocked[0]}' cannot be set in {source}. "
+                "Embedding configuration comes from the vector store's server-side registration."
+            },
+        )
+
+
 ########################################################
 # OpenAI Compatible Endpoints
 ########################################################
 
 
+def build_request_data_from_managed_vector_store(
+    vector_store: LiteLLM_ManagedVectorStore,
+) -> Mapping[str, object]:
+    top_level: Final = MappingProxyType(
+        {
+            key: vector_store.get(key)
+            for key in ("custom_llm_provider", "litellm_credential_name")
+            if key in vector_store
+        }
+    )
+    litellm_params: Final = vector_store.get("litellm_params") or MappingProxyType({})
+    return MappingProxyType({**top_level, **litellm_params})
+
+
 async def _update_request_data_with_litellm_managed_vector_store_registry(
     data: dict,
     vector_store_id: str,
@@ -48,25 +87,14 @@ async def _update_request_data_with_litellm_managed_vector_store_registry(
     vector_store_to_run: Final[LiteLLM_ManagedVectorStore | None] = await get_litellm_managed_vector_store(
         vector_store_id=vector_store_id
     )
-    if vector_store_to_run is not None:
-        if user_api_key_dict is not None:
-            await assert_user_can_access_vector_store(
-                vector_store=vector_store_to_run,
-                user_api_key_dict=user_api_key_dict,
-            )
-
-        if "custom_llm_provider" in vector_store_to_run:
-            data["custom_llm_provider"] = vector_store_to_run.get("custom_llm_provider")
-
-        if "litellm_credential_name" in vector_store_to_run:
-            data["litellm_credential_name"] = vector_store_to_run.get("litellm_credential_name")
-
-        if "litellm_params" in vector_store_to_run:
-            litellm_params: Final = (
-                vector_store_to_run.get("litellm_params", {}) or {}
-            )  # mutable-ok: request execution merges persisted params into a mutable body
-            data.update(litellm_params)
-    return data
+    if vector_store_to_run is None:
+        return data
+    if user_api_key_dict is not None:
+        await assert_user_can_access_vector_store(
+            vector_store=vector_store_to_run,
+            user_api_key_dict=user_api_key_dict,
+        )
+    return {**data, **build_request_data_from_managed_vector_store(vector_store_to_run)}
 
 
 @router.post(
@@ -105,6 +133,7 @@ async def vector_store_search(
     )
 
     data = await _read_request_body(request=request)
+    reject_caller_embedding_selection_params(payload=data, source="the search request body")
     data["vector_store_id"] = vector_store_id
 
     # Check for legacy vector store registry (non-managed vector stores)
diff --git a/litellm/proxy/vector_store_endpoints/management_endpoints.py b/litellm/proxy/vector_store_endpoints/management_endpoints.py
index 8ca45f736ae..c928398a87f 100644
--- a/litellm/proxy/vector_store_endpoints/management_endpoints.py
+++ b/litellm/proxy/vector_store_endpoints/management_endpoints.py
@@ -212,10 +212,9 @@ async def create_vector_store_in_db(
     # (``api_key``, ``api_base``, ``api_version``) into this row. That
     # exposed every env-stored embedding-model credential on the
     # ``/vector_store/{new,info,update,list}`` responses. Keep the user's
-    # raw ``litellm_embedding_model`` reference; resolution now happens in
-    # ``_update_request_data_with_litellm_managed_vector_store_registry``
-    # at request-handling time so the cleartext config exists only in
-    # per-request memory and never reaches the database.
+    # raw ``litellm_embedding_model`` reference; each search embeds the
+    # query through the router at request time, so the credentials stay
+    # on the deployment and never reach the database.
     if litellm_params:
         litellm_params_dict: Final = GenericLiteLLMParams(**litellm_params).model_dump(exclude_none=True)
         data_to_create["litellm_params"] = safe_dumps(litellm_params_dict)
@@ -605,11 +604,9 @@ async def update_vector_store(
 
         # Handle litellm_params if provided. As with the create path, the
         # embedding-config auto-resolve previously persisted cleartext
-        # credentials into the row; resolution now happens at request-
-        # handling time in
-        # ``_update_request_data_with_litellm_managed_vector_store_registry``
-        # so this row only ever stores the user-supplied
-        # ``litellm_embedding_model`` reference.
+        # credentials into the row; each search now embeds the query
+        # through the router at request time, so this row only ever stores
+        # the user-supplied ``litellm_embedding_model`` reference.
         if "litellm_params" in update_data:
             _input_litellm_params: Final[dict] = update_data.get("litellm_params", {}) or {}
             litellm_params_dict: Final = GenericLiteLLMParams(**_input_litellm_params).model_dump(exclude_none=True)
diff --git a/litellm/rag/main.py b/litellm/rag/main.py
index 7bc1a6a52a3..94bfc305a6a 100644
--- a/litellm/rag/main.py
+++ b/litellm/rag/main.py
@@ -14,6 +14,7 @@ import contextvars
 from collections.abc import Coroutine, Iterator
 from contextlib import contextmanager
 from functools import partial
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
@@ -50,6 +51,21 @@ INGESTION_REGISTRY: Final[dict[str, type[BaseRAGIngestion]]] = {
     "vertex_ai": VertexAIRAGIngestion,
 }
 
+# Only these retrieval_config keys are forwarded to vector_stores.asearch as
+# provider-specific params. The explicit allowlist keeps caller-controlled
+# connection overrides (api_base, api_key, ...) away from the search call,
+# where they could redirect store credentials to an attacker-chosen host.
+_FORWARDABLE_RETRIEVAL_CONFIG_KEYS: Final = frozenset(
+    {
+        "aws_region_name",
+        "vector_bucket_name",
+        "embedding_model",
+        "litellm_embedding_model",
+        "litellm_embedding_config",
+        "litellm_credential_name",
+    }
+)
+
 
 def get_ingestion_class(provider: str) -> type[BaseRAGIngestion]:
     """
@@ -224,13 +240,20 @@ async def _execute_query_pipeline(
         raise ValueError("No query found in messages for RAG query")
 
     # 2. Search vector store
+    # Forward allowlisted provider retrieval_config extras (region, embedding
+    # model, bucket, credential refs) to the search call; kwargs win on conflict.
+    provider_search_params: Final = MappingProxyType(
+        {k: v for k, v in retrieval_config.items() if k in _FORWARDABLE_RETRIEVAL_CONFIG_KEYS}
+    )
+    forwarded_search_params: Final = MappingProxyType({**provider_search_params, **kwargs})
     with _suppressed_sub_call_billing():
         search_response: Final = await litellm.vector_stores.asearch(
             vector_store_id=retrieval_config["vector_store_id"],
             query=query_text,
             max_num_results=retrieval_config.get("top_k", 10),
             custom_llm_provider=retrieval_config.get("custom_llm_provider", "openai"),
-            **kwargs,
+            router=router,
+            **forwarded_search_params,
         )
 
     search_provider: Final = retrieval_config.get("custom_llm_provider", "openai")
diff --git a/litellm/repositories/user_repository.py b/litellm/repositories/user_repository.py
index 9df1bceac9c..87eb45f262d 100644
--- a/litellm/repositories/user_repository.py
+++ b/litellm/repositories/user_repository.py
@@ -6,15 +6,34 @@ import json
 from collections.abc import Mapping
 from typing import TYPE_CHECKING, Final
 
-from litellm.models.user import LiteLLM_UserTable
+from pydantic import TypeAdapter
+
+from litellm.models.user import LiteLLM_UserTable, SCIMPlaceholder
 from litellm.repositories.base_repository import BaseRepository, DbRecord, record_to_dict
 from litellm.repositories.prisma_protocols import TableActions
 
 if TYPE_CHECKING:
+    from prisma import Prisma
     from prisma import models as prisma_models
 
 _JSON_ENCODED_COLUMNS: Final = frozenset({"metadata", "model_spend", "model_max_budget"})
 
+_SHADOWING_PLACEHOLDERS_SQL: Final = """
+SELECT p.user_id AS placeholder_user_id,
+       array_agg(r.user_id ORDER BY r.user_id) AS resolved_user_ids,
+       p.teams AS team_ids
+FROM "LiteLLM_UserTable" p
+JOIN "LiteLLM_UserTable" r
+  ON r.user_id <> p.user_id
+ AND (r.sso_user_id = p.user_id OR LOWER(r.user_email) = LOWER(p.user_id))
+WHERE p.sso_user_id IS NULL
+  AND NOT EXISTS (SELECT 1 FROM "LiteLLM_VerificationToken" k WHERE k.user_id = p.user_id)
+GROUP BY p.user_id, p.teams
+ORDER BY p.user_id
+"""
+
+_PLACEHOLDER_ROWS_ADAPTER: Final = TypeAdapter(tuple[SCIMPlaceholder, ...])
+
 
 class UserRepository(BaseRepository[LiteLLM_UserTable]):
     """Repository for user database operations."""
@@ -59,6 +78,11 @@ class UserRepository(BaseRepository[LiteLLM_UserTable]):
         """Find all users in a team."""
         return await self.find_many(where={"teams": {"has": team_id}})
 
+    async def find_shadowing_placeholders(self, tx: "Prisma") -> tuple[SCIMPlaceholder, ...]:
+        """Users with no SSO id and no virtual keys whose id is another user's SSO id or email."""
+        rows: Final = await tx.query_raw(_SHADOWING_PLACEHOLDERS_SQL)
+        return _PLACEHOLDER_ROWS_ADAPTER.validate_python(rows)
+
     async def count_billable_users(self) -> int:
         """Number of users that count toward the license seat limit.
 
diff --git a/litellm/rerank_api/main.py b/litellm/rerank_api/main.py
index c8f7842aebf..37ca989b8d3 100644
--- a/litellm/rerank_api/main.py
+++ b/litellm/rerank_api/main.py
@@ -6,6 +6,7 @@ from typing import Any, Final, Literal
 
 import litellm
 from litellm._logging import verbose_logger
+from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
 from litellm.llms.bedrock.rerank.handler import BedrockRerankHandler
@@ -43,10 +44,23 @@ async def arerank(
     """
     Async: Reranks a list of documents based on their relevance to the query
     """
+    _custom_llm_provider: str | None = (
+        None  # rebind-ok: set by the declared-provider guard or the get_llm_provider unpack; read in the except
+    )
     try:
         loop: Final = asyncio.get_event_loop()
         kwargs["arerank"] = True
 
+        declared_provider: Final = declared_authenticating_provider(model, custom_llm_provider)
+        if declared_provider is not None:
+            _custom_llm_provider = declared_provider  # rebind-ok: see pre-declaration above
+        else:
+            _, _custom_llm_provider, _, _ = litellm.get_llm_provider(  # rebind-ok: see pre-declaration above
+                model=model,
+                custom_llm_provider=custom_llm_provider,
+                api_base=kwargs.get("api_base", None),
+            )
+
         func: Final = partial(
             rerank,
             model,
@@ -70,7 +84,11 @@ async def arerank(
             response = init_response
         return response
     except Exception as e:
-        raise e
+        raise exception_type(
+            model=model,
+            custom_llm_provider=_custom_llm_provider or custom_llm_provider,
+            original_exception=e,
+        )
 
 
 @client
@@ -115,6 +133,7 @@ def rerank(
     model_info: Final = kwargs.get("model_info", None)
     user: Final = kwargs.get("user", None)
     client: Final = kwargs.get("client", None)
+    _custom_llm_provider: str | None = None  # rebind-ok: set by the get_llm_provider unpack; read in the except
     try:
         _is_async: Final = kwargs.pop("arerank", False) is True
         optional_params: Final = GenericLiteLLMParams(**kwargs)
@@ -127,7 +146,7 @@ def rerank(
 
         (
             model,
-            _custom_llm_provider,
+            _custom_llm_provider,  # rebind-ok: see pre-declaration above
             dynamic_api_key,
             dynamic_api_base,
         ) = litellm.get_llm_provider(
@@ -538,4 +557,8 @@ def rerank(
         return response
     except Exception as e:
         verbose_logger.error("Error in rerank: %s", e)
-        raise exception_type(model=model, custom_llm_provider=custom_llm_provider, original_exception=e)
+        raise exception_type(
+            model=model,
+            custom_llm_provider=_custom_llm_provider or custom_llm_provider,
+            original_exception=e,
+        )
diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
index db1c3acbefb..bc25f4fffb1 100644
--- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py
+++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
@@ -1169,16 +1169,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
 
     def _emit_response_completed_event(self, litellm_model_response: ModelResponse) -> ResponseCompletedEvent | None:
         if litellm_model_response:
-            # Add cost to usage object if include_cost_in_streaming_usage is True
-            if litellm.include_cost_in_streaming_usage and self.litellm_logging_obj is not None:
-                usage: Final[object] = getattr(litellm_model_response, "usage", None)
-                if usage is not None:
-                    setattr(
-                        usage,
-                        "cost",
-                        self.litellm_logging_obj._response_cost_calculator(result=litellm_model_response),
-                    )
-
             # Transform the response
             responses_api_response: Final = (
                 LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py
index de802b95086..7871c85220c 100644
--- a/litellm/responses/streaming_iterator.py
+++ b/litellm/responses/streaming_iterator.py
@@ -407,23 +407,7 @@ class BaseResponsesAPIStreamingIterator:
                     openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED,
                 ):
                     self.completed_response = openai_responses_api_chunk
-                    # Add cost to usage object if include_cost_in_streaming_usage is True
-                    if litellm.include_cost_in_streaming_usage and self.logging_obj is not None:
-                        response_obj: Final[ResponsesAPIResponse | None] = getattr(
-                            openai_responses_api_chunk, "response", None
-                        )
-                        if response_obj:
-                            usage_obj: Final[ResponseAPIUsage | None] = getattr(response_obj, "usage", None)
-                            if usage_obj is not None:
-                                try:
-                                    cost: Final[float | None] = self.logging_obj._response_cost_calculator(
-                                        result=response_obj
-                                    )
-                                    if cost is not None:
-                                        setattr(usage_obj, "cost", cost)
-                                except Exception:
-                                    # Best-effort usage cost annotation should not break stream replay.
-                                    pass
+                    _stamp_responses_usage_cost(getattr(openai_responses_api_chunk, "response", None), self.logging_obj)
 
                     if _chunk_type == openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED:
                         self._handle_logging_failed_response()
@@ -1023,7 +1007,7 @@ class MockResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator):
         transformed: ResponsesAPIResponse,
         logging_obj: LiteLLMLoggingObj,
     ) -> None:
-        self._events: list[ResponsesAPIStreamingResponse] = _build_synthetic_response_events(
+        self._events: Sequence[ResponsesAPIStreamingResponse] = build_synthetic_response_events(
             transformed=transformed,
             logging_obj=logging_obj,
             chunk_size=self.CHUNK_SIZE,
@@ -1090,7 +1074,7 @@ class CachedResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator):
         transformed: ResponsesAPIResponse,
         logging_obj: LiteLLMLoggingObj,
     ) -> None:
-        self._events = _build_synthetic_response_events(
+        self._events = build_synthetic_response_events(
             transformed=transformed,
             logging_obj=logging_obj,
             chunk_size=MockResponsesAPIStreamingIterator.CHUNK_SIZE,
@@ -1274,22 +1258,32 @@ def _add_text_like_part_events(
         )
 
 
-def _build_synthetic_response_events(
+def _stamp_responses_usage_cost(
+    response_obj: ResponsesAPIResponse | None, logging_obj: LiteLLMLoggingObj | None
+) -> None:
+    if response_obj is None or logging_obj is None:
+        return
+    usage_obj: Final[ResponseAPIUsage | None] = getattr(response_obj, "usage", None)
+    if usage_obj is None:
+        return
+    if isinstance(getattr(usage_obj, "cost", None), (int, float)):
+        return
+    try:
+        cost: Final[float | None] = logging_obj._response_cost_calculator(result=response_obj)
+    except Exception:
+        return
+    if isinstance(cost, (int, float)) and cost > 0:
+        setattr(usage_obj, "cost", cost)
+
+
+def build_synthetic_response_events(
     *,
     transformed: ResponsesAPIResponse,
-    logging_obj: LiteLLMLoggingObj,
+    logging_obj: LiteLLMLoggingObj | None,
     chunk_size: int,
 ) -> list[ResponsesAPIStreamingResponse]:
     openai_types: Final = _get_openai_response_types()
-    if litellm.include_cost_in_streaming_usage and logging_obj is not None:
-        usage_obj: Final = transformed.usage if hasattr(transformed, "usage") else None
-        if usage_obj is not None:
-            try:
-                cost: Final[float | None] = logging_obj._response_cost_calculator(result=transformed)
-                if cost is not None:
-                    setattr(usage_obj, "cost", cost)
-            except Exception:
-                pass
+    _stamp_responses_usage_cost(transformed, logging_obj)
 
     events: Final[list[ResponsesAPIStreamingResponse]] = [
         _build_response_status_event(openai_types.ResponsesAPIStreamEvents.RESPONSE_CREATED, transformed),
diff --git a/litellm/router.py b/litellm/router.py
index 9e0e267f21c..991f1bc2828 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -22,7 +22,7 @@ import traceback
 import weakref
 from collections import defaultdict
 from collections.abc import AsyncGenerator, AsyncIterator, Callable, Generator, Mapping, Sequence
-from functools import lru_cache
+from functools import lru_cache, partial
 from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Literal, Optional, TypeAlias, TypeVar, Union, cast
 
@@ -50,6 +50,7 @@ from litellm.constants import (
     DEFAULT_HEALTH_CHECK_INTERVAL,
     DEFAULT_HEALTH_CHECK_STALENESS_MULTIPLIER,
     DEFAULT_MAX_LRU_CACHE_SIZE,
+    RUNTIME_UPDATABLE_ROUTER_SETTINGS,
     SESSION_DEPLOYMENT_AFFINITY_TTL_METADATA_KEY,
 )
 from litellm.integrations.custom_logger import CustomLogger
@@ -146,7 +147,11 @@ from litellm.router_utils.cooldown_handlers import (
 from litellm.router_utils.fallback_event_handlers import (
     AttemptedFallbackTargets,
     _check_non_standard_fallback_format,
-    get_fallback_model_group,
+    clear_pre_routing_selection,
+    fallback_lookup_groups,
+    get_fallback_model_group_for_lookup_groups,
+    get_pre_routing_selection,
+    record_pre_routing_selection,
     run_async_fallback,
 )
 from litellm.router_utils.get_retry_from_policy import (
@@ -353,6 +358,13 @@ _PreRoutingStrategyT = TypeVar("_PreRoutingStrategyT")
 _ALIAS_PARAMS_NEVER_FORWARDED: Final = frozenset({"model", "api_base", "api_key", "api_version"})
 _ALIAS_MARKER_FORWARDED_PARAMS_KWARG: Final = "_alias_marker_forwarded_params"
 
+_RUNTIME_TOGGLEABLE_PRE_CALL_CHECKS: Final[Mapping[str, type[CustomLogger]]] = MappingProxyType(
+    {
+        "prompt_caching": PromptCachingDeploymentCheck,
+        "enforce_model_rate_limits": ModelRateLimitingCheck,
+    }
+)
+
 
 def _stream_chunks_have_generated_content(chunks: Sequence[ModelResponseStream]) -> bool:
     for chunk in chunks:
@@ -824,6 +836,7 @@ class Router:
         self._zero_cost_cache: dict[str, bool] = {}
         self._routing_group_rows: tuple[DeploymentTypedDict, ...] | None = None
         self._init_routing_groups(None)
+        self._provider_unresolved_deployments: tuple[Callable[[], Deployment | None], ...] = ()
 
         self.deployment_affinity_ttl_seconds = deployment_affinity_ttl_seconds
         self.model_group_affinity_config = model_group_affinity_config
@@ -2070,11 +2083,39 @@ class Router:
             if _callback is None:
                 continue
 
+            if self.optional_callbacks is not None and any(
+                isinstance(callback, type(_callback)) for callback in self.optional_callbacks
+            ):
+                continue
             if self.optional_callbacks is None:
                 self.optional_callbacks = []
             self.optional_callbacks.append(_callback)
             litellm.logging_callback_manager.add_litellm_callback(_callback)
 
+    def set_optional_pre_call_checks(self, optional_pre_call_checks: OptionalPreCallChecks | None) -> None:
+        if optional_pre_call_checks is None:
+            return
+        requested: Final = frozenset(optional_pre_call_checks)
+        for name, callback_cls in _RUNTIME_TOGGLEABLE_PRE_CALL_CHECKS.items():
+            if name not in requested:
+                self._remove_optional_callbacks_of_type(callback_cls)
+        self.add_optional_pre_call_checks(optional_pre_call_checks)
+
+    def _remove_optional_callbacks_of_type(self, callback_cls: type[CustomLogger]) -> None:
+        if self.optional_callbacks is None or not any(type(cb) is callback_cls for cb in self.optional_callbacks):
+            return
+        self.optional_callbacks = [cb for cb in self.optional_callbacks if type(cb) is not callback_cls]
+        if any(
+            router is not self and any(type(cb) is callback_cls for cb in (router.optional_callbacks or []))
+            for router in tuple(_live_routers)
+        ):
+            return
+        for cb in tuple(litellm.callbacks):
+            if type(cb) is callback_cls:
+                litellm.logging_callback_manager.remove_callback_from_list_by_object(
+                    litellm.callbacks, cb, require_self=False
+                )
+
     def print_deployment(self, deployment: dict):
         """
         returns a copy of the deployment with the api key masked
@@ -2322,7 +2363,7 @@ class Router:
     @overload
     async def acompletion(
         self, model: str, messages: list[AllMessageValues], stream: Literal[True, False] = False, **kwargs
-    ) -> CustomStreamWrapper | ModelResponse: 
+    ) -> CustomStreamWrapper | ModelResponse:
         ...
 
     # fmt: on
@@ -4921,6 +4962,19 @@ class Router:
                 )
                 response = await response
 
+            if self._should_raise_anthropic_refusal_error(
+                model=model,
+                original_generic_function=original_generic_function,
+                response=response,
+                kwargs=kwargs,
+            ):
+                from litellm.llms.anthropic.experimental_pass_through.messages.utils import (
+                    safeguard_refusal_error,
+                )
+
+                refusal_details: Final = cast(dict, response["stop_details"])  # cast-ok: gate verified the shape
+                raise safeguard_refusal_error(model=model, stop_details=refusal_details)
+
             self.success_calls[model_name] += 1
             verbose_router_logger.info("ageneric_api_call_with_fallbacks(model=%s)\x1b[32m 200 OK\x1b[0m", model_name)
 
@@ -4967,6 +5021,11 @@ class Router:
         # fallback to the original reference for any non-picklable value.
         # The original_generic_function is preserved so the per-attempt
         # helper knows which underlying API to call on fallback.
+        # The pre-routing hook stamps its tier selection into this bucket during the primary
+        # attempt; seeding it before the snapshot gives both the live kwargs and the copy a
+        # bucket, so the post-call carry-over below always has somewhere to read and write.
+        kwargs.setdefault("litellm_metadata", {})  # mutable-ok: shared bucket  # rebind-ok: stamp must be readable here
+
         fallback_kwargs: Final[dict[str, object]] = kwargs.copy()
         if isinstance(fallback_kwargs.get("litellm_metadata"), dict):
             fallback_kwargs["litellm_metadata"] = safe_deep_copy(fallback_kwargs["litellm_metadata"])
@@ -4976,6 +5035,14 @@ class Router:
 
         response: Final = await self._ageneric_api_call_with_fallbacks(original_function=original_function, **kwargs)
 
+        # The snapshot predates the pre-routing hook, so the tier it stamped into the live kwargs
+        # is carried over write-or-clear: a stale or caller-supplied selection left in the copy
+        # would key the mid-stream fallback lookup off a tier this attempt never routed to.
+        clear_pre_routing_selection(fallback_kwargs)
+        live_pre_routing_selection: Final = get_pre_routing_selection(kwargs)
+        if live_pre_routing_selection is not None:
+            record_pre_routing_selection(fallback_kwargs, live_pre_routing_selection)
+
         if kwargs.get("stream") and isinstance(response, BaseResponsesAPIStreamingIterator):
             return await self._aresponses_streaming_iterator(
                 response=response,
@@ -5033,6 +5100,10 @@ class Router:
         from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
             aclose_if_supported,
             parse_anthropic_error_event,
+            parse_anthropic_refusal_stop_details,
+        )
+        from litellm.llms.anthropic.experimental_pass_through.messages.utils import (
+            safeguard_refusal_error,
         )
 
         source_iterator: Final = response
@@ -5071,13 +5142,35 @@ class Router:
                         continue
                     if _anthropic_stream_commits_now(chunk, has_generated_content, len(buffered_lifecycle_chunks)):
                         has_generated_content = True  # rebind-ok: real content seen, or the buffer cap was hit
-                    error_event = parse_anthropic_error_event(chunk)
+                    # A transport can split one SSE data line across byte chunks, so pre-content
+                    # detection parses the accumulated buffer plus the current chunk, never the
+                    # chunk alone; the buffer is already capped, which bounds this window too.
+                    parse_window = (  # rebind-ok: freshly computed each iteration, never carried over
+                        b"".join(c for c in (*buffered_lifecycle_chunks, chunk) if isinstance(c, (bytes, bytearray)))  # pyright: ignore[reportUnnecessaryIsInstance]  # bridge-path chunks are not always bytes at runtime
+                        if not has_generated_content and isinstance(chunk, (bytes, bytearray))  # pyright: ignore[reportUnnecessaryIsInstance]  # bridge-path chunks are not always bytes at runtime
+                        else chunk
+                    )
+                    error_event = parse_anthropic_error_event(parse_window)
                     retriable_pending_error = (  # rebind-ok: freshly computed each iteration, never carried over
                         not has_generated_content
                         and error_event is not None
                         and _is_retriable_anthropic_status(error_event[2])
                         and not _anthropic_stream_error_is_gateway_verdict(chunk)
                     )
+                    refusal_stop_details = (  # rebind-ok: freshly computed each iteration, never carried over
+                        parse_anthropic_refusal_stop_details(parse_window)
+                        if not has_generated_content and error_event is None
+                        else None
+                    )
+                    if refusal_stop_details is not None and self._has_content_policy_fallback(model, initial_kwargs):
+                        refusal_error = safeguard_refusal_error(model=model, stop_details=refusal_stop_details)
+                        raise MidStreamFallbackError(
+                            message=refusal_error.message,
+                            model=model,
+                            llm_provider="anthropic",
+                            original_exception=refusal_error,
+                            is_pre_first_chunk=True,
+                        )
                     if not has_generated_content and not retriable_pending_error and error_event is None:
                         buffered_lifecycle_chunks = (*buffered_lifecycle_chunks, chunk)
                         continue
@@ -5189,8 +5282,13 @@ class Router:
                 kwargs=initial_kwargs,
                 metadata_variable_name="litellm_metadata",
             )
+            # The content-policy dispatch branch matches on the trigger's own type, so a refusal's
+            # MidStreamFallbackError envelope is unwrapped here or the wrong fallback list is consulted.
+            fallback_trigger: Final[Exception] = (
+                e.original_exception if isinstance(e.original_exception, litellm.ContentPolicyViolationError) else e
+            )
             fallback_response = await self.async_function_with_fallbacks_common_utils(  # rebind-ok: set on success
-                e=e,
+                e=fallback_trigger,
                 disable_fallbacks=False,
                 fallbacks=fallbacks,
                 context_window_fallbacks=context_window_fallbacks,
@@ -5246,6 +5344,11 @@ class Router:
         # share, leaking primary-deployment metadata into the mid-stream
         # fallback request. safe_deep_copy avoids deep-copying the full
         # kwargs (which can hold non-deepcopyable logging handles/clients).
+        # The pre-routing hook stamps its tier selection into this bucket during the primary
+        # attempt; seeding it before the snapshot gives both the live kwargs and the copy a
+        # bucket, so the post-call carry-over below always has somewhere to read and write.
+        kwargs.setdefault("litellm_metadata", {})  # mutable-ok: shared bucket  # rebind-ok: stamp must be readable here
+
         fallback_kwargs: Final[dict[str, object]] = kwargs.copy()  # mutable-ok: mutated below before re-entry
         if isinstance(fallback_kwargs.get("litellm_metadata"), dict):
             fallback_kwargs["litellm_metadata"] = safe_deep_copy(fallback_kwargs["litellm_metadata"])
@@ -5255,6 +5358,14 @@ class Router:
 
         response: Final = await self._ageneric_api_call_with_fallbacks(original_function=original_function, **kwargs)
 
+        # The snapshot predates the pre-routing hook, so the tier it stamped into the live kwargs
+        # is carried over write-or-clear: a stale or caller-supplied selection left in the copy
+        # would key the mid-stream fallback lookup off a tier this attempt never routed to.
+        clear_pre_routing_selection(fallback_kwargs)
+        live_pre_routing_selection: Final = get_pre_routing_selection(kwargs)
+        if live_pre_routing_selection is not None:
+            record_pre_routing_selection(fallback_kwargs, live_pre_routing_selection)
+
         if kwargs.get("stream") and hasattr(response, "__aiter__"):
             return await self._aanthropic_messages_streaming_iterator(
                 response=cast("AsyncIterator[bytes]", response),  # cast-ok: stream=True always returns a byte iterator
@@ -6302,8 +6413,6 @@ class Router:
             "responses",
             "generate_content",
             "generate_content_stream",
-            "vector_store_search",
-            "vector_store_create",
             "ocr",
             "search",
             "video_generation",
@@ -6322,39 +6431,13 @@ class Router:
                 client: object | None = None,
                 **kwargs,
             ):
-                if call_type == "vector_store_search":
-                    metadata: Final = self._vector_store_request_metadata(kwargs)
-                    provider_kwargs: Final = (
-                        {
-                            "custom_llm_provider": custom_llm_provider
-                        }  # mutable-ok: provider kwargs are expanded into the request
-                        if custom_llm_provider is not None
-                        else MappingProxyType({})
-                    )
-                    search_kwargs: Final = {  # mutable-ok: the routed request requires dynamic keyword arguments
-                        **kwargs,
-                        **provider_kwargs,
-                        "_direct_vector_store_embedding_executor": RouterVectorStoreEmbeddingExecutor(
-                            router=self,
-                            metadata=metadata,
-                        ),
-                    }
-                    model: Final = search_kwargs.get("model")
-                    if isinstance(model, str) and model:
-                        routed_kwargs: Final = {  # mutable-ok: model must be removed before expanding routed kwargs
-                            key: value for key, value in search_kwargs.items() if key != "model"
-                        }
-                        return self._generic_api_call_with_fallbacks(
-                            model=model,
-                            original_function=original_function,
-                            **routed_kwargs,
-                        )
-                    return original_function(**search_kwargs)
                 return self._generic_api_call_with_fallbacks(original_function=original_function, **kwargs)
 
             return sync_wrapper
 
         if call_type in (
+            "vector_store_search",
+            "vector_store_create",
             "vector_store_retrieve",
             "vector_store_list",
             "vector_store_update",
@@ -6366,11 +6449,29 @@ class Router:
                 client: object | None = None,
                 **kwargs,
             ):
-                if custom_llm_provider and "custom_llm_provider" not in kwargs:
-                    kwargs["custom_llm_provider"] = custom_llm_provider
-                if kwargs.get("model"):
-                    return self._generic_api_call_with_fallbacks(original_function=original_function, **kwargs)
-                return original_function(**kwargs)
+                provider_kwargs: Final = (
+                    MappingProxyType({**kwargs, "custom_llm_provider": custom_llm_provider})
+                    if custom_llm_provider and "custom_llm_provider" not in kwargs
+                    else MappingProxyType(kwargs)
+                )
+                search_kwargs: Final = (
+                    MappingProxyType(
+                        {
+                            **provider_kwargs,
+                            "_direct_vector_store_embedding_executor": RouterVectorStoreEmbeddingExecutor(
+                                router=self,
+                                metadata=self._vector_store_request_metadata(kwargs),
+                            ),
+                        }
+                    )
+                    if call_type == "vector_store_search"
+                    else provider_kwargs
+                )
+                if search_kwargs.get("model"):
+                    return self._generic_api_call_with_fallbacks(original_function=original_function, **search_kwargs)
+                if call_type == "vector_store_search":
+                    return original_function(**MappingProxyType({**search_kwargs, "router": self}))
+                return original_function(**search_kwargs)
 
             return vector_store_sync_wrapper
 
@@ -6557,6 +6658,7 @@ class Router:
                 return await self._init_vector_store_api_endpoints(
                     original_function=original_function,
                     custom_llm_provider=custom_llm_provider,
+                    call_type=call_type,
                     **vector_store_kwargs,
                 )
             elif call_type in ("afile_delete", "afile_content"):
@@ -6609,6 +6711,7 @@ class Router:
         self,
         original_function: Callable,
         custom_llm_provider: str | None = None,
+        call_type: str | None = None,
         **kwargs,
     ):
         """
@@ -6627,6 +6730,13 @@ class Router:
                 **kwargs,
             )
 
+        # For search, pass the router so provider transforms can resolve
+        # router-managed embedding models (e.g. S3 Vectors query embeddings).
+        # The merge also overrides any client-supplied `router` key.
+        if call_type == "avector_store_search":
+            search_kwargs: Final = MappingProxyType({**kwargs, "router": self})
+            return await original_function(**search_kwargs)
+
         # Otherwise, call the original function directly
         return await original_function(**kwargs)
 
@@ -6643,7 +6753,10 @@ class Router:
         metadata. When present, decode the ID, replace ``container_id`` with the
         upstream value, and route through ``_ageneric_api_call_with_fallbacks`` so
         deployment credentials (e.g. regional ``api_base`` for Azure) match
-        :meth:`_init_responses_api_endpoints`. Otherwise call the handler directly.
+        :meth:`_init_responses_api_endpoints`. Create/list calls carry no container ID, so
+        they route through the deployment named by ``model`` when the caller passes one,
+        falling back to the direct call when no deployment matches. Otherwise call the
+        handler directly with global provider credentials.
         """
         if custom_llm_provider and "custom_llm_provider" not in kwargs:
             kwargs["custom_llm_provider"] = custom_llm_provider
@@ -6675,6 +6788,14 @@ class Router:
                     **kwargs,
                 )
 
+        requested_model: Final = kwargs.get("model")
+        if isinstance(requested_model, str) and requested_model.strip():
+            return await self._ageneric_api_call_with_fallbacks(
+                original_function=original_function,
+                passthrough_on_no_deployment=True,
+                **kwargs,
+            )
+
         return await original_function(**kwargs)
 
     async def _init_responses_api_endpoints(
@@ -6861,6 +6982,9 @@ class Router:
         original_exception: Final = e
         fallback_model_group = None
         original_model_group: Final[str | None] = kwargs.get("model")
+        # A pre-routing hook (complexity / auto / adaptive / quality routers) picks a tier
+        # behind the router name, and fallbacks are configured per tier, not per router.
+        lookup_groups: Final[tuple[str, ...]] = fallback_lookup_groups(kwargs, model_group)
         fallback_failure_exception_str = ""
 
         if disable_fallbacks is True or original_model_group is None:
@@ -6905,15 +7029,15 @@ class Router:
             ]
             # Get external fallbacks — handle both standard and non-standard formats
             external_fallback_group: list | None = None
-            if fallbacks is not None and model_group is not None:
+            if fallbacks is not None and lookup_groups:
                 if _check_non_standard_fallback_format(fallbacks=fallbacks):
                     # Non-standard formats (e.g. ["claude-3-haiku"] or
                     # [{"model": "...", "messages": [...]}]) are passed through directly
                     external_fallback_group = fallbacks
                 else:
-                    external_fallback_group, generic_idx = get_fallback_model_group(
+                    external_fallback_group, generic_idx = get_fallback_model_group_for_lookup_groups(
                         fallbacks=fallbacks,
-                        model_group=cast(str, model_group),
+                        lookup_groups=lookup_groups,
                     )
                     if external_fallback_group is None and generic_idx is not None:
                         external_fallback_group = fallbacks[generic_idx]["*"]
@@ -6971,9 +7095,9 @@ class Router:
             if isinstance(e, litellm.ContextWindowExceededError):
                 if context_window_fallbacks is not None:
                     context_window_fallback_model_group: Final[list[str] | None] = (
-                        self._get_fallback_model_group_from_fallbacks(
+                        self._get_fallback_model_group_for_lookup_groups(
                             fallbacks=context_window_fallbacks,
-                            model_group=model_group,
+                            lookup_groups=lookup_groups,
                         )
                     )
                     if context_window_fallback_model_group is None:
@@ -7004,9 +7128,9 @@ class Router:
             elif isinstance(e, litellm.ContentPolicyViolationError):
                 if content_policy_fallbacks is not None:
                     content_policy_fallback_model_group: Final[list[str] | None] = (
-                        self._get_fallback_model_group_from_fallbacks(
+                        self._get_fallback_model_group_for_lookup_groups(
                             fallbacks=content_policy_fallbacks,
-                            model_group=model_group,
+                            lookup_groups=lookup_groups,
                         )
                     )
                     if content_policy_fallback_model_group is None:
@@ -7033,14 +7157,14 @@ class Router:
 
                     if litellm.expose_router_debug_in_errors:
                         e.message += f"\n{error_message}"
-            if fallbacks is not None and model_group is not None:
+            if fallbacks is not None and lookup_groups:
                 verbose_router_logger.debug("inside model fallbacks: %s", mask_sensitive_structure(fallbacks))
                 (
                     fallback_model_group,
                     generic_fallback_idx,
-                ) = get_fallback_model_group(
+                ) = get_fallback_model_group_for_lookup_groups(
                     fallbacks=fallbacks,  # if fallbacks = [{"gpt-3.5-turbo": ["claude-3-haiku"]}]
-                    model_group=cast(str, model_group),
+                    lookup_groups=lookup_groups,
                 )
                 ## if none, check for generic fallback
                 if fallback_model_group is None and generic_fallback_idx is not None:
@@ -7049,12 +7173,12 @@ class Router:
                 if fallback_model_group is None:
                     masked_fallbacks: Final = mask_sensitive_structure(fallbacks)
                     verbose_router_logger.info(
-                        "No fallback model group found for original model_group=%s. Fallbacks=%s",
-                        model_group,
+                        "No fallback model group found for lookup_groups=%s. Fallbacks=%s",
+                        " -> ".join(lookup_groups),
                         masked_fallbacks,
                     )
                     if hasattr(original_exception, "message") and litellm.expose_router_debug_in_errors:
-                        original_exception.message += f"No fallback model group found for original model_group={model_group}. Fallbacks={masked_fallbacks}"
+                        original_exception.message += f"No fallback model group found for lookup_groups={' -> '.join(lookup_groups)}. Fallbacks={masked_fallbacks}"
                     raise original_exception
 
                 input_kwargs.update(
@@ -7100,6 +7224,7 @@ class Router:
         If it fails after num_retries, fall back to another model group
         """
         model_group: Final[str | None] = kwargs.get("model")
+        clear_pre_routing_selection(kwargs)  # pyright: ignore[reportUnknownArgumentType]  # **kwargs is untyped at this boundary
         if not isinstance(kwargs.get("attempted_targets"), AttemptedFallbackTargets):
             _fallback_metadata_key: Final = _get_router_metadata_variable_name(
                 function_name=getattr(kwargs.get("original_function"), "__name__", None)
@@ -7525,6 +7650,24 @@ class Router:
                 break
         return fallback_model_group
 
+    def _get_fallback_model_group_for_lookup_groups(
+        self,
+        fallbacks: list[dict[str, list[str]]],  # mutable-ok: mirrors the sibling resolver's contract
+        lookup_groups: tuple[str, ...],
+    ) -> list[str] | None:  # mutable-ok: mirrors the sibling resolver's contract
+        """First lookup group whose exact-key chain resolves (tier first, then requested group)."""
+        return next(
+            (
+                resolved
+                for resolved in (
+                    self._get_fallback_model_group_from_fallbacks(fallbacks=fallbacks, model_group=group)
+                    for group in lookup_groups
+                )
+                if resolved is not None
+            ),
+            None,
+        )
+
     def _get_first_default_fallback(self) -> str | None:
         """
         Returns the first model from the default_fallbacks list, if it exists.
@@ -7940,6 +8083,31 @@ class Router:
                     return True
         return False
 
+    def _has_content_policy_fallback(self, model_group: str, kwargs: Mapping[str, Any]) -> bool:
+        """
+        Whether a content-policy fallback would resolve for this request, keyed the same way
+        async_function_with_fallbacks_common_utils resolves it: the tier a pre-routing hook
+        selected wins over the requested group. Raising without this returning True would turn
+        a deliverable response into an error the fallback chain cannot recover from.
+        """
+        content_policy_fallbacks: Final = kwargs.get("content_policy_fallbacks", self.content_policy_fallbacks)
+        if content_policy_fallbacks is not None:
+            return (
+                self._get_fallback_model_group_for_lookup_groups(
+                    fallbacks=content_policy_fallbacks,
+                    lookup_groups=fallback_lookup_groups(kwargs, model_group),
+                )
+                is not None
+            )
+        if self._has_default_fallbacks():
+            return True
+        verbose_router_logger.debug(
+            "No content-policy fallback available. Returning original response. model=%s, content_policy_fallbacks=%s",
+            model_group,
+            content_policy_fallbacks,
+        )
+        return False
+
     def _should_raise_content_policy_error(self, model: str, response: ModelResponse, kwargs: dict) -> bool:
         """
         Determines if a content policy error should be raised.
@@ -7952,27 +8120,26 @@ class Router:
             if response.choices[0].finish_reason != "content_filter":
                 return False
 
-        content_policy_fallbacks: Final = kwargs.get("content_policy_fallbacks", self.content_policy_fallbacks)
+        return self._has_content_policy_fallback(model, kwargs)
 
-        ### ONLY RAISE ERROR IF CP FALLBACK AVAILABLE ###
-        if content_policy_fallbacks is not None:
-            fallback_model_group = None
-            for item in content_policy_fallbacks:  # [{"gpt-3.5-turbo": ["gpt-4"]}]
-                if list(item.keys())[0] == model:
-                    fallback_model_group = item[model]
-                    break
-
-            if fallback_model_group is not None:
-                return True
-        elif self._has_default_fallbacks():  # default fallbacks set
-            return True
-
-        verbose_router_logger.debug(
-            "Content Policy Error occurred. No available fallbacks. Returning original response. model=%s, content_policy_fallbacks=%s",
-            model,
-            content_policy_fallbacks,
+    def _should_raise_anthropic_refusal_error(
+        self, model: str, original_generic_function: Callable, response: object, kwargs: Mapping[str, Any]
+    ) -> bool:
+        """
+        The /v1/messages twin of _should_raise_content_policy_error: an Anthropic safeguard
+        refusal (stop_reason "refusal" carrying stop_details) re-enters the fallback chain only
+        when a content-policy fallback is configured; a plain refusal without stop_details, or
+        any response with nothing configured, is returned to the client unchanged.
+        """
+        from litellm.llms.anthropic.experimental_pass_through.messages.utils import (
+            get_safeguard_refusal_stop_details,
         )
-        return False
+
+        if getattr(original_generic_function, "__name__", "") != "anthropic_messages":
+            return False
+        if get_safeguard_refusal_stop_details(response) is None:
+            return False
+        return self._has_content_policy_fallback(model, kwargs)
 
     def _get_healthy_deployments(self, model: str, parent_otel_span: Span | None):
         _all_deployments: list = []
@@ -8406,6 +8573,19 @@ class Router:
             return deployment
         except Exception as e:
             if self.ignore_invalid_deployments:
+                if isinstance(e, litellm.BadRequestError):
+                    self._provider_unresolved_deployments = (
+                        *self._provider_unresolved_deployments,
+                        partial(
+                            self._create_deployment,
+                            deployment_info=deployment_info,
+                            _model_name=_model_name,
+                            _litellm_params=_litellm_params,
+                            _model_info=_model_info,
+                            declared_id=declared_id,
+                            duplicate_ids=duplicate_ids,
+                        ),
+                    )
                 verbose_router_logger.exception(
                     "Error creating deployment: %s, ignoring and continuing with other deployments.", e
                 )
@@ -8835,6 +9015,7 @@ class Router:
         self.quality_routers = {}
         self.complexity_routers = {}
         self.auto_routers = {}
+        self._provider_unresolved_deployments = ()
         self._invalidate_model_group_info_cache()
         self._invalidate_access_groups_cache()
         # we add api_base/api_key each model so load balancing between azure/gpt on api_base1 and api_base2 works
@@ -9457,8 +9638,12 @@ class Router:
         """Re-assert this router's deployments onto a freshly fetched catalog.
 
         Reads ``model_list`` at call time, so only deployments the router still
-        serves are restored.
+        serves are restored, plus any config deployment the fresh catalog now resolves.
         """
+        provider_unresolved: Final = self._provider_unresolved_deployments
+        self._provider_unresolved_deployments = ()
+        for create_deployment in provider_unresolved:
+            create_deployment()
         for entry in tuple(self.model_list):
             try:
                 deployment = entry if isinstance(entry, Deployment) else Deployment(**entry)
@@ -9661,6 +9846,26 @@ class Router:
             coerce_token_limit(model_info.get("max_output_tokens")),
         )
 
+    def get_configured_display_name(self, model_name: str) -> "str | None":
+        """
+        Return the display_name explicitly configured in a concrete deployment's
+        model_info for model_name, via O(1) index lookup.
+
+        Returns None for wildcard-expanded or unknown names, and treats a
+        non-string or empty configured value as absent rather than failing the
+        listing. Like get_configured_token_limits, this never triggers pattern
+        matching or deep copies, so it is safe to call per listed model on the
+        /v1/models hot path.
+        """
+        deployment: Final = self.get_deployment_by_model_group_name(model_group_name=model_name)
+        if deployment is None:
+            return None
+
+        display_name: Final = deployment.model_info.get("display_name")
+        if isinstance(display_name, str) and display_name.strip():
+            return display_name
+        return None
+
     def get_deployment_credentials_with_provider(
         self, model_id: str, team_id: str | None = None
     ) -> dict[str, Any] | None:
@@ -11246,27 +11451,6 @@ class Router:
         """
         Update the router settings.
         """
-        # only the following settings are allowed to be configured
-        _allowed_settings: Final = [
-            "routing_strategy_args",
-            "routing_strategy",
-            "routing_groups",
-            "allowed_fails",
-            "cooldown_time",
-            "num_retries",
-            "timeout",
-            "max_retries",
-            "retry_after",
-            "fallbacks",
-            "context_window_fallbacks",
-            "retry_policy",
-            "model_group_retry_policy",
-            "model_group_alias",
-            "enable_weighted_failover",
-            "enable_tag_filtering",
-            "tag_routing_prefix",
-        ]
-
         _int_settings: Final = [
             "timeout",
             "num_retries",
@@ -11279,13 +11463,15 @@ class Router:
         rebuild_routing_groups = False
         relink_lar1_from_args = False
         for var in kwargs:
-            if var in _allowed_settings:
+            if var in RUNTIME_UPDATABLE_ROUTER_SETTINGS:
                 if var in _int_settings:
                     _casted_value = int(kwargs[var])
                     setattr(self, var, _casted_value)
                 elif var == "routing_groups":
                     self._routing_groups_input = kwargs[var]
                     rebuild_routing_groups = True
+                elif var == "optional_pre_call_checks":
+                    self.set_optional_pre_call_checks(kwargs[var])
                 elif var == "retry_policy":
                     value = kwargs[var]
                     if isinstance(value, dict):
@@ -12141,6 +12327,7 @@ class Router:
             if pre_routing_hook_response is not None:
                 model = pre_routing_hook_response.model
                 messages = pre_routing_hook_response.messages
+                record_pre_routing_selection(request_kwargs, model)
                 if pre_routing_hook_response.litellm_params:
                     accepted_tier_params: Final = self._tier_params_the_target_accepts(
                         model, pre_routing_hook_response.litellm_params, request_kwargs
@@ -12256,6 +12443,7 @@ class Router:
             if pre_routing_hook_response is not None:
                 model = pre_routing_hook_response.model
                 messages = pre_routing_hook_response.messages
+                record_pre_routing_selection(request_kwargs, model)
                 if pre_routing_hook_response.litellm_params:
                     accepted_tier_params: Final = self._tier_params_the_target_accepts(
                         model, pre_routing_hook_response.litellm_params, request_kwargs
diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py
index d2842294a08..3d37ca216a7 100644
--- a/litellm/router_utils/fallback_event_handlers.py
+++ b/litellm/router_utils/fallback_event_handlers.py
@@ -214,6 +214,91 @@ def _check_stripped_model_group(model_group: str, fallback_key: str) -> bool:
     return False
 
 
+PRE_ROUTING_SELECTED_MODEL_KEY: Final = "pre_routing_selected_model"
+_ROUTER_METADATA_BUCKETS: Final = ("metadata", "litellm_metadata")
+
+
+def record_pre_routing_selection(request_kwargs: Mapping[str, Any] | None, selected_model: str) -> None:
+    """
+    Remember which model a pre-routing hook picked, so fallback lookup can key off it.
+
+    Fallback resolution runs on an outer kwargs dict that ``**kwargs`` already copied, so
+    writing the model there is invisible by the time routing picks a tier. The metadata
+    buckets are nested dicts shared by reference across those copies, which is how the
+    router already carries values back up.
+
+    The write goes through the proxy-internal bucket resolver, never into both buckets:
+    on /v1/messages the top-level ``metadata`` dict is the provider's own request field,
+    so a blanket write would forward the tier stamp upstream.
+    """
+    from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs
+
+    if request_kwargs is None:
+        return
+    bucket: Final = request_kwargs.get(get_metadata_variable_name_from_kwargs(request_kwargs))
+    if isinstance(bucket, dict):
+        bucket[PRE_ROUTING_SELECTED_MODEL_KEY] = selected_model
+
+
+def clear_pre_routing_selection(request_kwargs: Mapping[str, object] | None) -> None:
+    """
+    Drop any selection the router did not make itself on this hop.
+
+    The buckets carry whatever the caller sent, so an inbound value is the caller
+    choosing a fallback chain rather than the router choosing a tier. A fallback hop
+    also inherits the previous hop's selection, which would key its own failure off
+    the tier that already failed. Clearing at the start of every hop leaves only a
+    value the pre-routing hook wrote while routing that hop.
+    """
+    if request_kwargs is None:
+        return
+    for bucket in (request_kwargs.get(name) for name in _ROUTER_METADATA_BUCKETS):
+        if isinstance(bucket, dict) and PRE_ROUTING_SELECTED_MODEL_KEY in bucket:
+            del bucket[PRE_ROUTING_SELECTED_MODEL_KEY]
+
+
+def get_pre_routing_selection(kwargs: Mapping[str, Any]) -> str | None:
+    """The model a pre-routing hook selected for this request, if one did."""
+    buckets: Final = (kwargs.get(name) for name in _ROUTER_METADATA_BUCKETS)
+    selections: Final = (bucket.get(PRE_ROUTING_SELECTED_MODEL_KEY) for bucket in buckets if isinstance(bucket, dict))
+    return next((selected for selected in selections if isinstance(selected, str) and selected), None)
+
+
+def fallback_lookup_groups(kwargs: Mapping[str, Any], model_group: str | None) -> tuple[str, ...]:
+    """
+    Ordered keys for resolving a fallback chain: the tier a pre-routing hook selected wins,
+    and the requested group still resolves when no tier-keyed chain exists, so configs keyed
+    on the router name (the documented contract) keep working behind auto-routers.
+    """
+    ordered: Final = (get_pre_routing_selection(kwargs), model_group)
+    return tuple(dict.fromkeys(group for group in ordered if group))
+
+
+def _resolved_a_specific_chain(
+    fallbacks: list[Any],  # mutable-ok: mirrors get_fallback_model_group's contract
+    result: tuple[list[str] | None, int | None],  # mutable-ok: mirrors get_fallback_model_group's contract
+) -> bool:
+    resolved, generic_idx = result
+    if resolved is None:
+        return False
+    return generic_idx is None or resolved is not fallbacks[generic_idx]["*"]
+
+
+def get_fallback_model_group_for_lookup_groups(
+    fallbacks: list[Any],  # mutable-ok: mirrors get_fallback_model_group's contract
+    lookup_groups: tuple[str, ...],
+) -> tuple[list[str] | None, int | None]:  # mutable-ok: mirrors get_fallback_model_group's contract
+    """
+    First lookup group with a specifically-keyed chain wins; the generic "*" chain applies
+    only after every group missed, so a catch-all cannot shadow a later group's own chain.
+    """
+    results: Final = tuple(get_fallback_model_group(fallbacks=fallbacks, model_group=group) for group in lookup_groups)
+    specific: Final = next((result for result in results if _resolved_a_specific_chain(fallbacks, result)), None)
+    if specific is not None:
+        return specific
+    return next((result for result in results if result[0] is not None), (None, None))
+
+
 def get_fallback_model_group(fallbacks: list[Any], model_group: str) -> tuple[list[str] | None, int | None]:
     """
     Returns:
diff --git a/litellm/router_utils/search_api_router.py b/litellm/router_utils/search_api_router.py
index d96defbbcd6..ab5ef5853c9 100644
--- a/litellm/router_utils/search_api_router.py
+++ b/litellm/router_utils/search_api_router.py
@@ -9,6 +9,7 @@ import random
 import traceback
 from collections.abc import Callable
 from functools import partial
+from types import MappingProxyType
 from typing import Any, Final
 
 from litellm._logging import verbose_router_logger
@@ -214,6 +215,15 @@ class SearchAPIRouter:
             api_key, api_base = SearchAPIRouter._resolve_search_provider_credentials(
                 tool_litellm_params=litellm_params,
             )
+            protected_params: Final = frozenset(("search_provider", "api_key", "api_base"))
+            search_params: Final = MappingProxyType(
+                {
+                    key: value
+                    for params in (litellm_params, kwargs)
+                    for key, value in params.items()
+                    if key not in protected_params and value is not None
+                }
+            )
 
             verbose_router_logger.debug("Selected search tool with provider: %s", search_provider)
 
@@ -222,7 +232,7 @@ class SearchAPIRouter:
                 search_provider=search_provider,
                 api_key=api_key,
                 api_base=api_base,
-                **kwargs,
+                **search_params,
             )
 
             return response
diff --git a/litellm/search/cost_calculator.py b/litellm/search/cost_calculator.py
index 84461115e8e..21f27075e0f 100644
--- a/litellm/search/cost_calculator.py
+++ b/litellm/search/cost_calculator.py
@@ -2,16 +2,37 @@
 Cost calculation for search providers.
 """
 
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import Final
 
+from pydantic import TypeAdapter, ValidationError
+
 from litellm.utils import get_model_info
 
+PROVIDER_USAGE_ADAPTER: Final[TypeAdapter[tuple[Mapping[str, object], ...]]] = TypeAdapter(
+    tuple[Mapping[str, object], ...]
+)
+EMPTY_OPTIONAL_PARAMS: Final[Mapping[str, object]] = MappingProxyType({})
+
+
+def _provider_usage(
+    optional_params: Mapping[str, object] | None,
+    usage_param: str,
+) -> tuple[Mapping[str, object], ...] | None:
+    params: Final = optional_params if optional_params is not None else EMPTY_OPTIONAL_PARAMS
+    raw_usage: Final[object] = params.get(usage_param)
+    try:
+        return PROVIDER_USAGE_ADAPTER.validate_python(raw_usage)
+    except ValidationError:
+        return None
+
 
 def search_provider_cost_per_query(
     model: str,
     custom_llm_provider: str | None = None,
     number_of_queries: int = 1,
-    optional_params: dict | None = None,
+    optional_params: Mapping[str, object] | None = None,
 ) -> tuple[float, float]:
     """
     Calculate cost for search-only providers.
@@ -28,6 +49,18 @@ def search_provider_cost_per_query(
     Returns:
         Tuple of (input_cost, output_cost) where output_cost is always 0.0
     """
+    if custom_llm_provider == "parallel_ai":
+        from litellm.llms.parallel_ai.search.cost_calculator import (
+            PARALLEL_AI_USAGE_PARAM,
+            parallel_ai_search_cost,
+        )
+
+        input_cost: Final = parallel_ai_search_cost(
+            optional_params=optional_params if optional_params is not None else EMPTY_OPTIONAL_PARAMS,
+            usage=_provider_usage(optional_params, PARALLEL_AI_USAGE_PARAM),
+        )
+        return (input_cost, 0.0)
+
     model_info: Final = get_model_info(model=model, custom_llm_provider=custom_llm_provider)
 
     # Check for tiered pricing (e.g., Exa AI based on max_results)
diff --git a/litellm/types/integrations/datadog_llm_obs.py b/litellm/types/integrations/datadog_llm_obs.py
index 7853dda1213..bae876dfdd9 100644
--- a/litellm/types/integrations/datadog_llm_obs.py
+++ b/litellm/types/integrations/datadog_llm_obs.py
@@ -4,21 +4,58 @@ Payloads for Datadog LLM Observability Service (LLMObs)
 API Reference: https://docs.datadoghq.com/llm_observability/setup/api/?tab=example#api-standards
 """
 
+from collections.abc import Sequence
 from typing import Any, Literal
 
-from typing_extensions import TypedDict
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm.types.integrations.custom_logger import StandardCustomLoggerInitParams
 
 
+class ToolCall(TypedDict, total=False):
+    """A tool call on a message, as LLM Obs names its fields."""
+
+    name: ReadOnly[str]
+    arguments: ReadOnly[dict[str, Any] | str]  # parsed object, or the raw string when it will not parse to one
+    tool_id: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class ToolResult(TypedDict, total=False):
+    """The result of a tool call, as LLM Obs names its fields."""
+
+    name: ReadOnly[str]
+    result: ReadOnly[str]
+    tool_id: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class ToolDefinition(TypedDict, total=False):
+    """A tool the model was offered on the request."""
+
+    name: ReadOnly[str]
+    description: ReadOnly[str]
+    schema: ReadOnly[dict[str, Any]]
+
+
+class Message(TypedDict, total=False):
+    """A message on a span, as LLM Obs names its fields."""
+
+    content: ReadOnly[str]
+    role: ReadOnly[str]
+    reasoning_content: ReadOnly[str]
+    tool_calls: ReadOnly[Sequence[ToolCall]]
+    tool_results: ReadOnly[Sequence[ToolResult]]
+
+
 class InputMeta(TypedDict):
-    messages: list[
-        dict[str, Any]  # changed to fit with tool calls
+    messages: Sequence[
+        Message | dict[str, Any]  # changed to fit with tool calls
     ]  # Relevant Issue: https://github.com/BerriAI/litellm/issues/9494
 
 
 class OutputMeta(TypedDict):
-    messages: list[Any]
+    messages: Sequence[Any]
 
 
 class DDLLMObsError(TypedDict, total=False):
@@ -36,6 +73,7 @@ class Meta(TypedDict, total=False):
     output: OutputMeta  # The span's output information.
     metadata: dict[str, Any]
     error: DDLLMObsError | None  # Error information on the span
+    tool_definitions: ReadOnly[Sequence[ToolDefinition]]  # The tools offered to the model on this request
 
 
 class LLMMetrics(TypedDict, total=False):
@@ -45,6 +83,9 @@ class LLMMetrics(TypedDict, total=False):
     time_to_first_token: float
     time_per_output_token: float
     total_cost: float
+    cache_read_input_tokens: ReadOnly[float]
+    cache_write_input_tokens: ReadOnly[float]
+    non_cached_input_tokens: ReadOnly[float]
 
 
 class LLMObsPayload(TypedDict, total=False):
diff --git a/litellm/types/integrations/prometheus.py b/litellm/types/integrations/prometheus.py
index 01ed8b08571..8498b6f6d00 100644
--- a/litellm/types/integrations/prometheus.py
+++ b/litellm/types/integrations/prometheus.py
@@ -270,6 +270,10 @@ DEFINED_PROMETHEUS_METRICS = Literal[
     "litellm_deployment_rpm_limit",
     "litellm_remaining_api_key_requests_for_model",
     "litellm_remaining_api_key_tokens_for_model",
+    "litellm_api_key_rate_limit_allowed_metric",
+    "litellm_api_key_rate_limit_used_metric",
+    "litellm_team_rate_limit_allowed_metric",
+    "litellm_team_rate_limit_used_metric",
     "litellm_llm_api_failed_requests_metric",
     "litellm_callback_logging_failures_metric",
     "litellm_in_flight_requests",
@@ -775,6 +779,22 @@ class PrometheusMetricLabels:
         UserAPIKeyLabelNames.MODEL_ID.value,
     ]
 
+    litellm_api_key_rate_limit_allowed_metric: ClassVar[tuple[str, ...]] = (
+        UserAPIKeyLabelNames.API_KEY_HASH.value,
+        UserAPIKeyLabelNames.API_KEY_ALIAS.value,
+        UserAPIKeyLabelNames.RATE_LIMIT_TYPE.value,
+    )
+
+    litellm_api_key_rate_limit_used_metric = litellm_api_key_rate_limit_allowed_metric
+
+    litellm_team_rate_limit_allowed_metric: ClassVar[tuple[str, ...]] = (
+        UserAPIKeyLabelNames.TEAM.value,
+        UserAPIKeyLabelNames.TEAM_ALIAS.value,
+        UserAPIKeyLabelNames.RATE_LIMIT_TYPE.value,
+    )
+
+    litellm_team_rate_limit_used_metric = litellm_team_rate_limit_allowed_metric
+
     litellm_llm_api_failed_requests_metric = [
         UserAPIKeyLabelNames.END_USER.value,
         UserAPIKeyLabelNames.API_KEY_HASH.value,
diff --git a/litellm/types/llms/anthropic_messages/anthropic_response.py b/litellm/types/llms/anthropic_messages/anthropic_response.py
index 42ca3fd6d4b..4fe1dafc73b 100644
--- a/litellm/types/llms/anthropic_messages/anthropic_response.py
+++ b/litellm/types/llms/anthropic_messages/anthropic_response.py
@@ -78,6 +78,16 @@ class AnthropicUsage(TypedDict, total=False):
     server_tool_use: NotRequired[ReadOnly[ServerToolUsage]]
 
 
+class AnthropicStopDetails(TypedDict, total=False):
+    """
+    Safeguard verdict accompanying a `stop_reason: "refusal"` response:
+    https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback
+    """
+
+    category: ReadOnly[str | None]
+    explanation: ReadOnly[str | None]
+
+
 class AnthropicMessagesResponse(TypedDict, total=False):
     """
     Anthropic Messages API Response: https://docs.anthropic.com/en/api/messages
@@ -90,7 +100,8 @@ class AnthropicMessagesResponse(TypedDict, total=False):
     id: str
     model: str | None  # This represents the Model type from Anthropic
     role: Literal["assistant"] | None
-    stop_reason: Literal["end_turn", "max_tokens", "stop_sequence", "tool_use"] | None
+    stop_reason: Literal["end_turn", "max_tokens", "stop_sequence", "tool_use", "refusal"] | None
+    stop_details: NotRequired[ReadOnly[AnthropicStopDetails | None]]
     stop_sequence: str | None
     type: Literal["message"] | None
     usage: AnthropicUsage | None
diff --git a/litellm/types/proxy/management_endpoints/scim_v2.py b/litellm/types/proxy/management_endpoints/scim_v2.py
index 1612ea03817..7825684cfe5 100644
--- a/litellm/types/proxy/management_endpoints/scim_v2.py
+++ b/litellm/types/proxy/management_endpoints/scim_v2.py
@@ -150,6 +150,12 @@ class SCIMGroup(SCIMResource):
     members: list[SCIMMember] | None = None
 
 
+class SCIMPlaceholderMergeResult(BaseModel):
+    placeholder_user_id: str
+    merged_into_user_id: str
+    team_ids: tuple[str, ...]
+
+
 # SCIM List Response Models
 class SCIMListResponse(BaseModel):
     schemas: list[str] = ["urn:ietf:params:scim:api:messages:2.0:ListResponse"]
diff --git a/litellm/types/proxy/public_endpoints/public_endpoints.py b/litellm/types/proxy/public_endpoints/public_endpoints.py
index f6ee054ceaa..c7f80a61e0f 100644
--- a/litellm/types/proxy/public_endpoints/public_endpoints.py
+++ b/litellm/types/proxy/public_endpoints/public_endpoints.py
@@ -43,6 +43,8 @@ class AgentCredentialField(BaseModel):
     options: list[str] | None = None
     default_value: str | None = None
     include_in_litellm_params: bool | None = None
+    validation_pattern: str | None = None
+    validation_message: str | None = None
 
 
 class AgentCreateInfo(BaseModel):
diff --git a/litellm/types/router.py b/litellm/types/router.py
index e0957383aac..2a5f264cee3 100644
--- a/litellm/types/router.py
+++ b/litellm/types/router.py
@@ -106,6 +106,20 @@ class RetryPolicy(BaseModel):
     InternalServerErrorRetries: int | None = None
 
 
+OptionalPreCallChecks = list[
+    Literal[
+        "prompt_caching",
+        "router_budget_limiting",
+        "responses_api_deployment_check",
+        "deployment_affinity",
+        "session_affinity",
+        "forward_client_headers_by_model_group",
+        "enforce_model_rate_limits",
+        "encrypted_content_affinity",
+    ]
+]
+
+
 class UpdateRouterConfig(BaseModel):
     """
     Set of params that you can modify via `router.update_settings()`.
@@ -128,6 +142,7 @@ class UpdateRouterConfig(BaseModel):
     model_group_alias: dict[str, str | dict] | None = {}
     enable_tag_filtering: bool | None = None
     tag_routing_prefix: str | None = None
+    optional_pre_call_checks: OptionalPreCallChecks | None = None
 
     model_config = ConfigDict(protected_namespaces=())
 
@@ -869,20 +884,6 @@ class FallbackAccessCheck(Protocol):
     async def __call__(self, *, model: str, request_kwargs: Mapping[str, object], llm_router: "Router") -> bool: ...
 
 
-OptionalPreCallChecks = list[
-    Literal[
-        "prompt_caching",
-        "router_budget_limiting",
-        "responses_api_deployment_check",
-        "deployment_affinity",
-        "session_affinity",
-        "forward_client_headers_by_model_group",
-        "enforce_model_rate_limits",
-        "encrypted_content_affinity",
-    ]
-]
-
-
 class LiteLLM_RouterFileObject(TypedDict, total=False):
     """
     Tracking the litellm params hash, used for mapping the file id to the right model
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 3a0883b6607..5783a39b30c 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -3636,6 +3636,8 @@ all_litellm_params = (
         "client",
         "rpm",
         "tpm",
+        "default_api_key_rpm_limit",
+        "default_api_key_tpm_limit",
         "itpm",
         "otpm",
         "max_parallel_requests",
diff --git a/litellm/vector_stores/main.py b/litellm/vector_stores/main.py
index 89c3319ca5a..ade4d19815b 100644
--- a/litellm/vector_stores/main.py
+++ b/litellm/vector_stores/main.py
@@ -7,7 +7,7 @@ import builtins
 import contextvars
 from collections.abc import Coroutine, Mapping
 from functools import partial
-from typing import Final
+from typing import TYPE_CHECKING, Final
 
 import httpx
 
@@ -33,6 +33,9 @@ from litellm.types.vector_stores import (
 from litellm.utils import ProviderConfigManager, client
 from litellm.vector_stores.utils import VectorStoreRequestUtils
 
+if TYPE_CHECKING:
+    from litellm.router import Router
+
 ####### ENVIRONMENT VARIABLES ###################
 # Initialize any necessary instances or variables here
 base_llm_http_handler = BaseLLMHTTPHandler()
@@ -292,6 +295,7 @@ async def asearch(
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
+    router: "Router | None" = None,
     **kwargs,
 ) -> VectorStoreSearchResponse:
     """
@@ -326,6 +330,7 @@ async def asearch(
             timeout=timeout,
             custom_llm_provider=custom_llm_provider,
             _direct_vector_store_embedding_executor=embedding_executor,
+            router=router,
             **kwargs,
         )
 
@@ -365,6 +370,7 @@ def search(
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
+    router: "Router | None" = None,
     **kwargs,
 ) -> VectorStoreSearchResponse | Coroutine[object, object, VectorStoreSearchResponse]:
     """
@@ -473,6 +479,7 @@ def search(
             timeout=timeout or request_timeout,
             _is_async=_is_async,
             client=kwargs.get("client"),
+            router=router,
         )
 
         return response
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 55618d9f772..2846d12db6e 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -9643,7 +9643,8 @@
         "supported_endpoints": [
             "/v1/images/generations",
             "/v1/images/edits"
-        ]
+        ],
+        "deprecation_date": "2026-10-01"
     },
     "azure_ai/MAI-Image-2.5-Flash": {
         "input_cost_per_image_token": 1.75e-06,
@@ -9656,7 +9657,8 @@
         "supported_endpoints": [
             "/v1/images/generations",
             "/v1/images/edits"
-        ]
+        ],
+        "deprecation_date": "2026-10-01"
     },
     "azure_ai/MAI-Image-2e": {
         "deprecation_date": "2026-08-15",
@@ -10155,7 +10157,9 @@
         "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
         "supports_function_calling": true,
         "supports_reasoning": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "cache_read_input_token_cost": 1.45e-07,
+        "supports_prompt_caching": true
     },
     "azure_ai/deepseek-v4-flash": {
         "deprecation_date": "2028-02-20",
@@ -10169,18 +10173,20 @@
         "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
         "supports_function_calling": true,
         "supports_reasoning": true,
-        "supports_tool_choice": true
-    },
-    "azure_ai/deepseek-v4-flash-0731": {
+        "supports_tool_choice": true,
         "cache_read_input_token_cost": 2.8e-08,
+        "supports_prompt_caching": true
+    },
+    "azure_ai/DeepSeek-V4-Flash-0731": {
+        "cache_read_input_token_cost": 1.4e-08,
         "deprecation_date": "2026-12-03",
-        "input_cost_per_token": 1.9e-07,
+        "input_cost_per_token": 4.4e-07,
         "litellm_provider": "azure_ai",
         "max_input_tokens": 1000000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "mode": "chat",
-        "output_cost_per_token": 5.1e-07,
+        "output_cost_per_token": 1.32e-06,
         "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
         "supports_function_calling": true,
         "supports_prompt_caching": true,
@@ -10400,11 +10406,13 @@
         "max_tokens": 262144,
         "mode": "chat",
         "output_cost_per_token": 3e-06,
-        "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/kimi-k2-5-now-in-microsoft-foundry/4492321",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
         "supports_function_calling": true,
         "supports_tool_choice": true,
         "supports_video_input": true,
-        "supports_vision": true
+        "supports_vision": true,
+        "cache_read_input_token_cost": 1e-07,
+        "supports_prompt_caching": true
     },
     "azure_ai/kimi-k2.6": {
         "deprecation_date": "2027-04-16",
@@ -10415,7 +10423,7 @@
         "max_tokens": 262144,
         "mode": "chat",
         "output_cost_per_token": 4e-06,
-        "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-kimi-k2-6-in-microsoft-foundry/4513125",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
         "supported_modalities": [
             "text",
             "image"
@@ -10426,7 +10434,9 @@
         "supports_function_calling": true,
         "supports_reasoning": true,
         "supports_tool_choice": true,
-        "supports_vision": true
+        "supports_vision": true,
+        "cache_read_input_token_cost": 1.6e-07,
+        "supports_prompt_caching": true
     },
     "azure_ai/ministral-3b": {
         "input_cost_per_token": 4e-08,
@@ -12110,7 +12120,7 @@
         "max_output_tokens": 2048,
         "max_tokens": 2048,
         "mode": "chat",
-        "output_cost_per_token": 2.65e-06,
+        "output_cost_per_token": 6e-07,
         "supports_pdf_input": true
     },
     "bedrock/us-west-1/meta.llama3-70b-instruct-v1:0": {
@@ -23514,6 +23524,63 @@
         "web_search_billing_unit": "per_query",
         "google_maps_grounding_cost_per_query": 0.014
     },
+    "vertex_ai/gemini-3.8-flash": {
+        "prompt_cache_min_tokens": 4096,
+        "cache_read_input_token_cost": 7.5e-08,
+        "cache_read_input_token_cost_flex": 3.75e-08,
+        "input_cost_per_token": 7.5e-07,
+        "input_cost_per_token_batches": 3.75e-07,
+        "input_cost_per_token_flex": 3.75e-07,
+        "litellm_provider": "vertex_ai",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 3.75e-06,
+        "output_cost_per_token": 3.75e-06,
+        "output_cost_per_token_batches": 1.875e-06,
+        "output_cost_per_token_flex": 1.875e-06,
+        "regional_endpoint_uplift_multiplier": 1.1,
+        "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/completions",
+            "/v1/batch"
+        ],
+        "supported_modalities": [
+            "text",
+            "image",
+            "audio",
+            "video"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_audio_input": true,
+        "supports_function_calling": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_url_context": true,
+        "supports_video_input": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_native_streaming": true,
+        "input_cost_per_token_priority": 1.35e-06,
+        "output_cost_per_token_priority": 6.75e-06,
+        "cache_read_input_token_cost_priority": 1.35e-07,
+        "search_context_cost_per_query": {
+            "search_context_size_low": 0.014,
+            "search_context_size_medium": 0.014,
+            "search_context_size_high": 0.014
+        },
+        "web_search_billing_unit": "per_query",
+        "google_maps_grounding_cost_per_query": 0.014
+    },
     "vertex_ai/gemini-3.1-pro-preview": {
         "prompt_cache_min_tokens": 4096,
         "cache_read_input_token_cost": 2e-07,
@@ -25351,6 +25418,65 @@
         "web_search_billing_unit": "per_query",
         "google_maps_grounding_cost_per_query": 0.014
     },
+    "gemini/gemini-3.8-flash": {
+        "prompt_cache_min_tokens": 4096,
+        "cache_read_input_token_cost": 7.5e-08,
+        "cache_read_input_token_cost_flex": 3.75e-08,
+        "input_cost_per_token": 7.5e-07,
+        "input_cost_per_token_batches": 3.75e-07,
+        "input_cost_per_token_flex": 3.75e-07,
+        "litellm_provider": "gemini",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 3.75e-06,
+        "output_cost_per_token": 3.75e-06,
+        "output_cost_per_token_batches": 1.875e-06,
+        "output_cost_per_token_flex": 1.875e-06,
+        "rpm": 2000,
+        "source": "https://ai.google.dev/gemini-api/docs/pricing",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/completions",
+            "/v1/batch"
+        ],
+        "supported_modalities": [
+            "text",
+            "image",
+            "audio",
+            "video"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_audio_output": false,
+        "supports_audio_input": true,
+        "supports_function_calling": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_url_context": true,
+        "supports_video_input": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_native_streaming": true,
+        "tpm": 800000,
+        "input_cost_per_token_priority": 1.35e-06,
+        "output_cost_per_token_priority": 6.75e-06,
+        "cache_read_input_token_cost_priority": 1.35e-07,
+        "search_context_cost_per_query": {
+            "search_context_size_low": 0.014,
+            "search_context_size_medium": 0.014,
+            "search_context_size_high": 0.014
+        },
+        "web_search_billing_unit": "per_query",
+        "google_maps_grounding_cost_per_query": 0.014
+    },
     "gemini/gemini-omni-flash-preview": {
         "input_cost_per_audio_token": 1.5e-06,
         "input_cost_per_token": 1.5e-06,
@@ -25759,6 +25885,63 @@
         "web_search_billing_unit": "per_query",
         "google_maps_grounding_cost_per_query": 0.014
     },
+    "gemini-3.8-flash": {
+        "prompt_cache_min_tokens": 4096,
+        "cache_read_input_token_cost": 7.5e-08,
+        "cache_read_input_token_cost_flex": 3.75e-08,
+        "input_cost_per_token": 7.5e-07,
+        "input_cost_per_token_batches": 3.75e-07,
+        "input_cost_per_token_flex": 3.75e-07,
+        "litellm_provider": "vertex_ai-language-models",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 3.75e-06,
+        "output_cost_per_token": 3.75e-06,
+        "output_cost_per_token_batches": 1.875e-06,
+        "output_cost_per_token_flex": 1.875e-06,
+        "source": "https://ai.google.dev/gemini-api/docs/pricing",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/completions",
+            "/v1/batch"
+        ],
+        "supported_modalities": [
+            "text",
+            "image",
+            "audio",
+            "video"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_audio_output": false,
+        "supports_audio_input": true,
+        "supports_function_calling": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_url_context": true,
+        "supports_video_input": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_native_streaming": true,
+        "input_cost_per_token_priority": 1.35e-06,
+        "output_cost_per_token_priority": 6.75e-06,
+        "cache_read_input_token_cost_priority": 1.35e-07,
+        "search_context_cost_per_query": {
+            "search_context_size_low": 0.014,
+            "search_context_size_medium": 0.014,
+            "search_context_size_high": 0.014
+        },
+        "web_search_billing_unit": "per_query",
+        "google_maps_grounding_cost_per_query": 0.014
+    },
     "gemini/gemini-2.5-pro-preview-tts": {
         "cache_read_input_token_cost": 1.25e-07,
         "input_cost_per_audio_token": 7e-07,
@@ -29098,16 +29281,19 @@
         "cache_creation_input_token_cost": 5e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1e-05,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 5e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
         "cache_creation_input_token_cost_flex": 2.5e-06,
         "cache_creation_input_token_cost_priority": 1e-05,
         "cache_read_input_token_cost": 4e-07,
         "cache_read_input_token_cost_above_272k_tokens": 8e-07,
         "cache_read_input_token_cost_above_272k_tokens_flex": 4e-07,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
         "cache_read_input_token_cost_flex": 2e-07,
         "cache_read_input_token_cost_priority": 8e-07,
         "input_cost_per_token": 4e-06,
         "input_cost_per_token_above_272k_tokens": 8e-06,
         "input_cost_per_token_above_272k_tokens_flex": 4e-06,
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
         "input_cost_per_token_batches": 2e-06,
         "input_cost_per_token_flex": 2e-06,
         "input_cost_per_token_priority": 8e-06,
@@ -29119,6 +29305,7 @@
         "output_cost_per_token": 2e-05,
         "output_cost_per_token_above_272k_tokens": 3e-05,
         "output_cost_per_token_above_272k_tokens_flex": 1.5e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
         "output_cost_per_token_batches": 1e-05,
         "output_cost_per_token_flex": 1e-05,
         "output_cost_per_token_priority": 4e-05,
@@ -29161,16 +29348,19 @@
         "cache_creation_input_token_cost": 5e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1e-05,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 5e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
         "cache_creation_input_token_cost_flex": 2.5e-06,
         "cache_creation_input_token_cost_priority": 1e-05,
         "cache_read_input_token_cost": 4e-07,
         "cache_read_input_token_cost_above_272k_tokens": 8e-07,
         "cache_read_input_token_cost_above_272k_tokens_flex": 4e-07,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
         "cache_read_input_token_cost_flex": 2e-07,
         "cache_read_input_token_cost_priority": 8e-07,
         "input_cost_per_token": 4e-06,
         "input_cost_per_token_above_272k_tokens": 8e-06,
         "input_cost_per_token_above_272k_tokens_flex": 4e-06,
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
         "input_cost_per_token_batches": 2e-06,
         "input_cost_per_token_flex": 2e-06,
         "input_cost_per_token_priority": 8e-06,
@@ -29182,6 +29372,7 @@
         "output_cost_per_token": 2e-05,
         "output_cost_per_token_above_272k_tokens": 3e-05,
         "output_cost_per_token_above_272k_tokens_flex": 1.5e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
         "output_cost_per_token_batches": 1e-05,
         "output_cost_per_token_flex": 1e-05,
         "output_cost_per_token_priority": 4e-05,
@@ -29225,16 +29416,19 @@
         "cache_creation_input_token_cost": 2.5e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 5e-06,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-05,
         "cache_creation_input_token_cost_flex": 1.25e-06,
         "cache_creation_input_token_cost_priority": 5e-06,
         "cache_read_input_token_cost": 2e-07,
         "cache_read_input_token_cost_above_272k_tokens": 4e-07,
         "cache_read_input_token_cost_above_272k_tokens_flex": 2e-07,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07,
         "cache_read_input_token_cost_flex": 1e-07,
         "cache_read_input_token_cost_priority": 4e-07,
         "input_cost_per_token": 2e-06,
         "input_cost_per_token_above_272k_tokens": 4e-06,
         "input_cost_per_token_above_272k_tokens_flex": 2e-06,
+        "input_cost_per_token_above_272k_tokens_priority": 8e-06,
         "input_cost_per_token_batches": 1e-06,
         "input_cost_per_token_flex": 1e-06,
         "input_cost_per_token_priority": 4e-06,
@@ -29246,6 +29440,7 @@
         "output_cost_per_token": 1.2e-05,
         "output_cost_per_token_above_272k_tokens": 1.8e-05,
         "output_cost_per_token_above_272k_tokens_flex": 9e-06,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-05,
         "output_cost_per_token_batches": 6e-06,
         "output_cost_per_token_flex": 6e-06,
         "output_cost_per_token_priority": 2.4e-05,
@@ -29288,16 +29483,19 @@
         "cache_creation_input_token_cost": 2.5e-07,
         "cache_creation_input_token_cost_above_272k_tokens": 5e-07,
         "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-07,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-06,
         "cache_creation_input_token_cost_flex": 1.25e-07,
         "cache_creation_input_token_cost_priority": 5e-07,
         "cache_read_input_token_cost": 2e-08,
         "cache_read_input_token_cost_above_272k_tokens": 4e-08,
         "cache_read_input_token_cost_above_272k_tokens_flex": 2e-08,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08,
         "cache_read_input_token_cost_flex": 1e-08,
         "cache_read_input_token_cost_priority": 4e-08,
         "input_cost_per_token": 2e-07,
         "input_cost_per_token_above_272k_tokens": 4e-07,
         "input_cost_per_token_above_272k_tokens_flex": 2e-07,
+        "input_cost_per_token_above_272k_tokens_priority": 8e-07,
         "input_cost_per_token_batches": 1e-07,
         "input_cost_per_token_flex": 1e-07,
         "input_cost_per_token_priority": 4e-07,
@@ -29309,6 +29507,7 @@
         "output_cost_per_token": 1.2e-06,
         "output_cost_per_token_above_272k_tokens": 1.8e-06,
         "output_cost_per_token_above_272k_tokens_flex": 9e-07,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-06,
         "output_cost_per_token_batches": 6e-07,
         "output_cost_per_token_flex": 6e-07,
         "output_cost_per_token_priority": 2.4e-06,
@@ -29548,7 +29747,10 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": false
+        "supports_minimal_reasoning_effort": false,
+        "input_cost_per_token_above_272k_tokens_flex": 5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 2.25e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07
     },
     "gpt-5.5-2026-04-23": {
         "cache_read_input_token_cost": 5e-07,
@@ -29602,7 +29804,10 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": false
+        "supports_minimal_reasoning_effort": false,
+        "input_cost_per_token_above_272k_tokens_flex": 5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 2.25e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07
     },
     "gpt-5.5-pro": {
         "cache_read_input_token_cost": 3e-06,
@@ -29751,7 +29956,10 @@
         "supports_none_reasoning_effort": true,
         "default_reasoning_effort": "none",
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 2.5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 1.125e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07
     },
     "gpt-5.4-2026-03-05": {
         "cache_read_input_token_cost": 2.5e-07,
@@ -29800,7 +30008,10 @@
         "supports_none_reasoning_effort": true,
         "default_reasoning_effort": "none",
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 2.5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 1.125e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07
     },
     "gpt-5.4-pro": {
         "cache_read_input_token_cost": 3e-06,
@@ -29849,7 +30060,9 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": false,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 3e-05,
+        "output_cost_per_token_above_272k_tokens_flex": 0.000135
     },
     "gpt-5.4-pro-2026-03-05": {
         "cache_read_input_token_cost": 3e-06,
@@ -29898,7 +30111,9 @@
         "supports_web_search": true,
         "supports_none_reasoning_effort": false,
         "supports_xhigh_reasoning_effort": true,
-        "supports_minimal_reasoning_effort": true
+        "supports_minimal_reasoning_effort": true,
+        "input_cost_per_token_above_272k_tokens_flex": 3e-05,
+        "output_cost_per_token_above_272k_tokens_flex": 0.000135
     },
     "gpt-5.4-mini": {
         "cache_read_input_token_cost": 7.5e-08,
@@ -30834,17 +31049,18 @@
     },
     "gpt-realtime-2": {
         "cache_creation_input_audio_token_cost": 4e-07,
+        "cache_read_input_audio_token_cost": 4e-07,
         "cache_read_input_token_cost": 4e-07,
         "input_cost_per_audio_token": 3.2e-05,
         "input_cost_per_image": 5e-06,
         "input_cost_per_token": 4e-06,
         "litellm_provider": "openai",
-        "max_input_tokens": 32000,
-        "max_output_tokens": 4096,
-        "max_tokens": 4096,
+        "max_input_tokens": 128000,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
         "mode": "realtime",
         "output_cost_per_audio_token": 6.4e-05,
-        "output_cost_per_token": 1.6e-05,
+        "output_cost_per_token": 2.4e-05,
         "supported_endpoints": [
             "/v1/realtime"
         ],
@@ -30908,8 +31124,8 @@
         "input_cost_per_token": 6e-07,
         "litellm_provider": "openai",
         "max_input_tokens": 128000,
-        "max_output_tokens": 4096,
-        "max_tokens": 4096,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
         "mode": "realtime",
         "output_cost_per_audio_token": 2e-05,
         "output_cost_per_token": 2.4e-06,
@@ -30941,7 +31157,7 @@
         "input_cost_per_audio_token": 1e-05,
         "input_cost_per_token": 6e-07,
         "litellm_provider": "openai",
-        "max_input_tokens": 128000,
+        "max_input_tokens": 32000,
         "max_output_tokens": 4096,
         "max_tokens": 4096,
         "mode": "realtime",
@@ -33705,19 +33921,21 @@
         "source": "https://mistral.ai/pricing#api-pricing"
     },
     "mistral/magistral-medium-latest": {
-        "input_cost_per_token": 2e-06,
+        "cache_read_input_token_cost": 1.5e-07,
+        "input_cost_per_token": 1.5e-06,
         "litellm_provider": "mistral",
-        "max_input_tokens": 40000,
-        "max_output_tokens": 40000,
-        "max_tokens": 40000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
-        "output_cost_per_token": 5e-06,
-        "source": "https://mistral.ai/news/magistral",
+        "output_cost_per_token": 7.5e-06,
+        "source": "https://docs.mistral.ai/models/model-cards/mistral-medium-3-5-26-04",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
         "supports_reasoning": true,
         "supports_response_schema": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "supports_vision": true
     },
     "mistral/magistral-small-2506": {
         "deprecation_date": "2025-11-30",
@@ -33736,19 +33954,21 @@
         "supports_tool_choice": true
     },
     "mistral/magistral-small-latest": {
-        "input_cost_per_token": 5e-07,
+        "cache_read_input_token_cost": 1.5e-08,
+        "input_cost_per_token": 1.5e-07,
         "litellm_provider": "mistral",
-        "max_input_tokens": 40000,
-        "max_output_tokens": 40000,
-        "max_tokens": 40000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
-        "output_cost_per_token": 1.5e-06,
-        "source": "https://mistral.ai/pricing#api-pricing",
+        "output_cost_per_token": 6e-07,
+        "source": "https://docs.mistral.ai/models/model-cards/mistral-small-4-0-26-03",
         "supports_assistant_prefill": true,
         "supports_function_calling": true,
         "supports_reasoning": true,
         "supports_response_schema": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "supports_vision": true
     },
     "mistral/magistral-small-1-2-2509": {
         "deprecation_date": "2026-07-31",
@@ -33880,16 +34100,21 @@
         "supports_vision": true
     },
     "mistral/mistral-medium": {
-        "input_cost_per_token": 2.7e-06,
+        "cache_read_input_token_cost": 1.5e-07,
+        "input_cost_per_token": 1.5e-06,
         "litellm_provider": "mistral",
-        "max_input_tokens": 32000,
-        "max_output_tokens": 8191,
-        "max_tokens": 8191,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
-        "output_cost_per_token": 8.1e-06,
+        "output_cost_per_token": 7.5e-06,
+        "source": "https://docs.mistral.ai/models/model-cards/mistral-medium-3-5-26-04",
         "supports_assistant_prefill": true,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
         "supports_response_schema": true,
-        "supports_tool_choice": true
+        "supports_tool_choice": true,
+        "supports_vision": true
     },
     "mistral/mistral-medium-2312": {
         "deprecation_date": "2025-06-16",
@@ -38556,12 +38781,22 @@
         "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
     },
     "parallel_ai/search": {
-        "input_cost_per_query": 0.004,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-fast": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
     "parallel_ai/search-pro": {
-        "input_cost_per_query": 0.009,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-turbo": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
@@ -41330,13 +41565,13 @@
         "source": "https://docs.together.ai/docs/serverless-models"
     },
     "together_ai/Qwen/Qwen3.8-2.4T-A95B": {
-        "cache_read_input_token_cost": 5e-07,
-        "input_cost_per_token": 2.5e-06,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 2e-06,
         "litellm_provider": "together_ai",
         "max_input_tokens": 1010000,
         "max_tokens": 1010000,
         "mode": "chat",
-        "output_cost_per_token": 6.25e-06,
+        "output_cost_per_token": 6e-06,
         "source": "https://docs.together.ai/docs/serverless-models",
         "supports_prompt_caching": true
     },
@@ -41946,6 +42181,70 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 1024
     },
+    "us-gov.anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "us-gov.anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
     "au.anthropic.claude-haiku-4-5-20251001-v1:0": {
         "cache_creation_input_token_cost": 1.375e-06,
         "cache_creation_input_token_cost_above_1hr": 2.2e-06,
@@ -45839,6 +46138,26 @@
         "mode": "rerank",
         "output_cost_per_token": 0.0
     },
+    "voyage/rerank-3": {
+        "input_cost_per_token": 5e-08,
+        "litellm_provider": "voyage",
+        "max_input_tokens": 32000,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
+        "mode": "rerank",
+        "output_cost_per_token": 0.0,
+        "source": "https://docs.voyageai.com/docs/pricing"
+    },
+    "voyage/rerank-3-lite": {
+        "input_cost_per_token": 2e-08,
+        "litellm_provider": "voyage",
+        "max_input_tokens": 32000,
+        "max_output_tokens": 32000,
+        "max_tokens": 32000,
+        "mode": "rerank",
+        "output_cost_per_token": 0.0,
+        "source": "https://docs.voyageai.com/docs/pricing"
+    },
     "voyage/voyage-2": {
         "input_cost_per_token": 1e-07,
         "litellm_provider": "voyage",
@@ -47090,6 +47409,27 @@
         "supports_vision": true,
         "supports_web_search": true
     },
+    "xai/grok-build-latest": {
+        "cache_read_input_token_cost": 3e-07,
+        "cache_read_input_token_cost_above_200k_tokens": 6e-07,
+        "input_cost_per_token": 2e-06,
+        "input_cost_per_token_above_200k_tokens": 4e-06,
+        "litellm_provider": "xai",
+        "max_input_tokens": 500000,
+        "max_output_tokens": 500000,
+        "max_tokens": 500000,
+        "mode": "chat",
+        "output_cost_per_token": 6e-06,
+        "output_cost_per_token_above_200k_tokens": 1.2e-05,
+        "source": "https://docs.x.ai/developers/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true
+    },
     "xai/grok-4.6": {
         "cache_read_input_token_cost": 5e-07,
         "cache_read_input_token_cost_above_200k_tokens": 1e-06,
@@ -57410,6 +57750,34 @@
         "supports_tool_choice": true,
         "supports_vision": false
     },
+    "fireworks_ai/accounts/fireworks/models/glm-5p3-flash": {
+        "cache_read_input_token_cost": 3e-08,
+        "input_cost_per_token": 1.5e-07,
+        "litellm_provider": "fireworks_ai",
+        "max_input_tokens": 1048576,
+        "max_tokens": 1048576,
+        "mode": "chat",
+        "output_cost_per_token": 5e-07,
+        "source": "https://docs.fireworks.ai/serverless/pricing",
+        "supports_function_calling": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "fireworks_ai/accounts/fireworks/models/inkling": {
+        "cache_read_input_token_cost": 1.7e-07,
+        "input_cost_per_token": 1e-06,
+        "litellm_provider": "fireworks_ai",
+        "max_input_tokens": 1048576,
+        "max_tokens": 1048576,
+        "mode": "chat",
+        "output_cost_per_token": 4.05e-06,
+        "source": "https://fireworks.ai/models/fireworks/inkling",
+        "supports_function_calling": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "fireworks_ai/accounts/fireworks/models/qwen3-embedding-8b": {
         "input_cost_per_token": 1e-07,
         "output_cost_per_token": 0.0,
@@ -57469,5 +57837,542 @@
         "supported_endpoints": [
             "/v1/audio/transcriptions"
         ]
+    },
+    "scaleway/glm-5.2": {
+        "input_cost_per_token": 1.8e-06,
+        "litellm_provider": "scaleway",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-06,
+        "source": "https://www.scaleway.com/en/pricing/model-as-a-service/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_vision": false
+    },
+    "scaleway/deepseek-v4-flash-0731": {
+        "cache_read_input_token_cost": 8e-08,
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "scaleway",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 8e-07,
+        "source": "https://www.scaleway.com/en/pricing/model-as-a-service/",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_vision": false
+    },
+    "azure_ai/kimi-k2.7-code": {
+        "cache_read_input_token_cost": 1.9e-07,
+        "deprecation_date": "2026-10-03",
+        "input_cost_per_token": 9.5e-07,
+        "litellm_provider": "azure_ai",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
+        "mode": "chat",
+        "output_cost_per_token": 4e-06,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-nano-3-30b": {
+        "input_cost_per_token": 7.2e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.88e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2": {
+        "input_cost_per_token": 2.4e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_system_messages": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 7.8e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0": {
+        "input_cost_per_token": 8.4e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3.6e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-west-1/anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b": {
+        "input_cost_per_token": 7.2e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.88e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-nano-12b-v2": {
+        "input_cost_per_token": 2.4e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_system_messages": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 7.8e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/openai.gpt-oss-20b-1:0": {
+        "input_cost_per_token": 8.4e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3.6e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/openai.gpt-oss-120b-1:0": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-east-1/anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-terra": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 2.64e-06,
+        "input_cost_per_token_above_272k_tokens": 5.28e-06,
+        "cache_creation_input_token_cost": 3.3e-06,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-06,
+        "cache_read_input_token_cost": 2.64e-07,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-07,
+        "output_cost_per_token": 1.584e-05,
+        "output_cost_per_token_above_272k_tokens": 2.376e-05
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-luna": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 2.64e-07,
+        "input_cost_per_token_above_272k_tokens": 5.28e-07,
+        "cache_creation_input_token_cost": 3.3e-07,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-07,
+        "cache_read_input_token_cost": 2.64e-08,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-08,
+        "output_cost_per_token": 1.584e-06,
+        "output_cost_per_token_above_272k_tokens": 2.376e-06
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.4": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 3.3e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "output_cost_per_token": 1.98e-05
+    },
+    "bedrock_mantle/us-gov-west-1/xai.grok-4.3": {
+        "use_openai_responses_path": true,
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "input_cost_per_token": 1.5e-06,
+        "output_cost_per_token": 3e-06,
+        "cache_read_input_token_cost": 2.4e-07
+    },
+    "bedrock_mantle/us-gov-east-1/openai.gpt-5.4": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 3.3e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "output_cost_per_token": 1.98e-05
+    },
+    "azure/us-gov/gpt-5.1": {
+        "cache_read_input_token_cost": 1.71875e-07,
+        "default_reasoning_effort": "none",
+        "input_cost_per_token": 1.71875e-06,
+        "litellm_provider": "azure",
+        "max_input_tokens": 272000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.375e-05,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/batch",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text",
+            "image"
+        ],
+        "supports_function_calling": true,
+        "supports_native_streaming": true,
+        "supports_none_reasoning_effort": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "azure/us-gov/o3-mini": {
+        "cache_read_input_token_cost": 7.57e-07,
+        "input_cost_per_token": 1.513e-06,
+        "litellm_provider": "azure",
+        "max_input_tokens": 200000,
+        "max_output_tokens": 100000,
+        "max_tokens": 100000,
+        "mode": "chat",
+        "output_cost_per_token": 6.05e-06,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": false
+    },
+    "azure/us-gov/text-embedding-3-large": {
+        "input_cost_per_token": 1.63e-07,
+        "litellm_provider": "azure",
+        "max_input_tokens": 8191,
+        "max_tokens": 8191,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0
+    },
+    "azure/us-gov/text-embedding-3-small": {
+        "input_cost_per_token": 2.5e-08,
+        "litellm_provider": "azure",
+        "max_input_tokens": 8191,
+        "max_tokens": 8191,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0
+    },
+    "cloudflare/@cf/openai/whisper": {
+        "input_cost_per_second": 7.5e-06,
+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper/",
+        "supported_endpoints": [
+            "/v1/audio/transcriptions"
+        ]
+    },
+    "cloudflare/@cf/openai/whisper-large-v3-turbo": {
+        "input_cost_per_second": 8.5e-06,
+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper-large-v3-turbo/",
+        "supported_endpoints": [
+            "/v1/audio/transcriptions"
+        ]
     }
 }
diff --git a/pyproject.toml b/pyproject.toml
index 2866e27e84c..60162544612 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -161,7 +161,7 @@ proxy-runtime = [
     "mangum>=0.17.0,<1.0",
     "azure-ai-contentsafety>=1.0.0,<2.0",
     "azure-storage-file-datalake>=12.20.0,<13.0",
-    "pypdf>=6.12.0,<7.0",
+    "pypdf>=6.16.1,<7.0",
     "llm-sandbox>=0.3.39,<1.0",
     "detect-secrets>=1.5.0,<2.0",
 ]
@@ -292,7 +292,7 @@ exclude = [
 
 [tool.uv]
 constraint-dependencies = [
-    "tornado>=6.5.6",
+    "tornado>=6.5.8",
     "aiohttp>=3.14.2,<4.0",
     "packaging>=24.0",
     "soupsieve>=2.8.4",
diff --git a/rust-toolchain.toml b/rust-toolchain.toml
new file mode 100644
index 00000000000..a1598ccbb34
--- /dev/null
+++ b/rust-toolchain.toml
@@ -0,0 +1,4 @@
+[toolchain]
+channel = "1.98.0"
+profile = "minimal"
+components = ["rustfmt", "clippy"]
diff --git a/tests/e2e/junit_properties.py b/tests/e2e/junit_properties.py
index e4f59f5c4d2..c5971c5362c 100644
--- a/tests/e2e/junit_properties.py
+++ b/tests/e2e/junit_properties.py
@@ -2,10 +2,16 @@
 
 The e2e suite ships results to Loki/Grafana from a standard pytest JUnit report
 (`--junitxml=e2e-report.xml`), not a bespoke log line. JUnit already records
-outcome, duration, and node id for every `<testcase>`; the only signals it cannot
-derive on its own are the normalized suite package and the coverage-registry cell
-ids a test covers. Those ride along as JUnit `<property>` entries via each item's
-`user_properties`, attached in `conftest.py::pytest_collection_modifyitems`.
+outcome, duration, and node id for every `<testcase>`; the signals it cannot
+derive on its own are the normalized suite package, the coverage-registry cell
+ids a test covers, and where the test's source lives. Those ride along as JUnit
+`<property>` entries via each item's `user_properties`, attached in
+`conftest.py::pytest_collection_modifyitems`.
+
+`source` is a property rather than the `file=` / `line=` attributes pytest used
+to write, because the `xunit2` family this suite runs on drops those, and
+switching families would change the XML for every consumer of it -- the
+Buildkite Test Engine upload and the Loki pipeline included.
 """
 
 from __future__ import annotations
@@ -14,22 +20,61 @@ from collections.abc import Iterable
 
 import pytest
 
+# Hardcoded because the runner image copies tests/e2e/ to /app/e2e, so nothing
+# at runtime names this suite's place in the repo. test_junit_properties.py
+# fails from a checkout if it moves.
+SUITE_ROOT = "tests/e2e"
+
+
+def suite_parts(path_part: str) -> tuple[str, ...]:
+    """Path components of a suite file relative to tests/e2e, however it ran.
+
+    Pytest paths are rootdir-relative, and rootdir moves with the invocation: a
+    repo-root run gives `tests/e2e/logging/test_x.py`, a suite-cwd run (the
+    runner image) gives `logging/test_x.py`. Both collapse to the same tuple.
+    """
+    raw = tuple(p for p in path_part.replace("\\", "/").split("/") if p and p != ".")
+    return raw[2:] if len(raw) >= 3 and raw[0] == "tests" and raw[1] == "e2e" else raw
+
 
 def package_from_nodeid(nodeid: str) -> str:
-    """Top-level suite package under tests/e2e/, or 'root' for top-level files.
-
-    Pytest nodeids are relative to the invocation cwd. Repo-root runs look like
-    `tests/e2e/logging/...`; suite-cwd runs look like `logging/...`. Strip the
-    `tests/e2e` prefix so package is the suite dir either way.
-    """
-    path_part = nodeid.split("::", 1)[0].replace("\\", "/")
-    raw = tuple(p for p in path_part.split("/") if p and p != ".")
-    parts = raw[2:] if len(raw) >= 3 and raw[0] == "tests" and raw[1] == "e2e" else raw
+    """Top-level suite package under tests/e2e/, or 'root' for top-level files."""
+    parts = suite_parts(nodeid.split("::", 1)[0])
     if len(parts) <= 1:
         return "root"
     return parts[0]
 
 
+def source_from_location(path: str, lineno: int | None) -> str:
+    """Repo-relative `path:line` for a test, or '' when nothing is linkable.
+
+    `pytest.Item.location` gives a rootdir-relative path and a ZERO-based line.
+    The path is re-rooted at SUITE_ROOT so consumers need not know how pytest was
+    started, and the line is emitted ONE-based to match editors, tracebacks and
+    code hosts. A decorated test anchors at its first decorator, which is where
+    pytest reports it.
+
+    Empty rather than a guess for anything unlinkable: no line, a path reaching
+    upward, or a path carrying a colon, which is both how an absolute Windows
+    path arrives and a character `path:line` has no way to represent.
+    """
+    if lineno is None:
+        return ""
+    normalized = path.replace("\\", "/")
+    if normalized.startswith("/") or ":" in normalized or ".." in normalized.split("/"):
+        return ""
+    parts = suite_parts(normalized)
+    if not parts:
+        return ""
+    return f"{'/'.join((SUITE_ROOT, *parts))}:{lineno + 1}"
+
+
+def source_from_item(item: pytest.Item) -> str:
+    """Read the repo-relative `path:line` off a pytest Item's reported location."""
+    path, lineno, _ = item.location
+    return source_from_location(path, lineno)
+
+
 def dedupe_covers(marker_args: Iterable[tuple[object, ...]]) -> tuple[str, ...]:
     """Flatten @pytest.mark.covers arg lists into unique, order-preserving cell
     ids, dropping anything that is not a non-empty string."""
@@ -43,10 +88,12 @@ def covers_from_item(item: pytest.Item) -> tuple[str, ...]:
 
 def result_properties(item: pytest.Item) -> tuple[tuple[str, str], ...]:
     """The custom signals a standard reporter cannot derive: the normalized suite
-    package and the comma-joined coverage-registry cell ids this test covers."""
+    package, the comma-joined coverage-registry cell ids this test covers, and the
+    repo-relative `path:line` its source sits at."""
     return (
         ("package", package_from_nodeid(item.nodeid)),
         ("covers", ",".join(covers_from_item(item))),
+        ("source", source_from_item(item)),
     )
 
 
diff --git a/tests/e2e/models.py b/tests/e2e/models.py
index 967144dfb16..79d9e011f7e 100644
--- a/tests/e2e/models.py
+++ b/tests/e2e/models.py
@@ -806,6 +806,7 @@ class LiteLLMParamsBody(BaseModel):
     mock_response: str | None = None
     timeout: float | None = None
     tpm: int | None = None
+    weight: int | None = None
 
 
 ModelMode = Literal["batch", "realtime", "image_generation"]
@@ -820,6 +821,7 @@ class ModelInfoBody(BaseModel):
     mode: ModelMode | None = None
     access_groups: list[str] | None = None
     team_id: str | None = None
+    allowed_fails_policy: dict[str, int] | None = None
 
 
 class ModelNewBody(BaseModel):
diff --git a/tests/e2e/router/reliability_support.py b/tests/e2e/router/reliability_support.py
index e342aa363ca..5822058003c 100644
--- a/tests/e2e/router/reliability_support.py
+++ b/tests/e2e/router/reliability_support.py
@@ -19,6 +19,8 @@ from models import (
     ChatMessage,
     ChatResponse,
     LiteLLMParamsBody,
+    ModelInfoBody,
+    ModelNewBody,
     ReliabilityChatBody,
     RouterSettingsOverride,
 )
@@ -26,6 +28,18 @@ from models import (
 REAL_MODEL = "openai/gpt-5.5"
 REAL_KEY = "os.environ/OPENAI_API_KEY"
 
+# The smallest-context chat model OpenAI still serves (16385 tokens). A prompt
+# past that limit comes back as a real `context_length_exceeded` 400, which is
+# what litellm maps to ContextWindowExceededError.
+SMALL_CONTEXT_MODEL = "openai/gpt-3.5-turbo"
+SMALL_CONTEXT_LIMIT_TOKENS = 16385
+
+
+def oversized_prompt(marker: str) -> str:
+    """A prompt comfortably past SMALL_CONTEXT_MODEL's context limit, so the
+    provider refuses it on length rather than answering a truncated version."""
+    return f"{marker} " + ("token " * (SMALL_CONTEXT_LIMIT_TOKENS + 4000))
+
 
 def create_bad_base_deployment(proxy: ProxyClient, name: str) -> str:
     """Register a deployment pointing at an unreachable base, so every call to it
@@ -40,6 +54,38 @@ def create_timeout_deployment(proxy: ProxyClient, name: str) -> str:
     return proxy.create_model(name, LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, timeout=0.001))
 
 
+def create_small_context_deployment(proxy: ProxyClient, name: str) -> str:
+    """Register a deployment on the smallest-context model OpenAI still serves, so an
+    oversized prompt earns a real context-window refusal from the provider."""
+    return proxy.create_model(name, LiteLLMParamsBody(model=SMALL_CONTEXT_MODEL, api_key=REAL_KEY))
+
+
+def create_always_timing_out_deployment(proxy: ProxyClient, name: str) -> str:
+    """The always-picked half of a retry pair: a 1ms deadline the backend always
+    exceeds, all of the model group's shuffle weight, and a cooldown policy that
+    benches it on its first Timeout so the retry cannot land on it again."""
+    return proxy.register_model(
+        ModelNewBody(
+            model_name=name,
+            litellm_params=LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, timeout=0.001, weight=1),
+            model_info=ModelInfoBody(allowed_fails_policy={"TimeoutErrorAllowedFails": 0}),
+        )
+    )
+
+
+def create_zero_weight_backup_deployment(proxy: ProxyClient, name: str) -> str:
+    """The other half of a retry pair: healthy, but weight 0, so the weighted shuffle
+    never opens on it. It is reachable only once its sibling is benched and the
+    weighted pick falls through to a uniform one over what is left."""
+    return proxy.register_model(
+        ModelNewBody(
+            model_name=name,
+            litellm_params=LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, weight=0),
+            model_info=ModelInfoBody(),
+        )
+    )
+
+
 def chat_override(
     proxy: ProxyClient,
     key: str,
diff --git a/tests/e2e/router/test_reliability_fallbacks_e2e.py b/tests/e2e/router/test_reliability_fallbacks_e2e.py
index d3ce62f8f95..8cece41ce2d 100644
--- a/tests/e2e/router/test_reliability_fallbacks_e2e.py
+++ b/tests/e2e/router/test_reliability_fallbacks_e2e.py
@@ -9,6 +9,10 @@ in the x-litellm-attempted-fallbacks header. Empty content is accepted only when
 `finish_reason == "length"` and the response billed completion tokens, since
 gpt-5.5 counts reasoning against max_tokens and can consume the whole budget
 before emitting any text; a fallback that produced nothing at all still fails.
+
+The context-window case is a different reroute from a plain failure: the provider
+refuses the prompt on length, and `context_window_fallbacks` is the setting that
+reroutes it, not `fallbacks`.
 """
 
 from __future__ import annotations
@@ -25,8 +29,10 @@ from reliability_support import (
     completion_tokens_of,
     content_of,
     create_bad_base_deployment,
+    create_small_context_deployment,
     create_timeout_deployment,
     finish_reason_of,
+    oversized_prompt,
     reasoning_tokens_of,
 )
 
@@ -82,3 +88,17 @@ class TestReliabilityFallbacks:
             override=RouterSettingsOverride(fallbacks=[{primary: ["gpt-5.5"]}]),
         )
         _assert_served_by_fallback(resp)
+
+    @pytest.mark.covers("reliability.fallback.context_window.routes_to_fallback")
+    def test_context_window_routes_to_fallback(
+        self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str
+    ) -> None:
+        primary = f"reliability-ctxfail-{unique_marker()}"
+        model_id = create_small_context_deployment(client.proxy, primary)
+        resources.defer(lambda: client.proxy.delete_model(model_id))
+
+        resp = chat_override(
+            client.proxy, scoped_key, primary, oversized_prompt(unique_marker()),
+            override=RouterSettingsOverride(context_window_fallbacks=[{primary: ["gpt-5.5"]}]),
+        )
+        _assert_served_by_fallback(resp)
diff --git a/tests/e2e/router/test_reliability_retries_e2e.py b/tests/e2e/router/test_reliability_retries_e2e.py
new file mode 100644
index 00000000000..5441412935c
--- /dev/null
+++ b/tests/e2e/router/test_reliability_retries_e2e.py
@@ -0,0 +1,73 @@
+"""Live e2e: a request that fails on its first deployment is retried inside its own
+model group and still comes back a completion.
+
+The model group is a pair: an always-timing-out deployment that holds all of the
+group's shuffle weight, and a healthy backup at weight 0. The weighted pick always
+opens on the timing-out one, its first Timeout benches it (an
+`allowed_fails_policy` of `TimeoutErrorAllowedFails: 0`), and the retry falls
+through to the only deployment left. So the customer sees a completion and the
+proxy reports that it took a retry to get there, with no random first pick in the
+middle of it.
+"""
+
+from __future__ import annotations
+
+import pytest
+
+from complexity_router_client import ComplexityRouterClient
+from e2e_config import unique_marker
+from lifecycle import ResourceManager
+from models import RouterSettingsOverride
+from reliability_support import (
+    chat_override,
+    completion_tokens_of,
+    content_of,
+    create_always_timing_out_deployment,
+    create_zero_weight_backup_deployment,
+    finish_reason_of,
+)
+
+pytestmark = pytest.mark.e2e
+
+
+class TestReliabilityRetries:
+    @pytest.mark.covers("reliability.retry.timeout.succeeds_within_retries")
+    def test_timeout_on_first_deployment_succeeds_on_retry(
+        self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str
+    ) -> None:
+        group = f"reliability-retry-{unique_marker()}"
+        timing_out = create_always_timing_out_deployment(client.proxy, group)
+        resources.defer(lambda: client.proxy.delete_model(timing_out))
+        backup = create_zero_weight_backup_deployment(client.proxy, group)
+        resources.defer(lambda: client.proxy.delete_model(backup))
+
+        resp = chat_override(
+            client.proxy,
+            scoped_key,
+            group,
+            f"say hi {unique_marker()}",
+            override=RouterSettingsOverride(num_retries=2),
+        )
+
+        assert resp.status_code == 200, (
+            f"the retry should have landed on the healthy backup, got {resp.status_code}: {resp.body[:300]}"
+        )
+
+        attempted = resp.headers.get("x-litellm-attempted-retries")
+        assert attempted is not None, "response is missing the x-litellm-attempted-retries header"
+        assert int(attempted) >= 1, (
+            f"x-litellm-attempted-retries is {attempted!r}; a 200 with no retry means the request never "
+            "opened on the timing-out deployment, so this proves nothing about retries"
+        )
+
+        content = content_of(resp)
+        finish_reason = finish_reason_of(resp)
+        completion_tokens = completion_tokens_of(resp) or 0
+        assert isinstance(content, str), (
+            f"the retry should have returned a completion body, got content {content!r} (body={resp.body[:300]})"
+        )
+        assert content or (finish_reason == "length" and completion_tokens > 0), (
+            f"the retry returned empty content with finish_reason={finish_reason!r}, "
+            f"completion_tokens={completion_tokens}; empty content is only acceptable when the budget "
+            f"was spent on non-visible reasoning (body={resp.body[:300]})"
+        )
diff --git a/tests/e2e/test_junit_properties.py b/tests/e2e/test_junit_properties.py
new file mode 100644
index 00000000000..02c1413c840
--- /dev/null
+++ b/tests/e2e/test_junit_properties.py
@@ -0,0 +1,131 @@
+"""Harness coverage for the custom JUnit properties.
+
+No proxy and no ``e2e`` marker. Pins the two normalizations that have to agree
+about where a suite file lives -- ``package_from_nodeid`` (strip the suite root)
+and ``source_from_location`` (re-root at it) -- across both ways the suite is
+launched, plus the one-based line offset and the refusal to emit a path that
+escapes the suite. The consumers of these properties are the Loki/Grafana
+rollups and, for ``source``, the status page's per-test links to GitHub.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import pytest
+from junit_properties import (
+    SUITE_ROOT,
+    attach_result_properties,
+    dedupe_covers,
+    package_from_nodeid,
+    result_properties,
+    source_from_location,
+    suite_parts,
+)
+
+
+def collected_item(request: pytest.FixtureRequest, name: str) -> pytest.Item:
+    """The Item pytest collected for test ``name`` in this file: the real nodeid,
+    location and marker machinery the collection hook reads, as pytest built it."""
+    return next(item for item in request.session.items if item.path == request.path and item.name == name)
+
+
+def repo_root() -> Path | None:
+    """The litellm checkout above this file, or None when there isn't one."""
+    return next((p for p in Path(__file__).resolve().parents if (p / ".git").exists()), None)
+
+
+class TestSuiteParts:
+    @pytest.mark.parametrize(
+        "path",
+        ["logging/test_x.py", "tests/e2e/logging/test_x.py", "./logging/test_x.py", "tests\\e2e\\logging\\test_x.py"],
+    )
+    def test_both_invocation_shapes_collapse_to_the_same_components(self, path: str) -> None:
+        """A repo-root run and a suite-cwd run report the same file differently;
+        every downstream signal has to see one spelling."""
+        assert suite_parts(path) == ("logging", "test_x.py")
+
+    def test_top_level_suite_file_keeps_its_single_component(self) -> None:
+        assert suite_parts("tests/e2e/test_fixture_mode.py") == ("test_fixture_mode.py",)
+
+
+class TestPackageFromNodeid:
+    @pytest.mark.parametrize(
+        ("nodeid", "expected"),
+        [
+            ("logging/test_x.py::TestFoo::test_bar", "logging"),
+            ("tests/e2e/logging/test_x.py::TestFoo::test_bar", "logging"),
+            ("quota_management/spend_tracking/test_x.py::test_bar", "quota_management"),
+            ("test_fixture_mode.py::TestParseFixtureMode::test_known_values_normalize", "root"),
+            ("tests/e2e/test_fixture_mode.py::test_bar", "root"),
+        ],
+    )
+    def test_package_is_the_first_dir_under_the_suite_root(self, nodeid: str, expected: str) -> None:
+        assert package_from_nodeid(nodeid) == expected
+
+
+class TestSourceFromLocation:
+    @pytest.mark.parametrize("path", ["a2a/test_a2a_agent_e2e.py", "tests/e2e/a2a/test_a2a_agent_e2e.py"])
+    def test_path_is_repo_relative_however_pytest_was_started(self, path: str) -> None:
+        assert source_from_location(path, 40) == "tests/e2e/a2a/test_a2a_agent_e2e.py:41"
+
+    def test_line_is_emitted_one_based(self) -> None:
+        """pytest.Item.location counts from 0; editors, tracebacks and GitHub's
+        #L anchor all count from 1, and an off-by-one lands on the decorator."""
+        assert source_from_location("a2a/test_x.py", 0) == "tests/e2e/a2a/test_x.py:1"
+
+    def test_top_level_suite_file_sits_directly_under_the_suite_root(self) -> None:
+        assert source_from_location("test_fixture_mode.py", 39) == "tests/e2e/test_fixture_mode.py:40"
+
+    @pytest.mark.parametrize(
+        ("path", "lineno"),
+        [
+            ("a2a/test_x.py", None),
+            ("/app/e2e/a2a/test_x.py", 40),
+            ("C:\\app\\e2e\\a2a\\test_x.py", 40),
+            ("../conftest.py", 40),
+            ("", 40),
+        ],
+    )
+    def test_nothing_linkable_yields_empty_rather_than_a_guess(self, path: str, lineno: int | None) -> None:
+        """A colon is rejected on two counts: it is how a Windows absolute path
+        arrives, and `path:line` cannot represent one in the path half."""
+        assert source_from_location(path, lineno) == ""
+
+
+class TestResultProperties:
+    def test_every_test_carries_package_covers_and_source(self, request: pytest.FixtureRequest) -> None:
+        """Read off this test's own collected Item, so the nodeid and location are
+        whatever pytest reports for the launch shape in use, and the marker is added
+        at run time so the coverage registry's collect-only pass never sees it."""
+        test = type(self).test_every_test_carries_package_covers_and_source
+        request.applymarker(pytest.mark.covers("LOG-1", "LOG-2"))
+        assert result_properties(collected_item(request, test.__name__)) == (
+            ("package", "root"),
+            ("covers", "LOG-1,LOG-2"),
+            ("source", f"tests/e2e/test_junit_properties.py:{test.__code__.co_firstlineno}"),
+        )
+
+    def test_attach_is_idempotent(self, request: pytest.FixtureRequest) -> None:
+        """Collection can run the hook more than once; a second pass must not
+        double the <property> entries in the report."""
+        item = collected_item(request, type(self).test_attach_is_idempotent.__name__)
+        attach_result_properties(item)
+        attach_result_properties(item)
+        assert [name for name, _ in item.user_properties] == ["package", "covers", "source"]
+
+
+class TestSuiteRoot:
+    def test_suite_root_names_this_file_s_real_home(self) -> None:
+        """SUITE_ROOT is hardcoded because the runner image has no repo to read it
+        from. Where there IS a checkout, prove the constant still points at us --
+        otherwise a moved tests/e2e/ ships links that 404."""
+        root = repo_root()
+        if root is None:
+            pytest.skip("no checkout above this file (the runner image copies tests/e2e/ to /app/e2e)")
+        assert (root / SUITE_ROOT / Path(__file__).name).resolve() == Path(__file__).resolve()
+
+
+class TestDedupeCovers:
+    def test_ids_are_unique_order_preserving_and_non_empty_strings(self) -> None:
+        assert dedupe_covers([("A", "B"), ("B", ""), ("C", 7)]) == ("A", "B", "C")
diff --git a/tests/llm_responses_api_testing/test_responses_hooks.py b/tests/llm_responses_api_testing/test_responses_hooks.py
index 66dbb29dba5..a86752c0172 100644
--- a/tests/llm_responses_api_testing/test_responses_hooks.py
+++ b/tests/llm_responses_api_testing/test_responses_hooks.py
@@ -841,7 +841,7 @@ def test_build_synthetic_response_events_covers_annotations_function_calls_and_r
     )
 
     try:
-        events = streaming_module._build_synthetic_response_events(
+        events = streaming_module.build_synthetic_response_events(
             transformed=transformed,
             logging_obj=logging_obj,
             chunk_size=5,
diff --git a/tests/ocr_tests/test_ocr_vertex_ai.py b/tests/ocr_tests/test_ocr_vertex_ai.py
index 1ba5b9d0883..1842eb063a5 100644
--- a/tests/ocr_tests/test_ocr_vertex_ai.py
+++ b/tests/ocr_tests/test_ocr_vertex_ai.py
@@ -5,9 +5,11 @@ Note: Vertex AI OCR automatically converts URLs to base64 data URIs since
 the Vertex AI endpoint doesn't have internet access.
 """
 
-import os
 import json
+import os
 import tempfile
+from typing import Final
+
 import pytest
 from base_ocr_unit_tests import BaseOCRTest
 
@@ -139,3 +141,19 @@ def test_vertex_ai_ocr_routing():
     assert isinstance(
         deepseek_variant, VertexAIDeepSeekOCRConfig
     ), "DeepSeek variant should route to VertexAIDeepSeekOCRConfig"
+
+
+@pytest.mark.parametrize("model", ("deepseek-ocr-maas", "deepseek-ai/deepseek-ocr-maas"))
+def test_deepseek_request_uses_single_provider_namespace(model: str) -> None:
+    from litellm.llms.vertex_ai.ocr.deepseek_transformation import (
+        VertexAIDeepSeekOCRConfig,
+    )
+
+    request: Final = VertexAIDeepSeekOCRConfig().transform_ocr_request(
+        model=model,
+        document={"type": "image_url", "image_url": "data:image/png;base64,AA=="},
+        optional_params={},
+        headers={},
+    )
+
+    assert request.data["model"] == "deepseek-ai/deepseek-ocr-maas"
diff --git a/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py b/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py
new file mode 100644
index 00000000000..ed21734c5fc
--- /dev/null
+++ b/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py
@@ -0,0 +1,58 @@
+"""Image-level check that the built proxy image can import the Bedrock realtime SDK.
+
+Bedrock Nova Sonic (`/v1/realtime`) imports `aws_sdk_bedrock_runtime` lazily on the
+first session, so an image whose `uv sync` stages skip the `bedrock-realtime` extra
+boots, passes health checks, and then fails every Nova Sonic session with
+"Missing aws_sdk_bedrock_runtime". Importing inside the built image is what catches
+that class of regression (missing extra, lockfile drift, a stage that syncs a
+different set of extras), which a static Dockerfile check cannot.
+
+Gated on LITELLM_IMAGE like the other image checks in this directory; exercised
+where an image has been built (the image-scan workflow). Requires a working docker CLI.
+"""
+
+import os
+import shutil
+import subprocess
+from typing import Final
+
+import pytest
+
+IMAGE: Final = os.getenv("LITELLM_IMAGE")
+NON_ROOT_UID: Final = "12345:0"
+IMPORT_PROBE: Final = "import aws_sdk_bedrock_runtime, smithy_aws_core; print('bedrock-realtime ok')"
+
+pytestmark = [
+    pytest.mark.skipif(IMAGE is None, reason="requires a built image (set LITELLM_IMAGE)"),
+    pytest.mark.skipif(shutil.which("docker") is None, reason="requires the docker CLI"),
+]
+
+
+def test_image_imports_bedrock_realtime_sdk():
+    assert IMAGE is not None
+
+    probe: Final = subprocess.run(
+        [
+            "docker",
+            "run",
+            "--rm",
+            "--network",
+            "none",
+            "--user",
+            NON_ROOT_UID,
+            "--entrypoint",
+            "python",
+            IMAGE,
+            "-c",
+            IMPORT_PROBE,
+        ],
+        capture_output=True,
+        text=True,
+        check=False,
+    )
+
+    assert probe.returncode == 0 and "bedrock-realtime ok" in probe.stdout, (
+        f"{IMAGE} cannot import aws_sdk_bedrock_runtime as uid {NON_ROOT_UID}, so Bedrock Nova Sonic "
+        "/v1/realtime sessions fail with 'Missing aws_sdk_bedrock_runtime'. Is `--extra bedrock-realtime` "
+        f"passed to every `uv sync` in its Dockerfile?\nstdout:\n{probe.stdout}\nstderr:\n{probe.stderr}"
+    )
diff --git a/tests/proxy_migration_tests/test_prisma_toolchain.py b/tests/proxy_migration_tests/test_prisma_toolchain.py
index d12a2c4dd4e..733870f3239 100644
--- a/tests/proxy_migration_tests/test_prisma_toolchain.py
+++ b/tests/proxy_migration_tests/test_prisma_toolchain.py
@@ -7,26 +7,36 @@ attempt fails identically. These tests pin the two behaviours that keep a
 container recoverable: an incomplete cache is deleted before Prisma is
 invoked, and the install gets a budget of its own rather than sharing the one
 that bounds each migration command.
+
+``prisma migrate deploy`` gets a budget of its own for the same reason: its
+runtime grows with the number of pending migrations, so a fresh database that
+replays every migration overran the per-command budget on slow machines and
+the proxy gave up after four identical timeouts.
 """
 
 import ast
 import json
+import logging
 import os
 import sys
 import time
+from collections.abc import Callable
 from pathlib import Path
 
 import pytest
 
 from litellm_proxy_extras.prisma_toolchain import (
     DEFAULT_PRISMA_COMMAND_TIMEOUT,
+    DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT,
     PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR,
     PRISMA_COMMAND_TIMEOUT_ENV_VAR,
+    PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR,
     ensure_prisma_toolchain,
     heal_incomplete_nodeenv_cache,
     node_binary_path,
     prisma_bootstrap_timeout,
     prisma_command_timeout,
+    prisma_migrate_deploy_timeout,
 )
 from litellm_proxy_extras.utils import ProxyExtrasDBManager
 
@@ -42,14 +52,27 @@ import time
 
 args = sys.argv[1:]
 cache_dir = os.environ["PRISMA_NODEENV_CACHE_DIR"]
-with pathlib.Path(os.environ["FAKE_PRISMA_LOG"]).open("a") as log:
+log_path = pathlib.Path(os.environ["FAKE_PRISMA_LOG"])
+earlier_same_command = sum(
+    1
+    for line in (log_path.read_text().splitlines() if log_path.exists() else [])
+    if json.loads(line)["args"][:2] == args[:2]
+)
+with log_path.open("a") as log:
     log.write(
         json.dumps({{"args": args, "cache_dir_present": os.path.isdir(cache_dir)}})
         + "\\n"
     )
 time.sleep(float(os.environ.get("FAKE_PRISMA_SLEEP", "0")))
 if args[:2] == ["migrate", "deploy"]:
+    if earlier_same_command == 0:
+        time.sleep(float(os.environ.get("FAKE_PRISMA_FIRST_DEPLOY_SLEEP", "0")))
+    elif os.environ.get("FAKE_PRISMA_LATER_DEPLOY_STDERR"):
+        print(os.environ["FAKE_PRISMA_LATER_DEPLOY_STDERR"], file=sys.stderr)
+        sys.exit(1)
     print("No pending migrations to apply")
+if args[:2] == ["db", "push"] and earlier_same_command == 0:
+    time.sleep(float(os.environ.get("FAKE_PRISMA_FIRST_PUSH_SLEEP", "0")))
 sys.exit(0)
 """
 
@@ -80,9 +103,14 @@ def toolchain_env(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> tuple[Path
     monkeypatch.setenv("PATH", f"{bin_dir}{os.pathsep}{os.environ['PATH']}")
     monkeypatch.delenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, raising=False)
     monkeypatch.delenv(PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR, raising=False)
+    monkeypatch.delenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, raising=False)
     return cache_dir, log_path
 
 
+def _deploy_calls(log_path: Path) -> list[list[str]]:
+    return [call["args"] for call in _fake_prisma_calls(log_path) if call["args"][:2] == ["migrate", "deploy"]]
+
+
 def _make_incomplete_cache(cache_dir: Path) -> None:
     (cache_dir / "lib").mkdir(parents=True)
     (cache_dir / "bin").mkdir()
@@ -209,25 +237,111 @@ def test_setup_database_prepares_the_toolchain_before_migrating(
     assert calls[0]["cache_dir_present"] is False
 
 
+@pytest.mark.parametrize("use_v2_resolver", [False, True], ids=["v1", "v2"])
+def test_migrate_deploy_is_not_bounded_by_the_per_command_timeout(
+    toolchain_env: tuple[Path, Path],
+    monkeypatch: pytest.MonkeyPatch,
+    use_v2_resolver: bool,
+) -> None:
+    """A fresh database replays every migration, which takes longer than any bookkeeping command."""
+    _, log_path = toolchain_env
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, "1")
+    monkeypatch.setenv("FAKE_PRISMA_FIRST_DEPLOY_SLEEP", "3")
+
+    assert ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=use_v2_resolver) is True
+    assert _deploy_calls(log_path) == [["migrate", "deploy"]]
+
+
+def test_migrate_deploy_stops_at_its_own_timeout(
+    toolchain_env: tuple[Path, Path], monkeypatch: pytest.MonkeyPatch
+) -> None:
+    """The deploy budget still bounds a deploy that hangs, so boot cannot wait forever."""
+    _, log_path = toolchain_env
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, "1")
+    monkeypatch.setenv("FAKE_PRISMA_FIRST_DEPLOY_SLEEP", "60")
+    monkeypatch.setenv("FAKE_PRISMA_LATER_DEPLOY_STDERR", "Error: P3018 permission denied for schema public")
+
+    started = time.monotonic()
+    with pytest.raises(RuntimeError, match="insufficient permissions"):
+        ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+    elapsed = time.monotonic() - started
+
+    assert len(_deploy_calls(log_path)) == 2
+    assert elapsed < 30
+
+
+def test_db_push_timeout_hint_names_the_per_command_budget(
+    toolchain_env: tuple[Path, Path], monkeypatch: pytest.MonkeyPatch, caplog: pytest.LogCaptureFixture
+) -> None:
+    """``db push`` keeps the per-command budget, so its timeout hint has to name that variable."""
+    _, log_path = toolchain_env
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, "1")
+    monkeypatch.setenv("FAKE_PRISMA_FIRST_PUSH_SLEEP", "3")
+
+    with caplog.at_level(logging.WARNING, logger="litellm_proxy_extras"):
+        assert ProxyExtrasDBManager.setup_database(use_migrate=False, use_v2_resolver=False) is True
+
+    assert [call["args"][:2] for call in _fake_prisma_calls(log_path)].count(["db", "push"]) == 2
+    assert [record.getMessage() for record in caplog.records if "timed out" in record.getMessage()] == [
+        f"Attempt 1 timed out. Raise {PRISMA_COMMAND_TIMEOUT_ENV_VAR} if this database needs longer to apply its schema."
+    ]
+
+
+@pytest.mark.parametrize(
+    ("command_timeout", "deploy_timeout", "expected"),
+    [
+        ("900", None, 900.0),
+        ("12", None, DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT),
+        ("900", "1200", 1200.0),
+        ("900", "300", 300.0),
+    ],
+    ids=["raised_command_budget_carries_over", "lowered_command_budget_does_not", "override_wins_upward", "override_wins_downward"],
+)
+def test_migrate_deploy_budget_keeps_a_raised_command_budget(
+    command_timeout: str, deploy_timeout: str | None, expected: float, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    """Deployments that raised the per-command budget to survive a long deploy keep that budget for deploy."""
+    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, command_timeout)
+    if deploy_timeout is None:
+        monkeypatch.delenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, raising=False)
+    else:
+        monkeypatch.setenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, deploy_timeout)
+
+    assert prisma_migrate_deploy_timeout() == expected
+
+
 @pytest.mark.parametrize(
     "raw",
     ["", "0", "-5", "not-a-number", "nan", "inf", "-inf", "1e400"],
 )
+@pytest.mark.parametrize(
+    ("env_var", "read_timeout", "default"),
+    [
+        (PRISMA_COMMAND_TIMEOUT_ENV_VAR, prisma_command_timeout, DEFAULT_PRISMA_COMMAND_TIMEOUT),
+        (PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, prisma_migrate_deploy_timeout, DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT),
+    ],
+    ids=["command", "migrate_deploy"],
+)
 def test_unusable_timeout_override_falls_back_to_the_default(
-    raw: str, monkeypatch: pytest.MonkeyPatch
+    raw: str, env_var: str, read_timeout: Callable[[], float], default: float, monkeypatch: pytest.MonkeyPatch
 ) -> None:
     """A non-finite override would silently disable the timeout it configures."""
-    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, raw)
+    monkeypatch.setenv(env_var, raw)
 
-    assert prisma_command_timeout() == DEFAULT_PRISMA_COMMAND_TIMEOUT
+    assert read_timeout() == default
 
 
 def test_timeout_overrides_are_independent(monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, "12")
     monkeypatch.setenv(PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR, "900")
+    monkeypatch.setenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, "1200")
 
     assert prisma_command_timeout() == 12
     assert prisma_bootstrap_timeout() == 900
+    assert prisma_migrate_deploy_timeout() == 1200
 
 
 @pytest.mark.parametrize("module", ["utils.py", "replica_identity.py"])
diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py
index 47554913419..54cce9cdd78 100644
--- a/tests/proxy_unit_tests/test_proxy_server.py
+++ b/tests/proxy_unit_tests/test_proxy_server.py
@@ -3076,7 +3076,9 @@ async def test_update_config_success_callback_normalization():
     admin_user = UserAPIKeyAuth(
         user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-test"
     )
-    await proxy_server.update_config(config_update, user_api_key_dict=admin_user)
+    request = MagicMock()
+    request.json = AsyncMock(return_value={"litellm_settings": {"success_callback": ["SQS", "sQs"]}})
+    await proxy_server.update_config(config_update, request=request, user_api_key_dict=admin_user)
 
     assert (
         "litellm_settings" in upserted
diff --git a/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py b/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py
index 3785ccdcfba..096efc33aaf 100644
--- a/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py
+++ b/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py
@@ -1,3 +1,5 @@
+import asyncio
+from types import MappingProxyType
 from unittest.mock import AsyncMock, patch
 
 
@@ -5,6 +7,7 @@ import pytest
 
 import litellm
 from litellm.caching.caching import DualCache
+from litellm.caching.redis_cache import RedisCache
 from datetime import datetime, timezone
 
 from litellm.litellm_core_utils.duration_parser import duration_in_seconds
@@ -1332,3 +1335,85 @@ async def test_the_user_scope_has_no_pre_upgrade_counter_to_carry():
         await limiter.is_user_within_model_budget(
             user_id="u1", user_model_max_budget=model_max_budget, model="openai/gpt-4"
         )
+
+
+class _SharedFakeRedis(RedisCache):
+    """Stand-in for the one Redis every replica's DualCache is attached to.
+
+    Only the methods the limiter and DualCache call are implemented, and
+    ``super().__init__`` is skipped so no connection is opened.
+    """
+
+    def __init__(self):
+        self._store = MappingProxyType({})
+
+    async def async_set_cache(self, key, value, **kwargs):
+        self._store = MappingProxyType({**self._store, key: value})
+
+    async def async_get_cache(self, key, **kwargs):
+        return self._store.get(key)
+
+    async def async_batch_get_cache(self, key_list, **kwargs):
+        return {key: self._store.get(key) for key in key_list}
+
+    async def async_increment_pipeline(self, increment_list, **kwargs):
+        for op in increment_list:
+            total = self._store.get(op["key"], 0.0) + op["increment_value"]
+            self._store = MappingProxyType({**self._store, op["key"]: total})
+        return [self._store[op["key"]] for op in increment_list]
+
+
+async def _log_spend(limiter, *, key_hash, model_max_budget, response_cost):
+    await limiter.async_log_success_event(
+        _success_kwargs(
+            model_group="gpt-4",
+            response_cost=response_cost,
+            key_hash=key_hash,
+            key_model_max_budget=model_max_budget,
+        ),
+        response_obj=None,
+        start_time=None,
+        end_time=None,
+    )
+    # The Redis push is scheduled as a task rather than awaited inline.
+    await asyncio.gather(*(t for t in asyncio.all_tasks() if t is not asyncio.current_task()))
+
+
+@pytest.mark.asyncio
+async def test_spend_logged_on_one_replica_is_enforced_and_reported_on_another():
+    """
+    Each replica increments its own in-memory copy of the per-model counter and
+    pushes the increment to the shared Redis, so only Redis holds the window's
+    total. A replica that has served part of the traffic must still enforce and
+    report the total, not its own share.
+
+    Regression: reads went to the in-memory tier first, so a replica whose local
+    copy sat under the cap kept admitting requests and /key/info on it reported
+    that local share, while the shared counter was already over the cap.
+    """
+    shared_redis = _SharedFakeRedis()
+    replica_a = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=DualCache(redis_cache=shared_redis))
+    replica_b = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=DualCache(redis_cache=shared_redis))
+    key_hash = "vk-shared"
+    model_max_budget = {"gpt-4": {"budget_limit": 1.0, "time_period": "30d"}}
+    user_api_key = UserAPIKeyAuth(token=key_hash, model_max_budget=model_max_budget)
+
+    await _log_spend(replica_b, key_hash=key_hash, model_max_budget=model_max_budget, response_cost=0.25)
+    await _log_spend(replica_a, key_hash=key_hash, model_max_budget=model_max_budget, response_cost=0.5)
+    await _log_spend(replica_a, key_hash=key_hash, model_max_budget=model_max_budget, response_cost=0.5)
+
+    with pytest.raises(litellm.BudgetExceededError):
+        await replica_b.is_key_within_model_budget(user_api_key, "gpt-4")
+
+    usage_on_b = await build_model_max_budget_usage(
+        entity_type=Litellm_EntityType.KEY,
+        entity_id=key_hash,
+        model_max_budget=model_max_budget,
+        cache=replica_b.dual_cache,
+    )
+    assert usage_on_b["gpt-4"]["current_spend"] == 1.25
+
+    # Control: a replica that never served this key reads the same total.
+    replica_c = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=DualCache(redis_cache=shared_redis))
+    with pytest.raises(litellm.BudgetExceededError):
+        await replica_c.is_key_within_model_budget(user_api_key, "gpt-4")
diff --git a/tests/router_unit_tests/test_router_anthropic_messages_fallback.py b/tests/router_unit_tests/test_router_anthropic_messages_fallback.py
new file mode 100644
index 00000000000..0c4d1dfc21e
--- /dev/null
+++ b/tests/router_unit_tests/test_router_anthropic_messages_fallback.py
@@ -0,0 +1,402 @@
+"""
+Unit tests for safeguard-refusal fallback on the /v1/messages router surface.
+
+An Anthropic safeguard refusal is an HTTP 200 whose body carries
+stop_reason "refusal" plus a stop_details object; the router converts it
+into a ContentPolicyViolationError so the content-policy fallback chain
+runs, but only when a matching fallback is configured. A plain refusal
+without stop_details, or any refusal with nothing configured, must reach
+the client byte-identical.
+
+The upstream is faked at the HTTP boundary by intercepting the third-party
+transport (httpx.AsyncClient.send), so requests run litellm's real
+transformation, allowlist, and streaming pipeline end to end.
+"""
+
+import json
+from typing import Any, AsyncIterator
+from unittest.mock import patch
+
+import httpx
+import pytest
+
+from litellm import Router
+from litellm.router_utils.fallback_event_handlers import (
+    PRE_ROUTING_SELECTED_MODEL_KEY,
+    record_pre_routing_selection,
+)
+
+REFUSAL_RESPONSE: dict[str, Any] = {
+    "id": "msg_refusal",
+    "type": "message",
+    "role": "assistant",
+    "model": "claude-fable-5",
+    "content": [],
+    "stop_reason": "refusal",
+    "stop_sequence": None,
+    "stop_details": {"category": "cyber", "explanation": "flagged"},
+    "usage": {"input_tokens": 25, "output_tokens": 1},
+}
+
+PLAIN_REFUSAL_RESPONSE: dict[str, Any] = {k: v for k, v in REFUSAL_RESPONSE.items() if k != "stop_details"}
+
+OK_RESPONSE: dict[str, Any] = {
+    "id": "msg_ok",
+    "type": "message",
+    "role": "assistant",
+    "model": "claude-opus-5",
+    "content": [{"type": "text", "text": "hello"}],
+    "stop_reason": "end_turn",
+    "stop_sequence": None,
+    "usage": {"input_tokens": 25, "output_tokens": 2},
+}
+
+
+def _sse(event: str, data: dict[str, Any]) -> bytes:
+    return f"event: {event}\ndata: {json.dumps(data)}\n\n".encode()
+
+
+REFUSAL_STREAM_FRAMES: tuple[bytes, ...] = (
+    _sse("message_start", {"type": "message_start", "message": {**REFUSAL_RESPONSE, "stop_reason": None}}),
+    _sse(
+        "message_delta",
+        {
+            "type": "message_delta",
+            "delta": {"stop_reason": "refusal", "stop_details": {"category": "cyber"}},
+            "usage": {"output_tokens": 1},
+        },
+    ),
+    _sse("message_stop", {"type": "message_stop"}),
+)
+
+OK_STREAM_FRAMES: tuple[bytes, ...] = (
+    _sse("message_start", {"type": "message_start", "message": {**OK_RESPONSE, "stop_reason": None}}),
+    _sse(
+        "content_block_delta",
+        {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "hello"}},
+    ),
+    _sse("message_stop", {"type": "message_stop"}),
+)
+
+
+def _split_frames_mid_data_line(frames: tuple[bytes, ...]) -> tuple[bytes, ...]:
+    """Split each frame's data line in half, modeling a transport chunk boundary."""
+    return tuple(part for frame in frames for part in (frame[: len(frame) // 2], frame[len(frame) // 2 :]))
+
+
+class _FrameStream(httpx.AsyncByteStream):
+    def __init__(self, frames: tuple[bytes, ...]) -> None:
+        self._frames = frames
+
+    async def __aiter__(self) -> AsyncIterator[bytes]:
+        for frame in self._frames:
+            yield frame
+
+    async def aclose(self) -> None:
+        return None
+
+
+class FakeAnthropicUpstream:
+    """Intercepts the third-party transport (httpx.AsyncClient.send): refuses on fable
+    models, answers on others. The router deliberately does not forward caller-injected
+    clients, so the transport is the seam that exercises the real litellm pipeline."""
+
+    def __init__(
+        self,
+        refusal_body: dict[str, Any] = REFUSAL_RESPONSE,
+        refusal_frames: tuple[bytes, ...] = REFUSAL_STREAM_FRAMES,
+    ) -> None:
+        self.refusal_body = refusal_body
+        self.refusal_frames = refusal_frames
+        self.calls: list[str] = []
+        self.bodies: list[dict[str, Any]] = []
+
+    async def send(self, request: httpx.Request, **kwargs: Any) -> httpx.Response:
+        body = json.loads(request.content or b"{}")
+        model = body.get("model", "")
+        self.calls.append(model)
+        self.bodies.append(body)
+        refuses = "fable" in model
+        if body.get("stream"):
+            frames = self.refusal_frames if refuses else OK_STREAM_FRAMES
+            return httpx.Response(
+                200,
+                stream=_FrameStream(frames),
+                headers={"content-type": "text/event-stream"},
+                request=request,
+            )
+        return httpx.Response(200, json=self.refusal_body if refuses else OK_RESPONSE, request=request)
+
+    def install(self):
+        async def _send(_client: httpx.AsyncClient, request: httpx.Request, **kwargs: Any) -> httpx.Response:
+            return await self.send(request, **kwargs)
+
+        return patch("httpx.AsyncClient.send", new=_send)
+
+
+FABLE_TIER = {
+    "model_name": "fable-tier",
+    "litellm_params": {"model": "anthropic/claude-fable-5", "api_key": "sk-test"},
+}
+OPUS_TARGET = {
+    "model_name": "opus-target",
+    "litellm_params": {"model": "anthropic/claude-opus-5", "api_key": "sk-test"},
+}
+
+
+def _router(content_policy_fallbacks: list | None) -> Router:
+    return Router(model_list=[FABLE_TIER, OPUS_TARGET], content_policy_fallbacks=content_policy_fallbacks)
+
+
+async def _collect(stream: AsyncIterator[bytes]) -> bytes:
+    return b"".join([chunk async for chunk in stream])
+
+
+@pytest.mark.asyncio
+async def test_non_streaming_refusal_with_fallback_row_returns_fallback_response():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    with fake.install():
+        response = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, messages=[{"role": "user", "content": "hi"}]
+        )
+
+    assert response["stop_reason"] == "end_turn"
+    assert response["id"] == "msg_ok"
+    assert len(fake.calls) == 2
+    assert "claude-opus-5" in fake.calls[1]
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "content_policy_fallbacks, upstream_body",
+    [
+        (None, REFUSAL_RESPONSE),
+        ([{"unrelated-group": ["opus-target"]}], REFUSAL_RESPONSE),
+        ([{"fable-tier": ["opus-target"]}], PLAIN_REFUSAL_RESPONSE),
+    ],
+    ids=["nothing-configured", "row-for-other-group", "refusal-without-stop-details"],
+)
+async def test_non_streaming_refusal_passes_through_untouched(content_policy_fallbacks, upstream_body):
+    fake = FakeAnthropicUpstream(refusal_body=upstream_body)
+    router = _router(content_policy_fallbacks=content_policy_fallbacks)
+
+    with fake.install():
+        response = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, messages=[{"role": "user", "content": "hi"}]
+        )
+
+    assert response["stop_reason"] == "refusal"
+    assert response.get("stop_details") == upstream_body.get("stop_details")
+    assert len(fake.calls) == 1
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_with_fallback_row_streams_fallback_frames():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"refusal"' not in body
+    assert b"text_delta" in body
+    assert len(fake.calls) == 2
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_split_across_chunks_still_falls_back():
+    fake = FakeAnthropicUpstream(refusal_frames=_split_frames_mid_data_line(REFUSAL_STREAM_FRAMES))
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"refusal"' not in body
+    assert b"text_delta" in body
+    assert len(fake.calls) == 2
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_without_fallback_row_passes_frames_through():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=None)
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"stop_reason": "refusal"' in body
+    assert b"stop_details" in body
+    assert len(fake.calls) == 1
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_on_routed_tier_matches_tier_keyed_row_without_inbound_metadata():
+    """The pre-routing hook's tier stamp must reach the mid-stream fallback lookup even when the
+    request carries no metadata bucket at all (the snapshot is taken before the request runs)."""
+    fake = FakeAnthropicUpstream()
+    smart_router = {
+        "model_name": "smart-router",
+        "litellm_params": {
+            "model": "auto_router/complexity_router",
+            "complexity_router_config": {
+                "tiers": {"SIMPLE": "fable-tier", "MEDIUM": "fable-tier", "COMPLEX": "fable-tier"}
+            },
+            "complexity_router_default_model": "fable-tier",
+        },
+        "model_info": {"id": "router-1", "db_model": True},
+    }
+    router = Router(
+        model_list=[FABLE_TIER, OPUS_TARGET, smart_router],
+        content_policy_fallbacks=[{"fable-tier": ["opus-target"]}],
+        ignore_invalid_deployments=True,
+    )
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="smart-router", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"refusal"' not in body
+    assert b"text_delta" in body
+    assert len(fake.calls) == 2
+
+
+@pytest.mark.asyncio
+async def test_caller_forged_tier_stamp_cannot_pick_the_streaming_fallback_chain():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=[{"forged-tier": ["opus-target"]}])
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier",
+            max_tokens=16,
+            stream=True,
+            messages=[{"role": "user", "content": "hi"}],
+            litellm_metadata={PRE_ROUTING_SELECTED_MODEL_KEY: "forged-tier"},
+        )
+        body = await _collect(stream)
+
+    assert b'"stop_reason": "refusal"' in body
+    assert len(fake.calls) == 1
+
+
+@pytest.mark.asyncio
+async def test_tier_stamp_never_reaches_provider_bound_metadata():
+    """On /v1/messages the top-level metadata dict is Anthropic's own request field, so the
+    routed-tier stamp must never appear in any upstream body even when the client sends one."""
+    fake = FakeAnthropicUpstream()
+    smart_router = {
+        "model_name": "smart-router",
+        "litellm_params": {
+            "model": "auto_router/complexity_router",
+            "complexity_router_config": {
+                "tiers": {"SIMPLE": "fable-tier", "MEDIUM": "fable-tier", "COMPLEX": "fable-tier"}
+            },
+            "complexity_router_default_model": "fable-tier",
+        },
+        "model_info": {"id": "router-1", "db_model": True},
+    }
+    router = Router(
+        model_list=[FABLE_TIER, OPUS_TARGET, smart_router],
+        content_policy_fallbacks=[{"fable-tier": ["opus-target"]}],
+        ignore_invalid_deployments=True,
+    )
+
+    with fake.install():
+        response = await router.aanthropic_messages(
+            model="smart-router",
+            max_tokens=16,
+            messages=[{"role": "user", "content": "hi"}],
+            metadata={"user_id": "u1"},
+        )
+
+    assert response["stop_reason"] == "end_turn"
+    assert len(fake.bodies) == 2
+    for body in fake.bodies:
+        assert body.get("metadata") == {"user_id": "u1"}
+
+
+def test_record_pre_routing_selection_writes_only_the_internal_bucket():
+    """The Anthropic request's own metadata field must never carry the tier stamp."""
+    kwargs = {"metadata": {"user_id": "u1"}, "litellm_metadata": {}}
+
+    record_pre_routing_selection(kwargs, "tier-x")
+
+    assert kwargs["litellm_metadata"] == {PRE_ROUTING_SELECTED_MODEL_KEY: "tier-x"}
+    assert kwargs["metadata"] == {"user_id": "u1"}
+
+
+def test_refusal_gate_keys_on_pre_routing_tier_stamp():
+    router = _router(content_policy_fallbacks=[{"tier-group": ["opus-target"]}])
+
+    def anthropic_messages(**kwargs: Any) -> None:
+        return None
+
+    refusal_kwargs = {"litellm_metadata": {PRE_ROUTING_SELECTED_MODEL_KEY: "tier-group"}}
+    assert (
+        router._should_raise_anthropic_refusal_error(
+            model="router-group",
+            original_generic_function=anthropic_messages,
+            response=dict(REFUSAL_RESPONSE),
+            kwargs=refusal_kwargs,
+        )
+        is True
+    )
+    assert (
+        router._should_raise_anthropic_refusal_error(
+            model="router-group",
+            original_generic_function=anthropic_messages,
+            response=dict(REFUSAL_RESPONSE),
+            kwargs={},
+        )
+        is False
+    )
+
+
+def test_has_content_policy_fallback_default_fallbacks_arm():
+    router = Router(model_list=[OPUS_TARGET], fallbacks=[{"*": ["opus-target"]}])
+
+    assert router._has_content_policy_fallback("any-group", {}) is True
+    assert router._has_content_policy_fallback("any-group", {"content_policy_fallbacks": [{"other": ["x"]}]}) is False
+
+
+def test_get_fallback_model_group_for_lookup_groups_orders_tier_before_requested():
+    router = _router(content_policy_fallbacks=None)
+    fallbacks = [{"tier1": ["backup-a"]}, {"smart-router": ["backup-b"]}]
+
+    assert router._get_fallback_model_group_for_lookup_groups(
+        fallbacks=fallbacks, lookup_groups=("tier1", "smart-router")
+    ) == ["backup-a"]
+    assert router._get_fallback_model_group_for_lookup_groups(
+        fallbacks=fallbacks, lookup_groups=("tier9", "smart-router")
+    ) == ["backup-b"]
+    assert router._get_fallback_model_group_for_lookup_groups(fallbacks=fallbacks, lookup_groups=()) is None
+
+
+def test_refusal_gate_ignores_other_generic_call_types():
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    def aresponses(**kwargs: Any) -> None:
+        return None
+
+    assert (
+        router._should_raise_anthropic_refusal_error(
+            model="fable-tier",
+            original_generic_function=aresponses,
+            response=dict(REFUSAL_RESPONSE),
+            kwargs={},
+        )
+        is False
+    )
diff --git a/tests/router_unit_tests/test_router_endpoints.py b/tests/router_unit_tests/test_router_endpoints.py
index d37af5b456a..a06aaa363ad 100644
--- a/tests/router_unit_tests/test_router_endpoints.py
+++ b/tests/router_unit_tests/test_router_endpoints.py
@@ -1324,6 +1324,98 @@ async def test_init_containers_api_endpoints_managed_id_without_model_id_applies
     assert call_kw["custom_llm_provider"] == "azure"
 
 
+@pytest.mark.asyncio
+async def test_init_containers_api_endpoints_create_with_model_uses_deployment_credentials(monkeypatch):
+    """
+    ``POST /v1/containers`` carries no container ID, so a ``model`` in the request
+    body is the only way to pick a deployment. The upstream call must receive that
+    deployment's ``api_key``/``api_base`` instead of falling back to the global
+    ``OPENAI_API_KEY`` (which may be unset on the proxy).
+    """
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-5.4",
+                "litellm_params": {
+                    "model": "openai/gpt-5.4",
+                    "api_key": "sk-model-list-key",
+                    "api_base": "https://custom.openai.example/v1",
+                },
+            }
+        ]
+    )
+    mock_original_function = AsyncMock(return_value={"id": "cntr_test", "name": "Test Container"})
+
+    await router._init_containers_api_endpoints(
+        original_function=mock_original_function,
+        custom_llm_provider="openai",
+        name="Test Container",
+        model="gpt-5.4",
+    )
+
+    mock_original_function.assert_called_once()
+    call_kw = mock_original_function.call_args.kwargs
+    assert call_kw["api_key"] == "sk-model-list-key"
+    assert call_kw["api_base"] == "https://custom.openai.example/v1"
+    assert call_kw["model"] == "openai/gpt-5.4"
+    assert call_kw["name"] == "Test Container"
+
+
+@pytest.mark.asyncio
+async def test_init_containers_api_endpoints_create_without_model_calls_directly():
+    """
+    Without ``model`` (or with ``model=None`` as the proxy forwards it), create/list
+    must keep calling the handler directly with global provider credentials.
+    """
+    router = Router(model_list=[])
+    router._ageneric_api_call_with_fallbacks = AsyncMock()
+    mock_original_function = AsyncMock(return_value={"id": "cntr_test"})
+
+    await router._init_containers_api_endpoints(
+        original_function=mock_original_function,
+        custom_llm_provider="openai",
+        name="Test Container",
+        model=None,
+    )
+
+    router._ageneric_api_call_with_fallbacks.assert_not_called()
+    mock_original_function.assert_called_once_with(custom_llm_provider="openai", name="Test Container", model=None)
+
+
+@pytest.mark.asyncio
+async def test_init_containers_api_endpoints_create_with_unknown_model_passes_through(monkeypatch):
+    """
+    A ``model`` that names no configured deployment must not turn into a 400. The call
+    falls through to the handler with the caller's model and no injected deployment
+    credentials, matching the behaviour before model-based routing existed.
+    """
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-5.4",
+                "litellm_params": {"model": "openai/gpt-5.4", "api_key": "sk-model-list-key"},
+            }
+        ]
+    )
+    mock_original_function = AsyncMock(return_value={"id": "cntr_test"})
+
+    await router._init_containers_api_endpoints(
+        original_function=mock_original_function,
+        custom_llm_provider="openai",
+        name="Test Container",
+        model="does-not-exist",
+    )
+
+    mock_original_function.assert_called_once()
+    call_kw = mock_original_function.call_args.kwargs
+    assert call_kw["model"] == "does-not-exist"
+    assert call_kw["name"] == "Test Container"
+    assert "api_key" not in call_kw
+    assert "api_base" not in call_kw
+
+
 def test_router_model_group_encrypted_content_affinity_callback_registration():
     from litellm.router_utils.pre_call_checks.deployment_affinity_check import (
         DeploymentAffinityCheck,
diff --git a/tests/router_unit_tests/test_router_helper_utils.py b/tests/router_unit_tests/test_router_helper_utils.py
index dcd2e9edf7b..7dbac243d55 100644
--- a/tests/router_unit_tests/test_router_helper_utils.py
+++ b/tests/router_unit_tests/test_router_helper_utils.py
@@ -2294,6 +2294,7 @@ def search_tools():
                 "search_provider": "perplexity",
                 "api_key": "test-api-key",
                 "api_base": "https://api.perplexity.ai",
+                "mode": "turbo",
             },
         },
         {
@@ -2302,6 +2303,7 @@ def search_tools():
                 "search_provider": "perplexity",
                 "api_key": "test-api-key-2",
                 "api_base": "https://api.perplexity.ai",
+                "mode": "turbo",
             },
         },
     ]
@@ -2393,6 +2395,7 @@ async def test_asearch_with_fallbacks_helper(search_tools):
         assert "search_provider" in kwargs
         assert kwargs["search_provider"] == "perplexity"
         assert "api_key" in kwargs
+        assert kwargs["mode"] == "turbo"
         assert kwargs["query"] == "helper test query"
         return mock_response
 
diff --git a/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py b/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py
index 5503a5668bf..a8fe464ec32 100644
--- a/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py
+++ b/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py
@@ -11,7 +11,9 @@ Verifies that:
 
 import json
 
+import httpx
 import pytest
+import respx
 from unittest.mock import AsyncMock, MagicMock, patch
 
 
@@ -295,6 +297,195 @@ class TestTransformation:
         assert headers["Authorization"].startswith("AWS4-HMAC-SHA256")
 
 
+SESSION_HEADER = "X-Amzn-Bedrock-AgentCore-Runtime-Session-Id"
+CONTEXT_ID = "conversation-alpha-0001-0000000000000000"
+KEY_HASH = "hashed-key-of-caller-one"
+
+
+def _params_with_context(context_id: object) -> dict:
+    return {"message": {**SAMPLE_PARAMS["message"], "contextId": context_id}}
+
+
+def _scoped(context_id: str, key_hash: str) -> str:
+    import hashlib
+
+    return f"{hashlib.sha256(key_hash.encode()).hexdigest()[:16]}-{context_id}"
+
+
+def _session_header(params: dict, litellm_params: dict) -> str:
+    from litellm.a2a_protocol.providers.bedrock_agentcore.transformation import (
+        BedrockAgentCoreA2ATransformation,
+    )
+
+    _, headers, _ = BedrockAgentCoreA2ATransformation.get_url_and_signed_request(
+        request_id="req-001",
+        params=params,
+        litellm_params=litellm_params,
+    )
+    return headers[SESSION_HEADER]
+
+
+@pytest.fixture
+def httpx_transport(monkeypatch):
+    import litellm
+
+    monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
+    monkeypatch.setenv("DISABLE_AIOHTTP_TRANSPORT", "True")
+    litellm.in_memory_llm_clients_cache.flush_cache()
+    yield
+    litellm.in_memory_llm_clients_cache.flush_cache()
+
+
+class TestRequestScopedRuntimeSession:
+    """message.contextId selects the AgentCore runtime session, scoped to the calling key."""
+
+    def test_context_id_scoped_to_calling_key(self):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH}
+        assert _session_header(_params_with_context(CONTEXT_ID), litellm_params) == _scoped(CONTEXT_ID, KEY_HASH)
+
+    def test_context_id_used_verbatim_without_principal(self):
+        assert _session_header(_params_with_context(CONTEXT_ID), SAMPLE_LITELLM_PARAMS) == CONTEXT_ID
+
+    def test_same_context_id_reuses_session_and_other_context_isolated(self):
+        first = _session_header(_params_with_context(CONTEXT_ID), SAMPLE_LITELLM_PARAMS)
+        second = _session_header(_params_with_context(CONTEXT_ID), SAMPLE_LITELLM_PARAMS)
+        other = _session_header(
+            _params_with_context("conversation-beta-00002-0000000000000000"),
+            SAMPLE_LITELLM_PARAMS,
+        )
+        assert first == second
+        assert other != first
+
+    def test_same_context_id_from_different_keys_is_isolated(self):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+
+        params = _params_with_context(CONTEXT_ID)
+        caller_one = _session_header(params, {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH})
+        caller_two = _session_header(
+            params, {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: "hashed-key-of-caller-two"}
+        )
+        assert caller_one != caller_two
+        assert caller_one.endswith(f"-{CONTEXT_ID}")
+        assert caller_two.endswith(f"-{CONTEXT_ID}")
+
+    def test_context_id_takes_precedence_over_configured_session(self):
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "a" * 40}
+        assert _session_header(_params_with_context(CONTEXT_ID), litellm_params) == CONTEXT_ID
+
+    def test_configured_session_is_fallback_without_context_id(self):
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "a" * 40}
+        assert _session_header(SAMPLE_PARAMS, litellm_params) == "a" * 40
+        assert _session_header(_params_with_context(""), litellm_params) == "a" * 40
+
+    def test_no_context_id_and_no_config_generates_new_session_per_request(self):
+        first = _session_header(SAMPLE_PARAMS, SAMPLE_LITELLM_PARAMS)
+        second = _session_header(SAMPLE_PARAMS, SAMPLE_LITELLM_PARAMS)
+        assert first != second
+        assert 33 <= len(first) <= 256
+
+    @pytest.mark.parametrize(
+        "context_id",
+        [
+            "short-context-id",
+            "x" * 257,
+        ],
+    )
+    def test_invalid_context_id_rejected_with_clear_error(self, context_id):
+        import litellm
+
+        with pytest.raises(litellm.BadRequestError, match="Invalid AgentCore runtime session id") as exc_info:
+            _session_header(_params_with_context(context_id), SAMPLE_LITELLM_PARAMS)
+        assert exc_info.value.status_code == 400
+        assert "33-256" in str(exc_info.value)
+
+    def test_scoped_context_id_shorter_than_33_rejected(self):
+        import litellm
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH}
+        with pytest.raises(litellm.BadRequestError, match=_scoped("c" * 15, KEY_HASH)):
+            _session_header(_params_with_context("c" * 15), litellm_params)
+        assert _session_header(_params_with_context("c" * 16), litellm_params) == _scoped("c" * 16, KEY_HASH)
+
+    def test_invalid_configured_session_rejected(self):
+        import litellm
+
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "too-short"}
+        with pytest.raises(litellm.BadRequestError, match="Invalid AgentCore runtime session id"):
+            _session_header(SAMPLE_PARAMS, litellm_params)
+
+    def test_non_string_context_id_falls_back(self):
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "a" * 40}
+        assert _session_header(_params_with_context(12345), litellm_params) == "a" * 40
+
+    def test_spoofed_session_header_does_not_override_context_id(self):
+        from litellm.a2a_protocol.providers.bedrock_agentcore.transformation import (
+            BedrockAgentCoreA2ATransformation,
+        )
+
+        _, headers, _ = BedrockAgentCoreA2ATransformation.get_url_and_signed_request(
+            request_id="req-001",
+            params=_params_with_context(CONTEXT_ID),
+            litellm_params=SAMPLE_LITELLM_PARAMS,
+            agent_extra_headers={SESSION_HEADER: "s" * 40},
+        )
+        assert headers[SESSION_HEADER] == CONTEXT_ID
+
+    @pytest.mark.asyncio
+    async def test_context_id_session_header_on_outbound_non_streaming_post(self, httpx_transport):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+        from litellm.a2a_protocol.providers.bedrock_agentcore.config import (
+            BedrockAgentCoreA2AConfig,
+        )
+
+        with respx.mock(assert_all_called=True) as router:
+            route = router.post(url__regex=r".*/invocations.*").mock(
+                return_value=httpx.Response(200, json={"jsonrpc": "2.0", "id": "req-001", "result": {}})
+            )
+            await BedrockAgentCoreA2AConfig().handle_non_streaming(
+                request_id="req-001",
+                params=_params_with_context(CONTEXT_ID),
+                litellm_params={**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH},
+            )
+
+        assert route.calls.last.request.headers[SESSION_HEADER] == _scoped(CONTEXT_ID, KEY_HASH)
+
+    @pytest.mark.asyncio
+    async def test_context_id_session_header_on_outbound_streaming_post(self, httpx_transport):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+        from litellm.a2a_protocol.providers.bedrock_agentcore.config import (
+            BedrockAgentCoreA2AConfig,
+        )
+
+        with respx.mock(assert_all_called=True) as router:
+            route = router.post(url__regex=r".*/invocations.*").mock(
+                return_value=httpx.Response(200, json={"jsonrpc": "2.0", "id": "req-001", "result": {}})
+            )
+            events = [
+                event
+                async for event in BedrockAgentCoreA2AConfig().handle_streaming(
+                    request_id="req-001",
+                    params=_params_with_context(CONTEXT_ID),
+                    litellm_params={**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH},
+                )
+            ]
+
+        assert events == [{"jsonrpc": "2.0", "id": "req-001", "result": {}}]
+        assert route.calls.last.request.headers[SESSION_HEADER] == _scoped(CONTEXT_ID, KEY_HASH)
+
+
 class TestNonStreaming:
     """Test end-to-end non-streaming flow."""
 
diff --git a/tests/test_litellm/containers/test_container_api.py b/tests/test_litellm/containers/test_container_api.py
index 885c4cd294a..16a3844431e 100644
--- a/tests/test_litellm/containers/test_container_api.py
+++ b/tests/test_litellm/containers/test_container_api.py
@@ -152,6 +152,42 @@ class TestContainerAPI:
             assert response.id == "cntr_async_123"
             assert response.name == "Async Test Container"
 
+    @pytest.mark.asyncio
+    async def test_acreate_container_encodes_router_model_id(self):
+        """
+        The async handler returns a coroutine, so the managed-ID encoding must run
+        after it resolves. Otherwise follow-up calls (retrieve/delete/files) lose the
+        deployment and fall back to global provider credentials.
+        """
+        upstream_response = ContainerObject(
+            id="cntr_upstream_123",
+            object="container",
+            created_at=1747857508,
+            status="running",
+            expires_after={"anchor": "last_active_at", "minutes": 20},
+            last_active_at=1747857508,
+            name="Routed Container",
+        )
+
+        async def _resolve_upstream():
+            return upstream_response
+
+        with patch.object(  # test-quality-ok: create_container exposes no client seam, only the handler
+            base_llm_http_handler,
+            "container_create_handler",
+            side_effect=lambda **kwargs: _resolve_upstream() if kwargs["_is_async"] else upstream_response,
+        ):
+            response = await acreate_container(
+                name="Routed Container",
+                custom_llm_provider="openai",
+                litellm_metadata={"model_info": {"id": "deployment-abc"}},
+            )
+
+        decoded = ResponsesAPIRequestUtils._decode_container_id(response.id)
+        assert decoded["model_id"] == "deployment-abc"
+        assert decoded["custom_llm_provider"] == "openai"
+        assert decoded["response_id"] == "cntr_upstream_123"
+
     @pytest.mark.asyncio
     async def test_alist_containers_basic(self):
         """Test basic async container listing functionality."""
diff --git a/tests/test_litellm/integrations/datadog/test_datadog_llm_obs.py b/tests/test_litellm/integrations/datadog/test_datadog_llm_obs.py
new file mode 100644
index 00000000000..2d0605e3b7f
--- /dev/null
+++ b/tests/test_litellm/integrations/datadog/test_datadog_llm_obs.py
@@ -0,0 +1,469 @@
+"""
+Regression tests for the Datadog LLM Observability payload schema (issue #35786).
+
+Datadog renders tool calls, tool results and prompt-cache savings only from the fields its
+own schema names. These assert on the payload `create_llm_obs_payload` actually hands the
+intake, so a regression that moves data back into `meta.metadata` fails here.
+
+Fixtures mirror what a live proxy run recorded on the callback, including the provider
+spelling of prompt-cache counts (`prompt_tokens_details.cached_tokens`).
+"""
+
+import json
+import os
+from datetime import datetime, timedelta
+from typing import Any
+from unittest.mock import patch
+
+import pytest
+
+from litellm.integrations.datadog.datadog_llm_obs import DataDogLLMObsLogger
+from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+
+TOOL_DEFINITION: dict[str, Any] = {
+    "type": "function",
+    "function": {
+        "name": "get_weather",
+        "description": "Get current weather for a city",
+        "parameters": {
+            "type": "object",
+            "properties": {"city": {"type": "string"}},
+            "required": ["city"],
+        },
+    },
+}
+
+ASSISTANT_TOOL_CALL: dict[str, Any] = {
+    "id": "call_abc123",
+    "type": "function",
+    "function": {"name": "get_weather", "arguments": '{"city":"Paris","unit":"c"}'},
+}
+
+
+@pytest.fixture
+def logger() -> DataDogLLMObsLogger:
+    with patch.dict(os.environ, {"DD_API_KEY": "k", "DD_SITE": "us5.datadoghq.com"}, clear=True):
+        with patch("asyncio.create_task"):
+            return DataDogLLMObsLogger()
+
+
+NOT_GIVEN: Any = object()
+
+
+def build_payload(
+    messages: Any = NOT_GIVEN,
+    response_message: dict[str, Any] | None = None,
+    usage_object: dict[str, Any] | None = None,
+    model_parameters: dict[str, Any] | None = None,
+    prompt_tokens: int = 4447,
+) -> dict[str, Any]:
+    return {
+        "standard_logging_object": {
+            "call_type": "acompletion",
+            "messages": [{"role": "user", "content": "hi"}] if messages is NOT_GIVEN else messages,
+            "response": {"choices": [{"message": response_message or {"role": "assistant", "content": "hello"}}]},
+            "model_parameters": model_parameters or {},
+            "metadata": {"usage_object": usage_object} if usage_object is not None else {},
+            "prompt_tokens": prompt_tokens,
+            "completion_tokens": 507,
+            "total_tokens": prompt_tokens + 507,
+            "response_cost": 0.02,
+            "status": "success",
+        },
+        "litellm_params": {"metadata": {}},
+    }
+
+
+def build(logger: DataDogLLMObsLogger, **kwargs: Any) -> dict[str, Any]:
+    """Build a span and read it back as the JSON the intake receives, not as Python objects."""
+    start = datetime(2026, 9, 1, 12, 0, 0)
+    payload = logger.create_llm_obs_payload(build_payload(**kwargs), start, start + timedelta(seconds=2))
+    return json.loads(safe_dumps(payload))
+
+
+def test_output_tool_calls_use_the_datadog_tool_call_schema(logger: DataDogLLMObsLogger) -> None:
+    """Datadog reads name/arguments/tool_id off the tool call; OpenAI nests them under `function`."""
+    payload = build(
+        logger,
+        response_message={"role": "assistant", "content": None, "tool_calls": [ASSISTANT_TOOL_CALL]},
+    )
+
+    message = payload["meta"]["output"]["messages"][0]
+    assert message["tool_calls"] == [
+        {
+            "name": "get_weather",
+            "arguments": {"city": "Paris", "unit": "c"},
+            "tool_id": "call_abc123",
+            "type": "function",
+        }
+    ]
+    assert "function" not in message["tool_calls"][0]
+
+
+def test_tool_calls_are_not_duplicated_into_metadata(logger: DataDogLLMObsLogger) -> None:
+    """The flat `output_tool_calls.*` keys were a second copy of a fact that now has its own field."""
+    payload = build(
+        logger,
+        response_message={"role": "assistant", "content": None, "tool_calls": [ASSISTANT_TOOL_CALL]},
+    )
+
+    assert [key for key in payload["meta"]["metadata"] if "tool_calls." in key] == []
+
+
+def test_tool_result_message_links_back_to_its_tool_call(logger: DataDogLLMObsLogger) -> None:
+    """Datadog pairs a result with its call through tool_id, and names the tool from the call."""
+    payload = build(
+        logger,
+        messages=[
+            {"role": "user", "content": "Weather in Paris?"},
+            {"role": "assistant", "content": None, "tool_calls": [ASSISTANT_TOOL_CALL]},
+            {"role": "tool", "tool_call_id": "call_abc123", "content": '{"temp_c": 18}'},
+        ],
+    )
+
+    tool_message = payload["meta"]["input"]["messages"][2]
+    assert tool_message["tool_results"] == [
+        {"name": "get_weather", "result": '{"temp_c": 18}', "tool_id": "call_abc123", "type": "function"}
+    ]
+
+
+def test_tool_result_without_a_matching_call_still_reports_its_id(logger: DataDogLLMObsLogger) -> None:
+    """A truncated conversation loses the call, so the name is unknown but the link must survive."""
+    payload = build(
+        logger,
+        messages=[{"role": "tool", "tool_call_id": "call_orphan", "content": "42"}],
+    )
+
+    assert payload["meta"]["input"]["messages"][0]["tool_results"] == [
+        {"name": "", "result": "42", "tool_id": "call_orphan", "type": "function"}
+    ]
+
+
+def test_cache_tokens_are_reported_as_span_metrics(logger: DataDogLLMObsLogger) -> None:
+    """
+    Datadog charts cache savings from span metrics; nested usage_object is not read for it.
+
+    litellm's normalized prompt count includes both cache categories, so the three cache
+    metrics must partition input_tokens: read + write + non_cached == input.
+    """
+    payload = build(
+        logger,
+        usage_object={"prompt_tokens_details": {"cached_tokens": 4300, "cache_write_tokens": 95}},
+    )
+
+    metrics = payload["metrics"]
+    assert metrics["cache_read_input_tokens"] == 4300.0
+    assert metrics["cache_write_input_tokens"] == 95.0
+    assert metrics["non_cached_input_tokens"] == 4447.0 - 4300.0 - 95.0
+    assert (
+        metrics["cache_read_input_tokens"] + metrics["cache_write_input_tokens"] + metrics["non_cached_input_tokens"]
+        == metrics["input_tokens"]
+    )
+
+
+def test_cache_write_tokens_are_not_counted_as_non_cached(logger: DataDogLLMObsLogger) -> None:
+    """A cache-priming request must not report its primed prefix as full-price uncached input."""
+    payload = build(logger, usage_object={"prompt_tokens_details": {"cache_write_tokens": 4000}})
+
+    assert payload["metrics"]["cache_write_input_tokens"] == 4000.0
+    assert payload["metrics"]["non_cached_input_tokens"] == 4447.0 - 4000.0
+    assert "cache_read_input_tokens" not in payload["metrics"]
+
+
+def test_a_fully_cached_request_reports_a_zero_non_cached_count(logger: DataDogLLMObsLogger) -> None:
+    """Zero residual is real data: everything was served from cache. Inconsistent counts clamp to it."""
+    payload = build(
+        logger,
+        usage_object={"prompt_tokens_details": {"cached_tokens": 4352, "cache_write_tokens": 95}},
+    )
+
+    assert payload["metrics"]["non_cached_input_tokens"] == 0.0
+
+
+def test_anthropic_top_level_cache_keys_are_read(logger: DataDogLLMObsLogger) -> None:
+    """A raw Anthropic usage dict records the counts top level, not under prompt_tokens_details."""
+    payload = build(
+        logger,
+        usage_object={"cache_read_input_tokens": 4300, "cache_creation_input_tokens": 95},
+    )
+
+    metrics = payload["metrics"]
+    assert metrics["cache_read_input_tokens"] == 4300.0
+    assert metrics["cache_write_input_tokens"] == 95.0
+    assert metrics["non_cached_input_tokens"] == 4447.0 - 4300.0 - 95.0
+
+
+def test_cache_metrics_come_from_the_normalized_field_not_the_anthropic_one(logger: DataDogLLMObsLogger) -> None:
+    """
+    litellm normalizes every provider's cache counters into prompt_tokens_details.
+
+    A real cached request from a non-Anthropic provider carries only `cached_tokens`, so
+    reading the Anthropic-specific `cache_read_input_tokens` key reports nothing for it.
+    """
+    payload = build(
+        logger,
+        usage_object={"prompt_tokens_details": {"audio_tokens": None, "cached_tokens": 4096}},
+        prompt_tokens=4335,
+    )
+
+    assert payload["metrics"]["cache_read_input_tokens"] == 4096.0
+    assert payload["metrics"]["non_cached_input_tokens"] == 4335.0 - 4096.0
+
+
+@pytest.mark.parametrize(
+    "usage_object",
+    [
+        {"prompt_tokens_details": {"cache_write_tokens": 95}},
+        {"prompt_tokens_details": {"cache_creation_tokens": 95}},
+        {"cache_creation_input_tokens": 95},
+    ],
+)
+def test_every_spelling_of_cache_write_tokens_is_read(
+    logger: DataDogLLMObsLogger, usage_object: dict[str, Any]
+) -> None:
+    """A raw usage dict that bypassed litellm's normalizer can carry any provider's spelling."""
+    payload = build(logger, usage_object=usage_object)
+
+    assert payload["metrics"]["cache_write_input_tokens"] == 95.0
+
+
+def test_a_cache_read_does_not_emit_a_zero_cache_write(logger: DataDogLLMObsLogger) -> None:
+    """A zero write on every cache-read span would drag Datadog's cache-write average to nothing."""
+    payload = build(logger, usage_object={"prompt_tokens_details": {"cached_tokens": 4096}})
+
+    assert payload["metrics"]["cache_read_input_tokens"] == 4096.0
+    assert "cache_write_input_tokens" not in payload["metrics"]
+
+
+def test_no_cache_keys_when_the_provider_reports_no_caching(logger: DataDogLLMObsLogger) -> None:
+    """An uncached request must not gain zero-valued cache metrics that dilute cache dashboards."""
+    payload = build(logger, usage_object={"prompt_tokens_details": None})
+
+    assert "cache_read_input_tokens" not in payload["metrics"]
+    assert "cache_write_input_tokens" not in payload["metrics"]
+    assert "non_cached_input_tokens" not in payload["metrics"]
+
+
+def test_tool_definitions_are_sent_on_meta(logger: DataDogLLMObsLogger) -> None:
+    payload = build(logger, model_parameters={"tools": [TOOL_DEFINITION]})
+
+    assert payload["meta"]["tool_definitions"] == [
+        {
+            "name": "get_weather",
+            "description": "Get current weather for a city",
+            "schema": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]},
+        }
+    ]
+
+
+def test_tool_definitions_accept_the_bare_anthropic_shape(logger: DataDogLLMObsLogger) -> None:
+    """The Anthropic surface declares tools unwrapped, with input_schema instead of parameters."""
+    payload = build(
+        logger,
+        model_parameters={"tools": [{"name": "get_weather", "description": "d", "input_schema": {"type": "object"}}]},
+    )
+
+    assert payload["meta"]["tool_definitions"] == [
+        {"name": "get_weather", "description": "d", "schema": {"type": "object"}}
+    ]
+
+
+def test_meta_omits_tool_definitions_when_no_tools_were_offered(logger: DataDogLLMObsLogger) -> None:
+    assert "tool_definitions" not in build(logger)["meta"]
+
+
+def test_unparseable_tool_arguments_are_preserved_rather_than_dropped(logger: DataDogLLMObsLogger) -> None:
+    """A truncated argument string is still the only record of what the model tried to call."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": '{"city":'}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == '{"city":'
+
+
+def test_oversized_tool_arguments_ship_unparsed(logger: DataDogLLMObsLogger) -> None:
+    """
+    Decoding attacker-sized compact JSON multiplies memory for a span that is only logging.
+
+    This payload is perfectly valid JSON, so the only reason it arrives as a string is the
+    size bound; a smaller copy of the same shape comes back as an object below.
+    """
+    oversized = '{"a":"' + "x" * 300_000 + '"}'
+
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": oversized}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == oversized
+
+
+def test_valid_arguments_below_the_bound_still_parse(logger: DataDogLLMObsLogger) -> None:
+    """The size bound must not swallow ordinary arguments; this is the oversized test's control."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [
+                {"id": "c1", "type": "function", "function": {"name": "f", "arguments": '{"a":"' + "x" * 64 + '"}'}}
+            ],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == {"a": "x" * 64}
+
+
+def test_a_result_is_named_even_when_its_call_had_unparseable_arguments(logger: DataDogLLMObsLogger) -> None:
+    """Correlating a result to its call reads ids and names, so bad arguments cannot break linking."""
+    payload = build(
+        logger,
+        messages=[
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {"id": "call_abc123", "type": "function", "function": {"name": "get_weather", "arguments": "{"}}
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_abc123", "content": "18C"},
+        ],
+    )
+
+    assert payload["meta"]["input"]["messages"][1]["tool_results"] == [
+        {"name": "get_weather", "result": "18C", "tool_id": "call_abc123", "type": "function"}
+    ]
+
+
+def test_deeply_nested_tool_arguments_do_not_drop_the_span(logger: DataDogLLMObsLogger) -> None:
+    """json.loads raises RecursionError, not JSONDecodeError, on hostile nesting."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": "[" * 50_000}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == "[" * 50_000
+
+
+def test_tool_arguments_that_parse_to_a_non_object_stay_a_string(logger: DataDogLLMObsLogger) -> None:
+    """Datadog types arguments as an object, so a bare JSON scalar must not land there as one."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": "42"}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == "42"
+
+
+def test_a_tool_without_a_name_is_not_offered_as_a_definition(logger: DataDogLLMObsLogger) -> None:
+    """A nameless tool cannot be matched to a call, so it is dropped rather than sent blank."""
+    payload = build(logger, model_parameters={"tools": [{"function": {"description": "no name"}}, TOOL_DEFINITION]})
+
+    assert [tool["name"] for tool in payload["meta"]["tool_definitions"]] == ["get_weather"]
+
+
+def test_a_tool_definition_without_a_schema_omits_the_field(logger: DataDogLLMObsLogger) -> None:
+    """An empty schema object would read as a tool that takes no arguments, which is a different claim."""
+    payload = build(logger, model_parameters={"tools": [{"name": "ping", "description": "d"}]})
+
+    assert payload["meta"]["tool_definitions"] == [{"name": "ping", "description": "d"}]
+
+
+def test_a_non_dict_message_still_reaches_datadog(logger: DataDogLLMObsLogger) -> None:
+    """Callers can log arbitrary message payloads, and dropping the span over one loses the request."""
+    payload = build(logger, messages=["just a bare string"])
+
+    assert payload["meta"]["input"]["messages"] == [{"input": "just a bare string"}]
+
+
+def test_messages_logged_as_a_bare_string_still_reach_datadog(logger: DataDogLLMObsLogger) -> None:
+    payload = build(logger, messages="the whole prompt as one string")
+
+    assert payload["meta"]["input"]["messages"] == [{"input": "the whole prompt as one string"}]
+
+
+def test_non_chat_call_types_log_an_empty_input(logger: DataDogLLMObsLogger) -> None:
+    """Embedding and image calls carry no messages; fabricating an "None" turn misreads in Datadog."""
+    payload = build(logger, messages=None)
+
+    assert payload["meta"]["input"]["messages"] == []
+
+
+def test_anthropic_tool_blocks_map_to_tool_calls_and_results(logger: DataDogLLMObsLogger) -> None:
+    """/v1/messages carries tool traffic as content blocks, not OpenAI fields."""
+    payload = build(
+        logger,
+        messages=[
+            {"role": "user", "content": [{"type": "text", "text": "Weather in Tokyo?"}]},
+            {
+                "role": "assistant",
+                "content": [{"type": "tool_use", "id": "toolu_1", "name": "get_weather", "input": {"city": "Tokyo"}}],
+            },
+            {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_1", "content": "18C"}]},
+        ],
+    )
+
+    assistant, result_turn = payload["meta"]["input"]["messages"][1:3]
+    assert assistant["tool_calls"] == [
+        {"name": "get_weather", "arguments": {"city": "Tokyo"}, "tool_id": "toolu_1", "type": "tool_use"}
+    ]
+    assert result_turn["tool_results"] == [
+        {"name": "get_weather", "result": "18C", "tool_id": "toolu_1", "type": "function"}
+    ]
+
+
+def test_content_with_no_text_parts_is_preserved_not_blanked(logger: DataDogLLMObsLogger) -> None:
+    """A content list the mapper does not understand must ride along, not be erased."""
+    blocks = [{"type": "image_url", "image_url": {"url": "https://example.com/x.png"}}]
+    payload = build(logger, messages=[{"role": "user", "content": blocks}])
+
+    assert payload["meta"]["input"]["messages"][0]["content"] == blocks
+
+
+def test_multimodal_content_parts_are_flattened_to_text(logger: DataDogLLMObsLogger) -> None:
+    """Datadog types Message.content as a string, so content lists collapse to their text."""
+    payload = build(
+        logger,
+        messages=[
+            {"role": "user", "content": [{"type": "text", "text": "describe "}, {"type": "text", "text": "this"}]}
+        ],
+    )
+
+    assert payload["meta"]["input"]["messages"][0]["content"] == "describe this"
+
+
+def test_mapping_input_messages_does_not_mutate_the_shared_payload(logger: DataDogLLMObsLogger) -> None:
+    """Sibling callbacks read the same messages list, so flattening must not write through it."""
+    messages: list[dict[str, Any]] = [{"role": "user", "content": [{"type": "text", "text": "hi"}]}]
+    kwargs = build_payload(messages=messages)
+    start = datetime(2026, 9, 1, 12, 0, 0)
+
+    logger.create_llm_obs_payload(kwargs, start, start + timedelta(seconds=1))
+
+    assert messages[0]["content"] == [{"type": "text", "text": "hi"}]
+
+
+def test_reasoning_content_survives_the_mapping(logger: DataDogLLMObsLogger) -> None:
+    payload = build(
+        logger,
+        response_message={"role": "assistant", "content": "answer", "reasoning_content": "thinking"},
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["reasoning_content"] == "thinking"
diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py
index ca628aa3405..99d706a9c44 100644
--- a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py
+++ b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py
@@ -541,6 +541,74 @@ def test_llm_call_adapter_extracts_cache_tokens_from_usage_object():
     assert data.usage.cache_read_input_tokens == 3
 
 
+def test_llm_call_adapter_normalizes_nested_cache_tokens():
+    cases: Final = (
+        ({"prompt_tokens_details": {"cached_tokens": 3}}, 3, None),
+        ({"prompt_cache_hit_tokens": 11}, 11, None),
+        ({"prompt_tokens_details": {"cache_write_tokens": 7}}, None, 7),
+        ({"prompt_tokens_details": {"cache_creation_tokens": 13}}, None, 13),
+        ({"prompt_tokens_details": {"cache_creation_input_tokens": 17}}, None, 17),
+    )
+    for usage_object, expected_read, expected_creation in cases:
+        case_payload = _sample_payload(metadata={"usage_object": usage_object})
+        data = LLMCallSpanData.from_standard_logging_payload(case_payload)
+        assert data.usage.cache_read_input_tokens == expected_read
+        assert data.usage.cache_creation_input_tokens == expected_creation
+
+
+def test_llm_call_adapter_prefers_nested_count_over_zero_top_level():
+    payload = _sample_payload(
+        metadata={
+            "usage_object": {
+                "cache_read_input_tokens": 0,
+                "cache_creation_input_tokens": 0,
+                "prompt_tokens_details": {"cached_tokens": 5, "cache_write_tokens": 7},
+            }
+        }
+    )
+    data = LLMCallSpanData.from_standard_logging_payload(payload)
+    assert data.usage.cache_read_input_tokens == 5
+    assert data.usage.cache_creation_input_tokens == 7
+
+
+def test_llm_call_adapter_ignores_invalid_cache_values_before_valid_fallbacks():
+    payload = _sample_payload(
+        metadata={
+            "usage_object": {
+                "cache_read_input_tokens": -1,
+                "cache_creation_input_tokens": "5.0",
+                "prompt_tokens_details": {"cached_tokens": 5, "cache_write_tokens": 7},
+            }
+        }
+    )
+    data = LLMCallSpanData.from_standard_logging_payload(payload)
+    assert data.usage.cache_read_input_tokens == 5
+    assert data.usage.cache_creation_input_tokens == 7
+
+
+def test_llm_call_adapter_ignores_non_finite_cache_values():
+    payload = _sample_payload(
+        metadata={
+            "usage_object": {
+                "prompt_tokens_details": {"cached_tokens": float("nan")},
+            }
+        }
+    )
+    data = LLMCallSpanData.from_standard_logging_payload(payload)
+    assert data.usage.cache_read_input_tokens is None
+
+
+def test_llm_call_adapter_preserves_explicit_zero_and_omits_missing_cache_tokens():
+    for usage_object, expected_read, expected_creation in (
+        ({"prompt_tokens_details": {"cached_tokens": 0}}, 0, None),
+        ({}, None, None),
+    ):
+        case_payload = _sample_payload(metadata={"usage_object": usage_object})
+        data = LLMCallSpanData.from_standard_logging_payload(case_payload)
+        assert data.usage.cache_read_input_tokens == expected_read
+        assert data.usage.cache_creation_input_tokens == expected_creation
+
+
 def test_llm_call_adapter_cache_tokens_none_without_usage_object():
     data = LLMCallSpanData.from_standard_logging_payload(_sample_payload())
     assert data.usage.cache_creation_input_tokens is None
diff --git a/tests/test_litellm/integrations/test_custom_guardrail.py b/tests/test_litellm/integrations/test_custom_guardrail.py
index d978eb48c12..7d70b9a8862 100644
--- a/tests/test_litellm/integrations/test_custom_guardrail.py
+++ b/tests/test_litellm/integrations/test_custom_guardrail.py
@@ -2237,3 +2237,202 @@ class TestRecordsOwnGuardrailInformation:
         )
 
         assert _guardrail_entries(request_data) == []
+
+
+class _ApplyOnlyObserver(CustomGuardrail):
+    """Overrides only apply_guardrail, like panw_prisma_airs; inherits async_logging_hook."""
+
+    def __init__(self, block: bool = False):
+        from litellm.types.guardrails import GuardrailEventHooks
+
+        super().__init__(guardrail_name="apply-only-observer", event_hook=GuardrailEventHooks.logging_only)
+        self.block = block
+        self.calls: list = []
+
+    @log_guardrail_information
+    async def apply_guardrail(self, inputs, request_data, input_type, logging_obj=None):
+        from fastapi import HTTPException
+
+        self.calls.append((input_type, list(inputs.get("texts") or [])))
+        if self.block:
+            raise HTTPException(status_code=400, detail={"error": "flagged"})
+        return GenericGuardrailAPIInputs(texts=["[MASKED]" for _ in inputs.get("texts") or []])
+
+
+def _logged_call(messages: list | str) -> tuple[dict, object]:
+    from litellm.types.utils import Choices, Message, ModelResponse
+
+    response = ModelResponse(choices=[Choices(message=Message(role="assistant", content="general kenobi"))])
+    kwargs = {
+        "model": "gpt-5.4-mini",
+        "messages": messages,
+        "litellm_call_id": "call-1",
+        "litellm_params": {"metadata": {"user_api_key_user_id": "u1"}},
+        "optional_params": {},
+        "standard_logging_object": {"guardrail_information": None},
+    }
+    return kwargs, response
+
+
+class TestLoggingOnlyApplyGuardrail:
+    """LIT-4876 regression: a guardrail in mode logging_only that implements only
+    apply_guardrail must still run against the logged request and response and
+    record guardrail_information, instead of inheriting the CustomLogger no-op."""
+
+    @pytest.mark.asyncio
+    async def test_runs_apply_guardrail_observe_only_and_records_verdict(self):
+        guardrail = _ApplyOnlyObserver()
+        messages = [{"role": "user", "content": "hello there"}]
+        kwargs, response = _logged_call(messages)
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == [("request", ["hello there"]), ("response", ["general kenobi"])]
+        assert out_kwargs["messages"] == [{"role": "user", "content": "hello there"}]
+        assert out_response.choices[0].message.content == "general kenobi"
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_name"] for e in entries] == ["apply-only-observer", "apply-only-observer"]
+        assert {e["guardrail_mode"] for e in entries} == {"logging_only"}
+        assert {e["guardrail_status"] for e in entries} == {"success"}
+        assert "standard_logging_guardrail_information" not in kwargs["litellm_params"]["metadata"]
+        assert kwargs["standard_logging_object"] == {"guardrail_information": None}
+
+    @pytest.mark.asyncio
+    async def test_appends_to_pre_call_verdicts_without_duplicating_them(self):
+        guardrail = _ApplyOnlyObserver()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there"}])
+        pre_call_entry = {"guardrail_name": "pii-blocker", "guardrail_mode": "pre_call", "guardrail_status": "success"}
+        kwargs["litellm_params"]["metadata"]["standard_logging_guardrail_information"] = [pre_call_entry]
+        kwargs["standard_logging_object"]["guardrail_information"] = [pre_call_entry]
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_name"] for e in entries] == ["pii-blocker", "apply-only-observer", "apply-only-observer"]
+        assert kwargs["litellm_params"]["metadata"]["standard_logging_guardrail_information"] == [pre_call_entry]
+
+    @pytest.mark.asyncio
+    async def test_request_copy_failure_is_swallowed(self):
+        import threading
+
+        guardrail = _ApplyOnlyObserver()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there", "lock": threading.Lock()}])
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == []
+        assert out_kwargs is kwargs
+        assert out_response is response
+
+    @pytest.mark.asyncio
+    async def test_block_verdict_is_recorded_without_raising(self):
+        guardrail = _ApplyOnlyObserver(block=True)
+        kwargs, response = _logged_call([{"role": "user", "content": "flagged content"}])
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == [("request", ["flagged content"])]
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["guardrail_intervened"]
+
+    @pytest.mark.asyncio
+    async def test_call_type_without_translation_is_skipped(self):
+        guardrail = _ApplyOnlyObserver()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there"}])
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.amoderation.value)
+
+        assert guardrail.calls == []
+        assert out_kwargs["standard_logging_object"]["guardrail_information"] is None
+
+    @pytest.mark.asyncio
+    async def test_aembedding_scans_logged_input(self):
+        from litellm.types.utils import EmbeddingResponse
+
+        guardrail = _ApplyOnlyObserver()
+        kwargs, _ = _logged_call("hello there")
+        response = EmbeddingResponse(data=[{"embedding": [0.1], "index": 0, "object": "embedding"}])
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.aembedding.value)
+
+        assert guardrail.calls == [("request", ["hello there"])]
+        assert out_kwargs["messages"] == "hello there"
+        assert out_response is response
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["success"]
+
+    @pytest.mark.asyncio
+    async def test_native_lifecycle_hook_guardrail_is_left_alone(self):
+        class _NativeHooks(_ApplyOnlyObserver):
+            use_native_lifecycle_hooks = True
+
+        guardrail = _NativeHooks()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there"}])
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == []
+        assert out_kwargs is kwargs
+        assert out_response is response
+
+    @pytest.mark.asyncio
+    async def test_aresponses_scans_logged_messages_when_input_is_cleared(self):
+        from litellm.types.llms.openai import ResponsesAPIResponse
+
+        guardrail = _ApplyOnlyObserver()
+        kwargs, _ = _logged_call([{"role": "user", "content": "hello there"}])
+        kwargs["input"] = None
+        response = ResponsesAPIResponse(
+            id="resp_1",
+            created_at=1,
+            model="gpt-5.4-mini",
+            object="response",
+            status="completed",
+            output=[
+                {
+                    "type": "message",
+                    "id": "msg_1",
+                    "status": "completed",
+                    "role": "assistant",
+                    "content": [{"type": "output_text", "text": "general kenobi"}],
+                }
+            ],
+        )
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.aresponses.value)
+
+        assert guardrail.calls == [("request", ["hello there"]), ("response", ["general kenobi"])]
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["success", "success"]
+
+    @pytest.mark.asyncio
+    async def test_async_success_handler_records_verdict_in_standard_logging_object(self):
+        import datetime as dt
+
+        from litellm.litellm_core_utils.litellm_logging import Logging
+
+        guardrail = _ApplyOnlyObserver()
+        guardrail.default_on = True
+        messages = [{"role": "user", "content": "hello there"}]
+        _, response = _logged_call(messages)
+        logging_obj = Logging(
+            model="gpt-5.4-mini",
+            messages=messages,
+            stream=False,
+            call_type=CallTypes.acompletion.value,
+            start_time=dt.datetime.now(),
+            litellm_call_id="call-1",
+            function_id="fn-1",
+            dynamic_async_success_callbacks=[guardrail],
+        )
+        logging_obj.update_environment_variables(
+            litellm_params={"metadata": {}}, optional_params={}, model="gpt-5.4-mini", custom_llm_provider="openai"
+        )
+
+        await logging_obj.async_success_handler(
+            result=response, start_time=dt.datetime.now(), end_time=dt.datetime.now()
+        )
+
+        assert guardrail.calls == [("request", ["hello there"]), ("response", ["general kenobi"])]
+        entries = logging_obj.model_call_details["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["success", "success"]
diff --git a/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py b/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py
index 029b097cb75..ea661d2ea78 100644
--- a/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py
+++ b/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py
@@ -93,6 +93,7 @@ async def test_async_post_call_success_hook_includes_client_ip_user_agent():
         logger._increment_token_metrics = MagicMock()
         logger._increment_remaining_budget_metrics = AsyncMock()
         logger._set_virtual_key_rate_limit_metrics = MagicMock()
+        logger._set_key_and_team_rate_limit_metrics = MagicMock()
         logger._set_latency_metrics = MagicMock()
         logger.set_llm_deployment_success_metrics = MagicMock()
         logger._increment_cache_metrics = MagicMock()
diff --git a/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py b/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py
index 9c6d2e018ff..bf1d68c7714 100644
--- a/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py
+++ b/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py
@@ -13,6 +13,7 @@ Covers two follow-up gaps to the unified rate-limit error work:
    429s don't silently break when the new class lands.
 """
 
+from collections.abc import Mapping
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -471,3 +472,254 @@ def test_should_ignore_non_int_v3_header_values(bad_value):
     logger.litellm_remaining_api_key_tokens_for_model.labels.return_value.set.assert_called_once_with(
         sys.maxsize
     )
+
+
+KEY_AND_TEAM_RATE_LIMIT_METRICS = (
+    "litellm_api_key_rate_limit_allowed_metric",
+    "litellm_api_key_rate_limit_used_metric",
+    "litellm_team_rate_limit_allowed_metric",
+    "litellm_team_rate_limit_used_metric",
+)
+
+
+def _clear_prometheus_registry() -> None:
+    from prometheus_client import REGISTRY
+
+    for collector in list(REGISTRY._collector_to_names.keys()):
+        try:
+            REGISTRY.unregister(collector)
+        except Exception:
+            pass
+
+
+def _collected_samples(metric_name: str) -> dict[tuple[tuple[str, str], ...], float]:
+    from prometheus_client import REGISTRY
+
+    return {
+        tuple(sorted(sample.labels.items())): sample.value
+        for metric in REGISTRY.collect()
+        for sample in metric.samples
+        if sample.name == metric_name
+    }
+
+
+def _success_kwargs_with_rate_limit_headers(additional_headers: Mapping[str, object] | None) -> dict[str, object]:
+    return {
+        "model": "claude-haiku-4-5",
+        "litellm_params": {"metadata": {}},
+        "standard_logging_object": {
+            "id": "t",
+            "call_type": "completion",
+            "response_cost": 0.001,
+            "status": "success",
+            "total_tokens": 20,
+            "prompt_tokens": 15,
+            "completion_tokens": 5,
+            "startTime": 1.0,
+            "endTime": 2.0,
+            "completionStartTime": 1.5,
+            "model": "claude-haiku-4-5",
+            "model_id": "model-123",
+            "model_group": "anthropic-haiku-4-5",
+            "api_base": "https://api.anthropic.com",
+            "custom_llm_provider": "anthropic",
+            "request_tags": [],
+            "end_user": None,
+            "cache_hit": False,
+            "stream": False,
+            "response": None,
+            "model_parameters": None,
+            "metadata": {
+                "user_api_key_hash": "key-hash",
+                "user_api_key_alias": "key-alias",
+                "user_api_key_team_id": "team-id",
+                "user_api_key_team_alias": "team-alias",
+                "user_api_key_user_id": "u",
+                "user_api_key_user_email": "e@x.com",
+                "user_api_key_org_id": None,
+                "user_api_key_org_alias": None,
+                "requester_metadata": None,
+                "user_api_key_end_user_id": None,
+                "usage_object": None,
+            },
+            "hidden_params": {
+                "litellm_overhead_time_ms": None,
+                "additional_headers": additional_headers,
+            },
+        },
+    }
+
+
+async def _run_success_event(
+    additional_headers: Mapping[str, object] | None, logger: PrometheusLogger | None = None
+) -> None:
+    import datetime
+
+    now = datetime.datetime.now()
+    await (logger or PrometheusLogger()).async_log_success_event(
+        _success_kwargs_with_rate_limit_headers(additional_headers), None, now, now
+    )
+
+
+@pytest.mark.asyncio
+async def test_should_emit_key_and_team_rate_limit_allowed_and_used_from_v3_headers():
+    """
+    LIT-1672: the v3 limiter mirrors ``x-ratelimit-{api_key,team}-{limit,remaining}-*``
+    into the logging payload. The gauges must expose the configured limit as-is
+    and the window consumption as ``limit - remaining`` for each key / team
+    dimension, split by ``rate_limit_type``.
+    """
+    _clear_prometheus_registry()
+    try:
+        await _run_success_event(
+            {
+                "x-ratelimit-api_key-limit-requests": 10,
+                "x-ratelimit-api_key-remaining-requests": 7,
+                "x-ratelimit-api_key-limit-tokens": 20000,
+                "x-ratelimit-api_key-remaining-tokens": 19947,
+                "x-ratelimit-team-limit-requests": 50,
+                "x-ratelimit-team-remaining-requests": 47,
+                "x-ratelimit-team-limit-tokens": 40000,
+                "x-ratelimit-team-remaining-tokens": 39960,
+                "x-ratelimit-model_per_key-limit-requests": 5,
+                "x-ratelimit-model_per_key-remaining-requests": 1,
+            }
+        )
+
+        key_requests = (
+            ("api_key_alias", "key-alias"),
+            ("hashed_api_key", "key-hash"),
+            ("rate_limit_type", "requests"),
+        )
+        key_tokens = (
+            ("api_key_alias", "key-alias"),
+            ("hashed_api_key", "key-hash"),
+            ("rate_limit_type", "tokens"),
+        )
+        team_requests = (
+            ("rate_limit_type", "requests"),
+            ("team", "team-id"),
+            ("team_alias", "team-alias"),
+        )
+        team_tokens = (
+            ("rate_limit_type", "tokens"),
+            ("team", "team-id"),
+            ("team_alias", "team-alias"),
+        )
+
+        assert _collected_samples("litellm_api_key_rate_limit_allowed_metric") == {
+            key_requests: 10,
+            key_tokens: 20000,
+        }
+        assert _collected_samples("litellm_api_key_rate_limit_used_metric") == {
+            key_requests: 3,
+            key_tokens: 53,
+        }
+        assert _collected_samples("litellm_team_rate_limit_allowed_metric") == {
+            team_requests: 50,
+            team_tokens: 40000,
+        }
+        assert _collected_samples("litellm_team_rate_limit_used_metric") == {
+            team_requests: 3,
+            team_tokens: 40,
+        }
+    finally:
+        _clear_prometheus_registry()
+
+
+@pytest.mark.asyncio
+async def test_should_emit_only_the_dimensions_the_limiter_enforced():
+    """
+    A key with only ``rpm_limit`` set and no team limits produces only the
+    key/requests headers, so no tokens series and no team series may appear
+    (a phantom 0 or sys.maxsize series would misreport an unlimited dimension).
+    """
+    _clear_prometheus_registry()
+    try:
+        await _run_success_event(
+            {
+                "x-ratelimit-api_key-limit-requests": 10,
+                "x-ratelimit-api_key-remaining-requests": 10,
+            }
+        )
+
+        key_requests = (
+            ("api_key_alias", "key-alias"),
+            ("hashed_api_key", "key-hash"),
+            ("rate_limit_type", "requests"),
+        )
+        assert _collected_samples("litellm_api_key_rate_limit_allowed_metric") == {key_requests: 10}
+        assert _collected_samples("litellm_api_key_rate_limit_used_metric") == {key_requests: 0}
+        assert _collected_samples("litellm_team_rate_limit_allowed_metric") == {}
+        assert _collected_samples("litellm_team_rate_limit_used_metric") == {}
+    finally:
+        _clear_prometheus_registry()
+
+
+@pytest.mark.asyncio
+async def test_should_drop_key_and_team_series_once_the_limiter_stops_reporting_a_limit():
+    """
+    Removing a key's ``rpm_limit`` / ``tpm_limit`` (or a team's ``tpm_limit``)
+    makes the v3 limiter stop emitting that descriptor's headers on later
+    requests. The old allowed/used samples must disappear instead of keeping
+    a limit that no longer exists on the scrape.
+    """
+    _clear_prometheus_registry()
+    try:
+        logger = PrometheusLogger()
+        await _run_success_event(
+            {
+                "x-ratelimit-api_key-limit-requests": 10,
+                "x-ratelimit-api_key-remaining-requests": 7,
+                "x-ratelimit-api_key-limit-tokens": 20000,
+                "x-ratelimit-api_key-remaining-tokens": 19947,
+                "x-ratelimit-team-limit-requests": 50,
+                "x-ratelimit-team-remaining-requests": 47,
+                "x-ratelimit-team-limit-tokens": 40000,
+                "x-ratelimit-team-remaining-tokens": 39960,
+            },
+            logger=logger,
+        )
+        await _run_success_event(
+            {
+                "x-ratelimit-team-limit-requests": 50,
+                "x-ratelimit-team-remaining-requests": 46,
+            },
+            logger=logger,
+        )
+
+        team_requests = (
+            ("rate_limit_type", "requests"),
+            ("team", "team-id"),
+            ("team_alias", "team-alias"),
+        )
+        assert _collected_samples("litellm_api_key_rate_limit_allowed_metric") == {}
+        assert _collected_samples("litellm_api_key_rate_limit_used_metric") == {}
+        assert _collected_samples("litellm_team_rate_limit_allowed_metric") == {team_requests: 50}
+        assert _collected_samples("litellm_team_rate_limit_used_metric") == {team_requests: 4}
+    finally:
+        _clear_prometheus_registry()
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "additional_headers",
+    [
+        None,
+        {"x-ratelimit-model_per_key-remaining-requests": 42},
+        {"x-ratelimit-api_key-limit-requests": 10},
+        {"x-ratelimit-api_key-limit-requests": "10", "x-ratelimit-api_key-remaining-requests": "7"},
+        {"x-ratelimit-team-limit-tokens": True, "x-ratelimit-team-remaining-tokens": 5},
+    ],
+)
+async def test_should_emit_no_key_or_team_rate_limit_series_without_a_complete_int_pair(
+    additional_headers,
+):
+    _clear_prometheus_registry()
+    try:
+        await _run_success_event(additional_headers)
+
+        for metric_name in KEY_AND_TEAM_RATE_LIMIT_METRICS:
+            assert _collected_samples(metric_name) == {}, metric_name
+    finally:
+        _clear_prometheus_registry()
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
index 0e1c832ebf5..b7f0ca1efe1 100644
--- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
@@ -1522,7 +1522,7 @@ def test_gpt_5_6_alias_prices_match_sol(local_model_cost_map):
     sol = litellm.model_cost["gpt-5.6-sol"]
 
     cost_fields = sorted(field for field in sol if "cost" in field)
-    assert len(cost_fields) == 23
+    assert len(cost_fields) == 27
 
     for field in cost_fields:
         assert alias.get(field) == sol.get(field), field
@@ -4039,8 +4039,8 @@ def test_fast_service_tier_matches_priority_above_the_context_threshold(_local_m
     )
 
     assert fast == priority
-    assert fast[0] == pytest.approx(300_000 * 8e-06, rel=1e-9)
-    assert fast[1] == pytest.approx(1_000 * 3e-05, rel=1e-9)
+    assert fast[0] == pytest.approx(300_000 * 1.6e-05, rel=1e-9)
+    assert fast[1] == pytest.approx(1_000 * 6e-05, rel=1e-9)
 
 
 def test_priority_reasoning_tokens_bill_at_the_priority_output_rate(_local_model_cost_map):
@@ -4200,6 +4200,86 @@ def test_generic_cost_per_token_gemini_37_flash(_local_model_cost_map):
     assert completion_cost == pytest.approx(0.001875)
 
 
+GEMINI_38_FLASH_LAUNCH_PRICING = [
+    ("gemini-3.8-flash", 7.5e-07, 3.75e-06, 7.5e-08),
+    ("gemini/gemini-3.8-flash", 7.5e-07, 3.75e-06, 7.5e-08),
+    ("vertex_ai/gemini-3.8-flash", 7.5e-07, 3.75e-06, 7.5e-08),
+]
+
+
+@pytest.mark.parametrize("model,input_cost,output_cost,cache_read_cost", GEMINI_38_FLASH_LAUNCH_PRICING)
+def test_gemini_38_flash_launch_pricing(model, input_cost, output_cost, cache_read_cost, _local_model_cost_map):
+    model_cost_map = litellm.model_cost[model]
+    assert model_cost_map["input_cost_per_token"] == input_cost
+    assert model_cost_map["output_cost_per_token"] == output_cost
+    assert model_cost_map["output_cost_per_reasoning_token"] == output_cost
+    assert model_cost_map["cache_read_input_token_cost"] == cache_read_cost
+    assert model_cost_map["mode"] == "chat"
+    assert model_cost_map["supports_reasoning"] is True
+    assert model_cost_map["supports_function_calling"] is True
+    assert model_cost_map["max_input_tokens"] == 1048576
+
+
+GEMINI_38_FLASH_FIELDS_SHARED_WITH_37_FLASH = (
+    "input_cost_per_token",
+    "output_cost_per_token",
+    "output_cost_per_reasoning_token",
+    "cache_read_input_token_cost",
+    "input_cost_per_token_batches",
+    "output_cost_per_token_batches",
+    "input_cost_per_token_flex",
+    "output_cost_per_token_flex",
+    "cache_read_input_token_cost_flex",
+    "input_cost_per_token_priority",
+    "output_cost_per_token_priority",
+    "cache_read_input_token_cost_priority",
+    "search_context_cost_per_query",
+    "google_maps_grounding_cost_per_query",
+    "prompt_cache_min_tokens",
+    "max_input_tokens",
+    "max_output_tokens",
+    "supports_reasoning",
+    "supports_function_calling",
+    "supports_prompt_caching",
+    "supports_vision",
+    "supports_pdf_input",
+    "supports_audio_input",
+    "supports_video_input",
+    "supports_response_schema",
+    "supports_tool_choice",
+    "supports_web_search",
+    "supports_url_context",
+)
+
+
+@pytest.mark.parametrize("prefix", ["", "gemini/", "vertex_ai/"])
+def test_gemini_38_flash_matches_37_flash_promotional_pricing(prefix, _local_model_cost_map):
+    new_model = litellm.model_cost[f"{prefix}gemini-3.8-flash"]
+    old_model = litellm.model_cost[f"{prefix}gemini-3.7-flash"]
+    for field in GEMINI_38_FLASH_FIELDS_SHARED_WITH_37_FLASH:
+        assert new_model[field] == old_model[field], field
+
+
+def test_generic_cost_per_token_gemini_38_flash(_local_model_cost_map):
+    usage = Usage(
+        prompt_tokens=1000,
+        completion_tokens=500,
+        total_tokens=1500,
+        completion_tokens_details=CompletionTokensDetailsWrapper(
+            reasoning_tokens=200,
+            text_tokens=300,
+        ),
+        prompt_tokens_details=PromptTokensDetailsWrapper(text_tokens=1000),
+    )
+    prompt_cost, completion_cost = generic_cost_per_token(
+        model="gemini-3.8-flash",
+        usage=usage,
+        custom_llm_provider="gemini",
+    )
+    assert prompt_cost == pytest.approx(0.00075)
+    assert completion_cost == pytest.approx(0.001875)
+
+
 def test_grok_46_launch_pricing(_local_model_cost_map):
     model_cost_map = litellm.model_cost["xai/grok-4.6"]
     assert model_cost_map["input_cost_per_token"] == 2e-06
diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py
index 64c96b575c5..dd2d45f00c6 100644
--- a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py
+++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py
@@ -2932,6 +2932,28 @@ def test_add_cache_point_tool_block_passes_ttl_for_claude_4_5(monkeypatch):
             monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", old_env)
 
 
+def test_add_cache_point_tool_block_stands_down_for_model_without_prompt_caching(monkeypatch):
+    """A tool carrying cache_control must not become a cachePoint for a Bedrock model
+    whose cost-map entry lacks prompt caching support, since Bedrock rejects the whole
+    request. An unmapped id keeps emitting so ARN deployments do not lose caching."""
+    from litellm.litellm_core_utils.prompt_templates.factory import (
+        add_cache_point_tool_block,
+    )
+
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    tool = {"cache_control": {"type": "ephemeral"}}
+
+    assert add_cache_point_tool_block(tool, model="nvidia.nemotron-super-3-120b") is None
+    assert add_cache_point_tool_block(tool, model="us.nvidia.nemotron-super-3-120b") is None
+    assert add_cache_point_tool_block(
+        tool, model="arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123"
+    ) == {"cachePoint": {"type": "default"}}
+    assert add_cache_point_tool_block(tool, model="us.anthropic.claude-sonnet-4-5-20250929-v1:0") == {
+        "cachePoint": {"type": "default"}
+    }
+
+
 def test_bedrock_tools_pt_passes_ttl_for_claude_4_5(monkeypatch):
     """
     End-to-end: _bedrock_tools_pt should produce cachePoint blocks with ttl
diff --git a/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py b/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py
index 8c0e8ee5d02..a374e03d1c7 100644
--- a/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py
+++ b/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py
@@ -256,14 +256,12 @@ def test_get_model_cost_map_stamps_loaded_at(monkeypatch):
     from litellm.litellm_core_utils import get_model_cost_map as module
 
     monkeypatch.setattr(module._cost_map_source_info, "loaded_at", None)
-    monkeypatch.setattr(
-        module.GetModelCostMap,
-        "fetch_remote_model_cost_map",
-        staticmethod(lambda url, timeout=5: _load_root_cost_map()),
+    client, _calls = _mock_client(
+        [httpx.Response(200, content=_real_map_bytes())], client_cls=httpx.Client
     )
 
     before = datetime.now(timezone.utc)
-    module.get_model_cost_map(url="https://example.invalid/cost_map.json")
+    module.get_model_cost_map(url="https://example.invalid/cost_map.json", client=client)
     loaded_at = module.get_model_cost_map_loaded_at()
 
     assert loaded_at is not None
@@ -308,7 +306,7 @@ def _unset_local_cost_map_env(monkeypatch):
     monkeypatch.delenv("LITELLM_LOCAL_MODEL_COST_MAP", raising=False)
 
 
-def _mock_client(outcomes):
+def _mock_client(outcomes, client_cls=httpx.AsyncClient):
     """httpx client over a MockTransport serving one outcome per request; an exception instance is raised."""
     calls = {"count": 0}
 
@@ -320,7 +318,7 @@ def _mock_client(outcomes):
             raise outcome
         return outcome
 
-    return httpx.AsyncClient(transport=httpx.MockTransport(handler)), calls
+    return client_cls(transport=httpx.MockTransport(handler)), calls
 
 
 @pytest.mark.asyncio
@@ -450,3 +448,97 @@ async def test_refetch_respects_local_env_override(monkeypatch):
     )
     assert isinstance(result, ModelCostMapReloaded)
     assert len(result.model_cost_map) > 100
+
+
+# ---------------------------------------------------------------------------
+# get_model_cost_map: the boot-time load retries transient failures like a reload does
+# ---------------------------------------------------------------------------
+
+from litellm.litellm_core_utils.get_model_cost_map import (
+    get_model_cost_map,
+    get_model_cost_map_source_info,
+)
+
+
+class _SyncSleepRecorder:
+    """Injected in place of time.sleep so the boot path's waits are asserted without delay."""
+
+    def __init__(self):
+        self.waits = []
+
+    def __call__(self, seconds: float) -> None:
+        self.waits.append(seconds)
+
+
+def test_boot_load_retries_transient_failures_instead_of_falling_back():
+    """A refused connection then a 503 at pod boot used to pin the process to the bundled
+    backup for its lifetime; both are transient and must be retried before giving up."""
+    client, calls = _mock_client(
+        [
+            httpx.ConnectError("connection refused"),
+            httpx.Response(503),
+            httpx.Response(200, content=_real_map_bytes()),
+        ],
+        client_cls=httpx.Client,
+    )
+    sleeper = _SyncSleepRecorder()
+
+    cost_map = get_model_cost_map(url=_URL, sleep=sleeper, rng=random.Random(0), client=client)
+
+    assert calls["count"] == 3
+    assert len(sleeper.waits) == 2
+    assert 2.0 <= sleeper.waits[0] < 3.0
+    assert 4.0 <= sleeper.waits[1] < 5.0
+    source = get_model_cost_map_source_info()
+    assert source["source"] == "remote"
+    assert source["fallback_reason"] is None
+    assert cost_map.keys() >= _load_root_cost_map().keys() - {"sample_spec", FALLBACK_GENERALIZATIONS_KEY}
+
+
+def test_boot_load_honors_retry_after_then_falls_back_after_max_attempts():
+    """An outage longer than the retry budget still ends on the bundled backup, and the
+    recorded fallback reason says how many attempts were spent so operators can tell."""
+    client, calls = _mock_client(
+        [httpx.Response(429, headers={"Retry-After": "7"})], client_cls=httpx.Client
+    )
+    sleeper = _SyncSleepRecorder()
+
+    cost_map = get_model_cost_map(url=_URL, sleep=sleeper, rng=random.Random(0), client=client)
+
+    assert calls["count"] == 3
+    assert sleeper.waits == [7.0, 7.0]
+    source = get_model_cost_map_source_info()
+    assert source["source"] == "local"
+    assert "after 3 attempts" in source["fallback_reason"]
+    assert len(cost_map) > 100
+
+
+def test_boot_load_does_not_retry_permanent_failures():
+    """A 404 or a malformed URL cannot heal by waiting: one attempt, no sleeps, backup."""
+    client, calls = _mock_client([httpx.Response(404)], client_cls=httpx.Client)
+    sleeper = _SyncSleepRecorder()
+
+    get_model_cost_map(url=_URL, sleep=sleeper, rng=random.Random(0), client=client)
+    assert calls["count"] == 1
+    assert sleeper.waits == []
+    assert get_model_cost_map_source_info()["source"] == "local"
+
+    get_model_cost_map(url="not a url", sleep=sleeper, rng=random.Random(0))
+    assert sleeper.waits == []
+    assert get_model_cost_map_source_info()["source"] == "local"
+
+
+def test_boot_load_respects_local_env_override(monkeypatch):
+    """LITELLM_LOCAL_MODEL_COST_MAP=True still short-circuits to the backup with zero HTTP."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+
+    def _fail(request):
+        raise AssertionError("no HTTP request should be made when local map is forced")
+
+    cost_map = get_model_cost_map(
+        url=_URL,
+        sleep=_SyncSleepRecorder(),
+        client=httpx.Client(transport=httpx.MockTransport(_fail)),
+    )
+    assert len(cost_map) > 100
+    assert get_model_cost_map_source_info()["is_env_forced"] is True
diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py b/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py
index 8ac050a04f9..bacbcbf132b 100644
--- a/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py
+++ b/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py
@@ -592,6 +592,59 @@ def test_stream_chunk_builder_litellm_usage_chunks():
     assert usage.total_tokens == 77
 
 
+def test_calculate_usage_honors_openai_sdk_completion_usage_chunks():
+    from openai.types.completion_usage import CompletionUsage
+
+    content_chunk = ModelResponseStream(
+        id="chatcmpl-sdk-usage-1",
+        created=1745513206,
+        model="mantle-claude",
+        object="chat.completion.chunk",
+        system_fingerprint=None,
+        choices=[
+            StreamingChoices(
+                finish_reason="stop",
+                index=0,
+                delta=Delta(
+                    provider_specific_fields=None,
+                    content="ok",
+                    role=None,
+                    function_call=None,
+                    tool_calls=None,
+                    audio=None,
+                ),
+                logprobs=None,
+            )
+        ],
+        provider_specific_fields=None,
+        stream_options={"include_usage": True},
+    )
+    usage_chunk = ModelResponseStream(
+        id="chatcmpl-sdk-usage-1",
+        created=1745513207,
+        model="mantle-claude",
+        object="chat.completion.chunk",
+        system_fingerprint=None,
+        choices=[],
+        provider_specific_fields=None,
+        stream_options={"include_usage": True},
+    )
+    usage_chunk.usage = CompletionUsage(
+        prompt_tokens=20, completion_tokens=60, total_tokens=80, cost=0.000704
+    )
+    assert type(usage_chunk.usage) is CompletionUsage
+
+    chunks = [content_chunk, usage_chunk]
+    usage = ChunkProcessor(chunks=chunks).calculate_usage(
+        chunks=chunks, model="mantle-claude", completion_output=""
+    )
+
+    assert usage.prompt_tokens == 20
+    assert usage.completion_tokens == 60
+    assert usage.total_tokens == 80
+    assert getattr(usage, "cost", None) == pytest.approx(0.000704)
+
+
 def test_get_model_from_chunks_azure_model_router():
     """
     Test that _get_model_from_chunks finds the actual model from Azure Model Router chunks.
diff --git a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
index bd750a47f63..043537f8c1f 100644
--- a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
+++ b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
@@ -3,11 +3,13 @@ import threading
 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
 from unittest.mock import AsyncMock, MagicMock, patch
 
+import httpx
 import pytest
 
 import litellm
 from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.llms.anthropic.chat.handler import ModelResponseIterator, make_call
+from litellm.llms.custom_httpx.http_handler import HTTPHandler
 from litellm.types.llms.openai import (
     ChatCompletionToolCallChunk,
     ChatCompletionToolCallFunctionChunk,
@@ -46,6 +48,43 @@ async def test_make_call_passes_logging_obj_to_client_post():
     assert call_kwargs.get("logging_obj") is logging_obj
 
 
+def test_anthropic_completion_does_not_send_deployment_default_limits():
+    captured_requests: list[httpx.Request] = []
+
+    def respond(request: httpx.Request) -> httpx.Response:
+        captured_requests.append(request)
+        return httpx.Response(
+            200,
+            json={
+                "id": "msg_default_limits",
+                "type": "message",
+                "role": "assistant",
+                "model": "claude-3-5-haiku-20241022",
+                "content": [{"type": "text", "text": "Hello"}],
+                "stop_reason": "end_turn",
+                "stop_sequence": None,
+                "usage": {"input_tokens": 1, "output_tokens": 1},
+            },
+        )
+
+    client = HTTPHandler(client=httpx.Client(transport=httpx.MockTransport(respond)))
+    try:
+        litellm.completion(
+            model="anthropic/claude-3-5-haiku-20241022",
+            messages=[{"role": "user", "content": "Hello"}],
+            api_key="test-key",
+            client=client,
+            default_api_key_rpm_limit=60,
+            default_api_key_tpm_limit=5000000,
+        )
+    finally:
+        client.close()
+
+    request_body = json.loads(captured_requests[0].content)
+    assert "default_api_key_rpm_limit" not in request_body
+    assert "default_api_key_tpm_limit" not in request_body
+
+
 def test_redacted_thinking_content_block_delta():
     chunk = {
         "type": "content_block_start",
diff --git a/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py b/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py
index 8e67a7e3438..21e3239f623 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py
@@ -96,10 +96,8 @@ def _completion_kwargs(**overrides):
     return kwargs
 
 
-def _run(**overrides):
-    with patch.object(
-        BedrockConverseLLM, "get_credentials", return_value=RESOLVED_CREDENTIALS
-    ):
+def _run(*, credentials: Credentials | None = RESOLVED_CREDENTIALS, **overrides):
+    with patch.object(BedrockConverseLLM, "get_credentials", return_value=credentials):
         return BedrockConverseLLM().completion(**_completion_kwargs(**overrides))
 
 
@@ -360,7 +358,7 @@ async def test_async_completion_logs_pre_call_by_default():
 
 def _sync_client_returning_converse_response():
     client = MagicMock()
-    client.post = lambda **_kwargs: httpx.Response(
+    client.post.side_effect = lambda **_kwargs: httpx.Response(
         200,
         json=CONVERSE_RESPONSE,
         request=httpx.Request("POST", "https://bedrock-runtime.us-west-2.amazonaws.com"),
@@ -487,3 +485,31 @@ def test_post_call_is_not_logged_twice_when_the_sync_rust_call_declines():
     assert response.choices[0].message.content == "hi"
     assert len(calls["post_call"]) == 1
     assert "hi" in calls["post_call"][0]["original_response"]
+
+
+def test_bearer_token_auth_serves_when_boto3_resolves_no_sigv4_credentials(monkeypatch):
+    """With only `AWS_BEARER_TOKEN_BEDROCK` configured boto3 resolves no
+    credentials at all. Preparing the Rust handoff must not dereference that
+    None: the bearer token signs the request on its own."""
+    monkeypatch.setenv("AWS_BEARER_TOKEN_BEDROCK", "bedrock-bearer-token")
+    client = _sync_client_returning_converse_response()
+
+    response = _run(credentials=None, litellm_params={}, client=client)
+
+    assert response.choices[0].message.content == "hi"
+    sent_headers = client.post.call_args.kwargs["headers"]
+    assert sent_headers["Authorization"] == "Bearer bedrock-bearer-token"
+
+
+def test_the_rust_opt_in_needs_no_sigv4_principal():
+    """The core resolves the bearer token itself, so a bearer-only deployment
+    keeps its opt-in and the gate sees no aws_* credential keys to sign with."""
+    seen = _inject()
+
+    response = _run(credentials=None, api_key="bedrock-bearer-token")
+
+    assert response.choices[0].message.content == "hello from rust"
+    params = seen["call"][0]["optional_params"]
+    assert not {"aws_access_key_id", "aws_secret_access_key", "aws_session_token"} & params.keys()
+    assert params["aws_region_name"] == "us-east-1"
+    assert seen["call"][0]["api_key"] == "bedrock-bearer-token"
diff --git a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
index 4f53d3481de..70f3153ed7e 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
@@ -5248,6 +5248,84 @@ def test_cache_control_injection_tool_config_drops_ttl_for_unsupported_model():
     assert tools[-1] == {"cachePoint": {"type": "default"}}
 
 
+@pytest.mark.parametrize(
+    ("model", "expects_cache_points"),
+    [
+        pytest.param("nvidia.nemotron-super-3-120b", False, id="mapped-model-without-prompt-caching"),
+        pytest.param("us.nvidia.nemotron-super-3-120b", False, id="regional-prefix-resolves-through-base-model"),
+        pytest.param(
+            "us.anthropic.claude-3-5-sonnet-20240620-v1:0", False, id="claude-named-but-not-caching-on-bedrock"
+        ),
+        pytest.param("us.anthropic.claude-sonnet-4-5-20250929-v1:0", True, id="mapped-model-with-prompt-caching"),
+        pytest.param(
+            "arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123",
+            True,
+            id="unmapped-arn-keeps-emitting",
+        ),
+    ],
+)
+def test_cache_points_emitted_only_for_models_that_support_prompt_caching(model, expects_cache_points, monkeypatch):
+    """Bedrock rejects cachePoint blocks for models without prompt caching support
+    ("You invoked an unsupported model or your request did not allow prompt caching"),
+    and clients like Claude Code attach cache_control to every request, so a map-known
+    model without the capability must not receive them. Unmapped ids (application
+    inference profile ARNs, models newer than the map) keep emitting so existing
+    caching setups never silently degrade."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+    body = AmazonConverseConfig().transform_request(
+        model=model,
+        messages=[
+            {"role": "system", "content": [{"type": "text", "text": "sys", "cache_control": {"type": "ephemeral"}}]},
+            {"role": "user", "content": [{"type": "text", "text": "hi", "cache_control": {"type": "ephemeral"}}]},
+        ],
+        optional_params={},
+        litellm_params={},
+        headers={},
+    )
+
+    assert ("cachePoint" in json.dumps(body)) is expects_cache_points
+    assert body["system"][0]["text"] == "sys"
+    assert body["messages"][0]["content"][0]["text"] == "hi"
+
+
+def test_tool_config_cachepoint_not_placed_or_credited_for_model_without_prompt_caching(monkeypatch):
+    """The tool_config injection point must stand down with the rest of the cachePoint
+    emission when the model cannot cache, and spend attribution must not credit the
+    gateway for a breakpoint that was never placed."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+    bucket: dict = {"user_api_key": "sk-test"}
+    data = AmazonConverseConfig()._transform_request_helper(
+        model="nvidia.nemotron-super-3-120b",
+        system_content_blocks=[],
+        optional_params={
+            "tools": [
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "get_weather",
+                        "description": "Get weather",
+                        "parameters": {
+                            "type": "object",
+                            "properties": {"location": {"type": "string"}},
+                            "required": ["location"],
+                        },
+                    },
+                }
+            ],
+            "cache_control_injection_points": [{"location": "tool_config"}],
+        },
+        messages=[{"role": "user", "content": "hi"}],
+        litellm_params={"metadata": bucket, "litellm_metadata": None, "model_info": {"id": "dep-bedrock"}},
+    )
+
+    assert "cachePoint" not in json.dumps(data.get("toolConfig", {}))
+    assert "litellm_gateway_injected_cache" not in bucket
+
+
 def test_translate_response_format_json_schema_still_injects_tool():
     """
     response_format with an explicit json_schema should still use the
@@ -6211,7 +6289,7 @@ def test_message_level_cache_control_drops_ttl_for_unsupported_model(ttl_target)
 
     result = _bedrock_converse_messages_pt(
         messages=_agentic_messages_with_ttl(ttl_target),
-        model="anthropic.claude-3-5-sonnet-20240620-v1:0",
+        model="anthropic.claude-3-5-sonnet-20241022-v2:0",
         llm_provider="bedrock_converse",
     )
 
diff --git a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py
index 7d07ac947b1..f854d806bdc 100644
--- a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py
+++ b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py
@@ -15,6 +15,7 @@ from unittest.mock import MagicMock, patch
 from botocore.awsrequest import AWSPreparedRequest, AWSRequest
 from botocore.auth import SigV4Auth
 from botocore.credentials import Credentials
+from botocore.exceptions import NoCredentialsError
 
 import litellm
 from litellm.llms.bedrock.base_aws_llm import (
@@ -801,6 +802,23 @@ def test_get_request_headers_with_sigv4():
         assert result == mock_request.prepare.return_value
 
 
+def test_get_request_headers_without_credentials_or_bearer_token_raises_no_credentials():
+    """Bearer-token auth needs no SigV4 principal, so `credentials` may be None.
+    Reaching the SigV4 branch with neither must fail the way botocore always
+    has instead of signing with a missing principal."""
+    llm = BaseAWSLLM()
+
+    with patch.dict(os.environ, {}, clear=True), pytest.raises(NoCredentialsError):
+        llm.get_request_headers(
+            credentials=None,
+            aws_region_name="us-west-2",
+            extra_headers=None,
+            endpoint_url="https://api.example.com",
+            data='{"prompt": "test"}',
+            headers={"Content-Type": "application/json"},
+        )
+
+
 def test_sigv4_matches_rust_golden_vector():
     request = AWSRequest(
         method="POST",
diff --git a/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py b/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py
index 4c92c52d556..7509e35e3f7 100644
--- a/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py
+++ b/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py
@@ -1,7 +1,11 @@
 import asyncio
 import concurrent.futures
+import socket
+import sys
+from typing import Final
 
 import aiohttp
+import aiohttp.abc
 import aiohttp.client_exceptions
 import aiohttp.http_exceptions
 import httpx
@@ -1140,3 +1144,55 @@ async def test_stopped_loop_session_disposed_synchronously_on_recycle():
     finally:
         await new_session.close()
         result["loop"].close()
+
+
+class _CancellingResolver(aiohttp.abc.AbstractResolver):
+    """Cancels the given task (or, by default, aiohttp's shielded DNS child task) mid-lookup."""
+
+    def __init__(self, task_to_cancel: "asyncio.Task[object] | None" = None):
+        self._task_to_cancel: Final = task_to_cancel
+
+    async def resolve(
+        self, host: str, port: int = 0, family: socket.AddressFamily = socket.AF_INET
+    ) -> list[aiohttp.abc.ResolveResult]:
+        target: Final = self._task_to_cancel or asyncio.current_task()
+        assert target is not None
+        target.cancel()
+        await asyncio.sleep(0)
+        raise OSError("resolver finished after the task was cancelled")
+
+    async def close(self) -> None:
+        return None
+
+
+@pytest.mark.asyncio
+@pytest.mark.skipif(
+    sys.version_info < (3, 11), reason="Task.cancelling() is needed to tell the two cancellations apart"
+)
+async def test_internal_dns_cancellation_maps_to_connect_error():
+    """A CancelledError the request task never asked for must surface as a mapped httpx transport error."""
+    session = aiohttp.ClientSession(connector=aiohttp.TCPConnector(resolver=_CancellingResolver()))
+    transport = LiteLLMAiohttpTransport(client=session)
+    try:
+        with pytest.raises(httpx.ConnectError):
+            await transport.handle_async_request(httpx.Request("GET", "http://example.invalid/"))
+        current = asyncio.current_task()
+        assert current is not None and current.cancelling() == 0
+    finally:
+        await transport.aclose()
+
+
+@pytest.mark.asyncio
+async def test_genuine_request_cancellation_still_propagates():
+    """Cancelling the request task itself (client disconnect, shutdown) must still propagate unmapped."""
+    current = asyncio.current_task()
+    assert current is not None
+    session = aiohttp.ClientSession(connector=aiohttp.TCPConnector(resolver=_CancellingResolver(current)))
+    transport = LiteLLMAiohttpTransport(client=session)
+    try:
+        with pytest.raises(asyncio.CancelledError):
+            await transport.handle_async_request(httpx.Request("GET", "http://example.invalid/"))
+    finally:
+        if sys.version_info >= (3, 11):
+            current.uncancel()
+        await transport.aclose()
diff --git a/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py b/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py
index a29e0be4655..7dd6065063a 100644
--- a/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py
+++ b/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py
@@ -1559,3 +1559,87 @@ class TestScanOnlyToolResults:
         assert data["messages"][3]["content"] == "page says [BLOCKED] here"
         assert data["messages"][3]["tool_call_id"] == "call_1"
         assert data["messages"][4]["content"] == "and then?"
+
+
+class TestBuildBlockSseChunks:
+    """build_block_sse_chunks turns a streaming ModifyResponseException into 200 SSE chunks"""
+
+    def _exc(self, original_response=None):
+        from litellm.exceptions import ModifyResponseException
+
+        return ModifyResponseException(
+            message="Blocked by policy.",
+            model="gpt-5.4-mini",
+            request_data={},
+            guardrail_name="test",
+            original_response=original_response,
+        )
+
+    def _payloads(self, chunks):
+        return [json.loads(chunk.decode().removeprefix("data: ").strip()) for chunk in chunks]
+
+    def test_standalone_block_uses_fresh_identity_and_zero_usage(self):
+        handler = OpenAIChatCompletionsHandler()
+        first, final = self._payloads(handler.build_block_sse_chunks(self._exc(), stream_started=False))
+        assert first["id"].startswith("chatcmpl-")
+        assert first["model"] == "gpt-5.4-mini"
+        assert first["choices"][0]["delta"] == {"role": "assistant", "content": "Blocked by policy."}
+        assert first["choices"][0]["finish_reason"] is None
+        assert final["choices"][0]["delta"] == {}
+        assert final["choices"][0]["finish_reason"] == "content_filter"
+        assert final["usage"] == {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}
+
+    def test_continuation_reuses_stream_identity_and_real_usage(self):
+        handler = OpenAIChatCompletionsHandler()
+        yielded = [
+            {"id": "chatcmpl-live", "created": 1724900000, "model": "gpt-5.4-mini-2026-01-01"},
+        ]
+        original = yielded + [
+            {"id": "chatcmpl-live", "usage": {"prompt_tokens": 11, "completion_tokens": 5}},
+        ]
+        first, final = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=original), stream_started=True, responses_so_far=yielded
+            )
+        )
+        assert (first["id"], first["created"], first["model"]) == (
+            "chatcmpl-live",
+            1724900000,
+            "gpt-5.4-mini-2026-01-01",
+        )
+        assert first["choices"][0]["delta"] == {"content": "Blocked by policy."}
+        assert final["id"] == "chatcmpl-live"
+        assert final["usage"] == {"prompt_tokens": 11, "completion_tokens": 5, "total_tokens": 16}
+
+
+class TestCheckStreamingHasEnded:
+    """_check_streaming_has_ended lets end_of_stream_only withhold the finish chunk until moderation"""
+
+    def test_empty_and_content_only_chunks_are_not_ended(self):
+        handler = OpenAIChatCompletionsHandler()
+        assert handler._check_streaming_has_ended([]) is False
+        content_only = [
+            {"id": "chatcmpl-live", "choices": [{"index": 0, "delta": {"content": "hi"}, "finish_reason": None}]},
+            {"id": "chatcmpl-live", "choices": []},
+            {"id": "chatcmpl-live", "usage": {"prompt_tokens": 1, "completion_tokens": 1}},
+        ]
+        assert handler._check_streaming_has_ended(content_only) is False
+
+    def test_dict_finish_chunk_marks_stream_ended(self):
+        handler = OpenAIChatCompletionsHandler()
+        chunks = [
+            {"id": "chatcmpl-live", "choices": [{"index": 0, "delta": {"content": "hi"}, "finish_reason": None}]},
+            {"id": "chatcmpl-live", "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]},
+        ]
+        assert handler._check_streaming_has_ended(chunks) is True
+
+    def test_object_finish_chunk_marks_stream_ended(self):
+        from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
+
+        handler = OpenAIChatCompletionsHandler()
+        chunks = [
+            ModelResponseStream(
+                choices=[StreamingChoices(index=0, delta=Delta(content=None), finish_reason="stop")]
+            )
+        ]
+        assert handler._check_streaming_has_ended(chunks) is True
diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
index ad392d4962d..315b6948bd8 100644
--- a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
+++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
@@ -1321,3 +1321,219 @@ class TestOpenAIResponsesHandlerToolInjection:
         names = [t.get("name") for t in result["tools"]]
         assert "get_weather" in names
         assert "injected_tool" in names
+
+
+class TestBuildBlockSseChunks:
+    """build_block_sse_chunks turns a streaming ModifyResponseException into 200 SSE events"""
+
+    def _exc(self, original_response=None):
+        from litellm.exceptions import ModifyResponseException
+
+        return ModifyResponseException(
+            message="Blocked by policy.",
+            model="gpt-5.4-mini",
+            request_data={},
+            guardrail_name="test",
+            original_response=original_response,
+        )
+
+    def _payloads(self, chunks):
+        import json
+
+        return [json.loads(chunk.decode().removeprefix("data: ").strip()) for chunk in chunks]
+
+    def test_standalone_block_emits_complete_synthetic_stream(self):
+        handler = OpenAIResponsesHandler()
+        payloads = self._payloads(handler.build_block_sse_chunks(self._exc(), stream_started=False))
+        types = [payload["type"] for payload in payloads]
+        assert types[0] == "response.created"
+        assert types[-1] == "response.completed"
+        completed = payloads[-1]["response"]
+        assert completed["id"].startswith("resp_")
+        assert completed["model"] == "gpt-5.4-mini"
+        assert completed["output"][0]["content"][0]["text"] == "Blocked by policy."
+
+    def test_continuation_appends_item_at_next_output_index_with_real_usage(self):
+        handler = OpenAIResponsesHandler()
+        yielded = [
+            {"type": "response.created", "response": {"id": "resp_live", "model": "gpt-5.4-mini-2026-01-01"}},
+            {"type": "response.output_item.added", "output_index": 2, "item": {"id": "msg_orig"}},
+        ]
+        original = yielded + [
+            {
+                "type": "response.completed",
+                "response": {
+                    "id": "resp_live",
+                    "model": "gpt-5.4-mini-2026-01-01",
+                    "output": [],
+                    "usage": {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28},
+                },
+            }
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=original), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert "response.created" not in types
+        assert types[0] == "response.output_item.done"
+        assert payloads[0]["output_index"] == 2
+        assert payloads[0]["item"]["id"] == "msg_orig"
+        assert payloads[0]["item"]["status"] == "completed"
+        assert types[1] == "response.output_item.added"
+        assert payloads[1]["output_index"] == 3
+        completed = payloads[-1]["response"]
+        assert completed["id"] == "resp_live"
+        assert completed["model"] == "gpt-5.4-mini-2026-01-01"
+        assert completed["output"][0]["content"][0]["text"] == "Blocked by policy."
+        assert completed["usage"] == {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28}
+
+    def test_continuation_reads_usage_from_typed_completed_event(self):
+        from litellm.types.llms.openai import (
+            ResponseCompletedEvent,
+            ResponsesAPIResponse,
+            ResponsesAPIStreamEvents,
+        )
+
+        handler = OpenAIResponsesHandler()
+        original = [
+            ResponseCompletedEvent(
+                type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
+                response=ResponsesAPIResponse.model_validate(
+                    {
+                        "id": "resp_live",
+                        "created_at": 1,
+                        "model": "gpt-5.4-mini",
+                        "output": [],
+                        "usage": {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28},
+                    }
+                ),
+            )
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=original), stream_started=True, responses_so_far=[]
+            )
+        )
+        completed = payloads[-1]["response"]
+        assert completed["usage"]["input_tokens"] == 7
+        assert completed["usage"]["output_tokens"] == 21
+        assert completed["usage"]["total_tokens"] == 28
+
+    def test_continuation_closes_open_item_given_pydantic_events_with_enum_types(self):
+        from litellm.types.llms.openai import (
+            BaseLiteLLMOpenAIResponseObject,
+            ContentPartAddedEvent,
+            OutputItemAddedEvent,
+            OutputTextDeltaEvent,
+            ResponsesAPIStreamEvents,
+        )
+
+        handler = OpenAIResponsesHandler()
+        open_item = GenericResponseOutputItem.model_validate(
+            {"type": "message", "id": "msg_live", "status": "in_progress", "role": "assistant", "content": []}
+        )
+        yielded = [
+            OutputItemAddedEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, output_index=0, item=open_item
+            ),
+            ContentPartAddedEvent(
+                type=ResponsesAPIStreamEvents.CONTENT_PART_ADDED,
+                item_id="msg_live",
+                output_index=0,
+                content_index=0,
+                part=BaseLiteLLMOpenAIResponseObject.model_validate(
+                    {"type": "output_text", "text": "", "annotations": []}
+                ),
+            ),
+            OutputTextDeltaEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+                item_id="msg_live",
+                output_index=0,
+                content_index=0,
+                delta="partial ",
+            ),
+            OutputTextDeltaEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+                item_id="msg_live",
+                output_index=0,
+                content_index=0,
+                delta="text",
+            ),
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=yielded), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert types[:3] == [
+            "response.output_text.done",
+            "response.content_part.done",
+            "response.output_item.done",
+        ]
+        assert payloads[0]["text"] == "partial text"
+        assert payloads[2]["item"]["id"] == "msg_live"
+        assert payloads[2]["item"]["status"] == "completed"
+        assert payloads[2]["item"]["content"][0]["text"] == "partial text"
+        assert types[3] == "response.output_item.added"
+        assert payloads[3]["output_index"] == 1
+
+    def test_continuation_closes_open_function_call_as_incomplete(self):
+        handler = OpenAIResponsesHandler()
+        yielded = [
+            {"type": "response.created", "response": {"id": "resp_live", "model": "gpt-5.4-mini"}},
+            {
+                "type": "response.output_item.added",
+                "output_index": 0,
+                "item": {
+                    "id": "fc_live",
+                    "type": "function_call",
+                    "status": "in_progress",
+                    "call_id": "call_1",
+                    "name": "run_payment",
+                    "arguments": "",
+                },
+            },
+            {
+                "type": "response.function_call_arguments.delta",
+                "item_id": "fc_live",
+                "output_index": 0,
+                "delta": '{"amount": 100}',
+            },
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=yielded), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert types[0] == "response.output_item.done"
+        closed = payloads[0]["item"]
+        assert closed["id"] == "fc_live"
+        assert closed["type"] == "function_call"
+        assert closed["status"] == "incomplete"
+        assert closed["name"] == "run_payment"
+        assert "content" not in closed
+        assert types[1] == "response.output_item.added"
+        assert payloads[1]["output_index"] == 1
+        assert types[-1] == "response.completed"
+
+    def test_continuation_without_open_item_emits_no_closing_events(self):
+        handler = OpenAIResponsesHandler()
+        yielded = [
+            {"type": "response.created", "response": {"id": "resp_live", "model": "gpt-5.4-mini"}},
+            {"type": "response.in_progress", "response": {"id": "resp_live"}},
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=yielded), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert types[0] == "response.output_item.added"
+        assert types[-1] == "response.completed"
+        dones = [payload for payload in payloads if payload["type"] == "response.output_item.done"]
+        assert len(dones) == 1
+        assert dones[0]["item"]["content"][0]["text"] == "Blocked by policy."
diff --git a/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py
index 8a9ae4dae6d..62b4d003b45 100644
--- a/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py
+++ b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py
@@ -2,6 +2,7 @@
 Tests for Parallel AI Search API integration (v1 endpoint).
 """
 
+import json
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
@@ -30,13 +31,41 @@ MOCK_V1_RESPONSE = {
 }
 
 
-def _mock_response():
+def _mock_response(payload=None):
     mock_response = MagicMock()
     mock_response.status_code = 200
-    mock_response.json.return_value = MOCK_V1_RESPONSE
+    mock_response.json.return_value = payload if payload is not None else MOCK_V1_RESPONSE
     return mock_response
 
 
+@pytest.fixture
+def httpx_transport(monkeypatch):
+    monkeypatch.setattr(  # test-quality-ok: respx needs HTTPX enabled to fake the provider HTTP boundary.
+        litellm,
+        "disable_aiohttp_transport",
+        True,
+    )
+    litellm.in_memory_llm_clients_cache.flush_cache()
+    yield
+    litellm.in_memory_llm_clients_cache.flush_cache()
+
+
+@pytest.fixture
+def bundled_cost_map(monkeypatch):
+    """Price lookups against the bundled cost map.
+
+    litellm caches model-info lookups, so swapping ``model_cost`` only takes
+    effect once those caches are invalidated -- on the way in and back out.
+    """
+    from litellm.utils import _invalidate_model_cost_lowercase_map
+
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    _invalidate_model_cost_lowercase_map()
+    yield
+    monkeypatch.undo()
+    _invalidate_model_cost_lowercase_map()
+
+
 class TestParallelAISearch:
     @pytest.fixture(autouse=True)
     def _set_api_key(self, monkeypatch):
@@ -135,9 +164,7 @@ class TestParallelAISearch:
             json_data = mock_post.call_args.kwargs.get("json")
             assert json_data["mode"] == "basic"
 
-    @pytest.mark.parametrize(
-        "processor,expected_mode", [("base", "basic"), ("pro", "advanced")]
-    )
+    @pytest.mark.parametrize("processor,expected_mode", [("base", "basic"), ("pro", "advanced")])
     @pytest.mark.asyncio
     async def test_legacy_processor_maps_to_mode(self, processor, expected_mode):
         with patch(
@@ -222,9 +249,7 @@ class TestParallelAISearch:
                 "arxiv.org",
                 "nature.com",
             ]
-            assert advanced_settings["source_policy"]["exclude_domains"] == [
-                "reddit.com"
-            ]
+            assert advanced_settings["source_policy"]["exclude_domains"] == ["reddit.com"]
             assert advanced_settings["excerpt_settings"]["max_chars_per_result"] == 1500
 
             assert "max_results" not in json_data
@@ -306,10 +331,7 @@ class TestParallelAISearch:
             )
 
             call_args = mock_post.call_args
-            assert (
-                call_args.kwargs["url"]
-                == "https://proxy.internal.example.com/v1/search"
-            )
+            assert call_args.kwargs["url"] == "https://proxy.internal.example.com/v1/search"
 
     @pytest.mark.asyncio
     async def test_caller_api_base_without_key_is_refused(self, monkeypatch):
@@ -338,3 +360,147 @@ class TestParallelAISearch:
                 query="AI developments",
                 search_provider="parallel_ai",
             )
+
+    @pytest.mark.asyncio
+    async def test_flat_source_and_fetch_params_nest_under_advanced_settings(self, respx_mock, httpx_transport):
+        route = respx_mock.post("https://api.parallel.ai/v1/search").respond(json=MOCK_V1_RESPONSE)
+
+        await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+            objective="find peer-reviewed AI research",
+            include_domains=["arxiv.org"],
+            after_date="2026-01-01",
+            location="gb",
+            fetch_policy={"max_age_seconds": 600, "disable_cache_fallback": True},
+            client_model="claude-fable-5",
+        )
+
+        json_data = json.loads(route.calls[0].request.content)
+        assert json_data["objective"] == "find peer-reviewed AI research"
+        assert json_data["client_model"] == "claude-fable-5"
+
+        advanced_settings = json_data["advanced_settings"]
+        assert advanced_settings["location"] == "gb"
+        assert advanced_settings["fetch_policy"] == {
+            "max_age_seconds": 600,
+            "disable_cache_fallback": True,
+        }
+        assert advanced_settings["source_policy"]["include_domains"] == ["arxiv.org"]
+        assert advanced_settings["source_policy"]["after_date"] == "2026-01-01"
+
+        assert "include_domains" not in json_data
+        assert "after_date" not in json_data
+        assert "location" not in json_data
+        assert "fetch_policy" not in json_data
+
+    @pytest.mark.asyncio
+    async def test_response_preserves_raw_parallel_fields(self, respx_mock, httpx_transport):
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=MOCK_V1_RESPONSE)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+        )
+
+        dumped = response.model_dump()
+        assert dumped["search_id"] == "search_abc123"
+        assert dumped["session_id"] == "session_xyz"
+        assert dumped["parallel_usage"] == [{"name": "search_advanced", "count": 1}]
+
+        first = response.results[0].model_dump()
+        assert first["excerpts"] == ["First excerpt.", "Second excerpt."]
+
+    @pytest.mark.asyncio
+    async def test_response_normalizes_null_result_fields(self, respx_mock, httpx_transport):
+        response_payload = {
+            **MOCK_V1_RESPONSE,
+            "results": [{"url": None, "title": None, "publish_date": None, "excerpts": None}],
+        }
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+        )
+
+        assert len(response.results) == 1
+        result = response.results[0]
+        assert result.url == ""
+        assert result.title == ""
+        assert result.snippet == ""
+        assert result.date is None
+        assert result.model_dump()["excerpts"] == ()
+
+    @pytest.mark.parametrize(
+        "mode,usage,max_results,expected_cost",
+        [
+            ("turbo", [{"name": "sku_search", "count": 1}], None, 0.001),
+            ("fast", [{"name": "sku_search", "count": 1}], None, 0.001),
+            ("basic", [{"name": "sku_search", "count": 1}], None, 0.005),
+            ("advanced", [{"name": "sku_search", "count": 1}], None, 0.005),
+            (
+                "basic",
+                [
+                    {"name": "sku_search", "count": 1},
+                    {"name": "sku_search_additional_results", "count": 2},
+                ],
+                20,
+                0.007,
+            ),
+            ("basic", None, 20, 0.015),
+        ],
+    )
+    @pytest.mark.asyncio
+    async def test_search_cost_uses_mode_and_provider_usage(
+        self, mode, usage, max_results, expected_cost, bundled_cost_map, respx_mock, httpx_transport
+    ):
+        response_payload = {**MOCK_V1_RESPONSE, "usage": usage}
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+            mode=mode,
+            max_results=max_results,
+        )
+
+        assert response._hidden_params["response_cost"] == pytest.approx(expected_cost)
+
+    @pytest.mark.asyncio
+    async def test_search_cost_treats_keyword_queries_as_one_request(
+        self, bundled_cost_map, respx_mock, httpx_transport
+    ):
+        response_payload = {
+            **MOCK_V1_RESPONSE,
+            "usage": [{"name": "sku_search", "count": 1}],
+        }
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query=["AI developments", "machine learning trends"],
+            search_provider="parallel_ai",
+            mode="basic",
+        )
+
+        assert response._hidden_params["response_cost"] == pytest.approx(0.005)
+
+    @pytest.mark.asyncio
+    async def test_caller_cannot_supply_provider_usage(self, bundled_cost_map, respx_mock, httpx_transport):
+        """`_parallel_ai_usage` prices the request, so a caller must not be able to set it.
+
+        The provider reports no usage here, which is the case where a caller-supplied
+        value would otherwise survive into the cost calculation.
+        """
+        response_payload = {k: v for k, v in MOCK_V1_RESPONSE.items() if k != "usage"}
+        route = respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+            mode="basic",
+            _parallel_ai_usage=[{"name": "sku_search", "count": 0}],
+        )
+
+        assert response._hidden_params["response_cost"] == pytest.approx(0.005)
+        assert "_parallel_ai_usage" not in json.loads(route.calls[0].request.content)
diff --git a/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search_gateway.py b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search_gateway.py
new file mode 100644
index 00000000000..72c69fc622c
--- /dev/null
+++ b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search_gateway.py
@@ -0,0 +1,191 @@
+"""Gateway coverage for Parallel AI Search."""
+
+from __future__ import annotations
+
+from collections.abc import Iterator
+from typing import Final
+from unittest.mock import AsyncMock
+
+import httpx
+import pytest
+from fastapi.testclient import TestClient
+
+import litellm
+from litellm import Router
+from litellm.integrations.websearch_interception.handler import (
+    WebSearchInterceptionLogger,
+)
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
+from litellm.proxy import proxy_server
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+from litellm.types.utils import LlmProviders
+
+PARALLEL_SEARCH_URL: Final = "https://api.parallel.ai/v1/search"
+
+
+@pytest.fixture
+def client() -> TestClient:
+    return TestClient(proxy_server.app, raise_server_exceptions=False)
+
+
+@pytest.fixture
+def auth_as() -> Iterator[None]:
+    async def _authorized_request() -> UserAPIKeyAuth:
+        return UserAPIKeyAuth(
+            api_key="hashed-sk-test",
+            user_id="parallel-test-user",
+        )
+
+    previous: Final = proxy_server.app.dependency_overrides.get(user_api_key_auth)
+    proxy_server.app.dependency_overrides[user_api_key_auth] = _authorized_request
+    try:
+        yield
+    finally:
+        if previous is None:
+            proxy_server.app.dependency_overrides.pop(user_api_key_auth, None)
+        else:
+            proxy_server.app.dependency_overrides[user_api_key_auth] = previous
+
+
+def _parallel_search_body() -> dict[str, object]:
+    return {
+        "search_id": "search_parallel_gateway",
+        "results": [
+            {
+                "url": "https://example.com/parallel",
+                "title": "Parallel result",
+                "publish_date": "2026-08-13",
+                "excerpts": ["First excerpt", "Second excerpt"],
+            }
+        ],
+        "usage": [{"name": "sku_search", "count": 1}],
+    }
+
+
+def _parallel_router(mode: str = "turbo") -> Router:
+    return Router(
+        model_list=[],
+        search_tools=[
+            {
+                "search_tool_name": "parallel-search",
+                "litellm_params": {
+                    "search_provider": "parallel_ai",
+                    "api_key": "parallel-search-key",
+                    "mode": mode,
+                },
+            }
+        ],
+        num_retries=0,
+    )
+
+
+def _mock_async_post(
+    monkeypatch,
+    *,
+    url: str,
+    response_body: dict[str, object],
+) -> AsyncMock:
+    response = httpx.Response(
+        status_code=200,
+        json=response_body,
+        request=httpx.Request("POST", url),
+    )
+    mock_post = AsyncMock(return_value=response)
+    monkeypatch.setattr(AsyncHTTPHandler, "post", mock_post)
+    return mock_post
+
+
+def test_parallel_search_gateway_route(client, auth_as, monkeypatch):
+    """The named search route selects its configured Parallel Search tool.
+
+    The tool-level `mode` must survive the router hop, so the upstream request
+    is sent as `turbo` rather than falling back to the adapter default.
+    """
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    monkeypatch.setattr(proxy_server, "llm_router", _parallel_router())
+    mock_post = _mock_async_post(
+        monkeypatch,
+        url=PARALLEL_SEARCH_URL,
+        response_body=_parallel_search_body(),
+    )
+
+    response = client.post(
+        "/v1/search/parallel-search",
+        json={"query": "Parallel AI news", "max_results": 3},
+    )
+
+    assert response.status_code == 200, response.text
+    assert response.json()["results"] == [
+        {
+            "title": "Parallel result",
+            "url": "https://example.com/parallel",
+            "snippet": "First excerpt ... Second excerpt",
+            "date": "2026-08-13",
+            "last_updated": None,
+            "excerpts": ["First excerpt", "Second excerpt"],
+        }
+    ]
+
+    request_kwargs = mock_post.await_args.kwargs
+    assert request_kwargs["url"] == PARALLEL_SEARCH_URL
+    assert request_kwargs["headers"]["x-api-key"] == "parallel-search-key"
+    assert request_kwargs["json"] == {
+        "objective": "Parallel AI news",
+        "search_queries": ["Parallel AI news"],
+        "mode": "turbo",
+        "advanced_settings": {"max_results": 3},
+    }
+
+
+@pytest.mark.asyncio
+async def test_web_search_interception_executes_parallel_search(monkeypatch):
+    """An intercepted web-search call uses the configured Parallel Search tool."""
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    monkeypatch.setattr(proxy_server, "llm_router", _parallel_router(mode="fast"))
+    mock_post = _mock_async_post(
+        monkeypatch,
+        url=PARALLEL_SEARCH_URL,
+        response_body=_parallel_search_body(),
+    )
+    logger = WebSearchInterceptionLogger(
+        enabled_providers=[LlmProviders.OPENAI],
+        search_tool_name="parallel-search",
+    )
+
+    plan = await logger.async_build_responses_agentic_loop_plan(
+        tools={
+            "tool_calls": [
+                {
+                    "id": "fc_parallel",
+                    "call_id": "fc_parallel",
+                    "type": "function_call",
+                    "name": "litellm_web_search",
+                    "arguments": '{"query":"Parallel AI news"}',
+                    "input": {"query": "Parallel AI news"},
+                }
+            ]
+        },
+        model="gpt-5",
+        messages=[{"role": "user", "content": "Research Parallel"}],
+        response=None,
+        optional_params={"tools": [{"type": "function", "name": "litellm_web_search"}]},
+        logging_obj=None,
+        stream=False,
+        kwargs={"custom_llm_provider": "openai"},
+    )
+
+    assert plan.run_agentic_loop is True
+    assert plan.request_patch is not None
+    assert plan.request_patch.messages[-1] == {
+        "type": "function_call_output",
+        "call_id": "fc_parallel",
+        "output": (
+            "Title: Parallel result\nURL: https://example.com/parallel\nSnippet: First excerpt ... Second excerpt"
+        ),
+    }
+
+    request_kwargs = mock_post.await_args.kwargs
+    assert request_kwargs["url"] == PARALLEL_SEARCH_URL
+    assert request_kwargs["headers"]["x-api-key"] == "parallel-search-key"
+    assert request_kwargs["json"]["mode"] == "fast"
diff --git a/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py b/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py
index 7085e45cdc3..4b58d220623 100644
--- a/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py
+++ b/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py
@@ -1,4 +1,4 @@
-from unittest.mock import MagicMock, Mock
+from unittest.mock import AsyncMock, MagicMock, Mock, patch
 
 import httpx
 import pytest
@@ -9,6 +9,18 @@ from litellm.llms.s3_vectors.vector_stores.transformation import (
 from litellm.types.vector_stores import VectorStoreSearchResponse
 
 
+def _mock_router(model_names, sync=False):
+    """Router mock serving the given embedding model names."""
+    router = MagicMock()
+    router.get_model_list.return_value = [{"model_name": name} for name in model_names]
+    embedding_response = Mock(data=[{"embedding": [0.1, 0.2, 0.3]}])
+    if sync:
+        router.embedding = MagicMock(return_value=embedding_response)
+    else:
+        router.aembedding = AsyncMock(return_value=embedding_response)
+    return router
+
+
 class TestS3VectorsVectorStoreConfig:
     def test_init(self):
         """Test that S3VectorsVectorStoreConfig initializes correctly"""
@@ -28,19 +40,174 @@ class TestS3VectorsVectorStoreConfig:
         url = config.get_complete_url(None, litellm_params)
         assert url == "https://s3vectors.us-west-2.api.aws"
 
-    def test_get_complete_url_missing_region(self):
-        """Test that missing region raises error"""
+    def test_get_complete_url_missing_region(self, monkeypatch):
+        """Missing region falls back to the default region (parity with ingestion)"""
+        monkeypatch.delenv("AWS_REGION_NAME", raising=False)
+        monkeypatch.delenv("AWS_REGION", raising=False)
         config = S3VectorsVectorStoreConfig()
-        litellm_params = {}
-        with pytest.raises(ValueError, match="aws_region_name is required"):
-            config.get_complete_url(None, litellm_params)
+        url = config.get_complete_url(None, {})
+        assert url == "https://s3vectors.us-west-2.api.aws"
+
+    def test_get_complete_url_uses_env_region(self, monkeypatch):
+        """Missing region param resolves from AWS_REGION_NAME env var"""
+        monkeypatch.setenv("AWS_REGION_NAME", "eu-west-1")
+        monkeypatch.delenv("AWS_REGION", raising=False)
+        config = S3VectorsVectorStoreConfig()
+        url = config.get_complete_url(None, {})
+        assert url == "https://s3vectors.eu-west-1.api.aws"
+
+    def test_get_complete_url_invalid_region_format(self):
+        """Invalid region format raises"""
+        config = S3VectorsVectorStoreConfig()
+        with pytest.raises(ValueError, match="Invalid AWS region format"):
+            config.get_complete_url(None, {"aws_region_name": "Bad_Region!"})
 
-    @pytest.mark.skip(reason="Requires embedding API call, tested in integration tests")
     def test_transform_search_request(self):
-        """Test search request transformation"""
-        # This test requires making an actual embedding API call
-        # It's better tested in integration tests
-        pass
+        """Full request-body transformation with a router-injected embedding"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["text-embedding-3-small"], sync=True)
+
+        url, request_body = config.transform_search_vector_store_request(
+            vector_store_id="test-bucket:test-index",
+            query="test query",
+            vector_store_search_optional_params={"max_num_results": 7},
+            api_base="https://s3vectors.us-west-2.api.aws",
+            litellm_logging_obj=mock_logging_obj,
+            litellm_params={},
+            extra_body=None,
+            router=router,
+        )
+
+        assert url == "https://s3vectors.us-west-2.api.aws/QueryVectors"
+        assert request_body == {
+            "vectorBucketName": "test-bucket",
+            "indexName": "test-index",
+            "queryVector": {"float32": [0.1, 0.2, 0.3]},
+            "topK": 7,
+            "returnDistance": True,
+            "returnMetadata": True,
+        }
+        assert mock_logging_obj.model_call_details["query"] == "test query"
+
+    @pytest.mark.asyncio
+    async def test_atransform_search_uses_router_for_virtual_model(self):
+        """Regression: router-served embedding models must resolve via the router,
+        not a bare litellm.aembedding call (which has no deployment credentials)."""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["my-embedding-model"])
+
+        with patch("litellm.aembedding", new=AsyncMock()) as mock_bare_aembedding:  # test-quality-ok: guards that the bare-embedding path is not taken; dispatch seam is the behavior under test
+            url, request_body = await config.atransform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={"embedding_model": "my-embedding-model"},
+                extra_body=None,
+                router=router,
+            )
+
+        router.aembedding.assert_awaited_once_with(model="my-embedding-model", input=["test query"])
+        mock_bare_aembedding.assert_not_awaited()
+        assert request_body["queryVector"]["float32"] == [0.1, 0.2, 0.3]
+        assert request_body["topK"] == 5  # default
+
+    @pytest.mark.asyncio
+    async def test_atransform_search_falls_back_when_router_does_not_serve_model(self):
+        """Router present but embedding_model is not a router deployment ->
+        bare litellm.aembedding keeps working (provider-prefixed + env creds stores)."""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["some-other-model"])
+
+        mock_bare = AsyncMock(return_value=Mock(data=[{"embedding": [0.4, 0.5]}]))
+        with patch("litellm.aembedding", new=mock_bare):  # test-quality-ok: stubs the bare-embedding fallback whose request body the test asserts on
+            _, request_body = await config.atransform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={"embedding_model": "azure/text-embedding-3-small"},
+                extra_body=None,
+                router=router,
+            )
+
+        mock_bare.assert_awaited_once_with(model="azure/text-embedding-3-small", input=["test query"])
+        router.aembedding.assert_not_awaited()
+        assert request_body["queryVector"]["float32"] == [0.4, 0.5]
+
+    @pytest.mark.asyncio
+    async def test_atransform_search_without_router_uses_bare_embedding(self):
+        """Backward compat: no router -> bare litellm.aembedding as before"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+
+        mock_bare = AsyncMock(return_value=Mock(data=[{"embedding": [0.6, 0.7]}]))
+        with patch("litellm.aembedding", new=mock_bare):  # test-quality-ok: stubs the bare-embedding fallback whose request body the test asserts on
+            _, request_body = await config.atransform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={},
+                extra_body=None,
+            )
+
+        mock_bare.assert_awaited_once_with(model="text-embedding-3-small", input=["test query"])
+        assert request_body["queryVector"]["float32"] == [0.6, 0.7]
+
+    def test_transform_search_uses_router_for_virtual_model_sync(self):
+        """Sync twin: router-served embedding model resolves via router.embedding"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["my-embedding-model"], sync=True)
+
+        with patch("litellm.embedding", new=MagicMock()) as mock_bare_embedding:  # test-quality-ok: guards that the bare-embedding path is not taken; dispatch seam is the behavior under test
+            _, request_body = config.transform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={"embedding_model": "my-embedding-model"},
+                extra_body=None,
+                router=router,
+            )
+
+        router.embedding.assert_called_once_with(model="my-embedding-model", input=["test query"])
+        mock_bare_embedding.assert_not_called()
+        assert request_body["queryVector"]["float32"] == [0.1, 0.2, 0.3]
+
+    def test_transform_search_without_router_uses_bare_embedding_sync(self):
+        """Sync twin: no router -> bare litellm.embedding as before"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+
+        mock_bare = MagicMock(return_value=Mock(data=[{"embedding": [0.8, 0.9]}]))
+        with patch("litellm.embedding", new=mock_bare):  # test-quality-ok: stubs the bare-embedding fallback whose request body the test asserts on
+            _, request_body = config.transform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={},
+                extra_body=None,
+            )
+
+        mock_bare.assert_called_once_with(model="text-embedding-3-small", input=["test query"])
+        assert request_body["queryVector"]["float32"] == [0.8, 0.9]
 
     def test_transform_search_request_invalid_vector_store_id(self):
         """Test that invalid vector_store_id format raises error"""
diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py
index 8c1de12e7d9..4679b978f78 100644
--- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py
+++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py
@@ -1096,10 +1096,13 @@ def test_natively_signed_parallel_turn_never_carries_a_placeholder(model):
         "gemini-3.5-flash",
         "gemini-3.6-flash",
         "gemini-3.7-flash",
+        "gemini-3.8-flash",
         "vertex_ai/gemini-3.5-flash",
         "vertex_ai/gemini-3.7-flash",
+        "vertex_ai/gemini-3.8-flash",
         "gemini/gemini-3.5-flash",
         "gemini/gemini-3.7-flash",
+        "gemini/gemini-3.8-flash",
     ],
 )
 def test_placeholder_scoped_to_first_call_across_gemini_3_variants(model):
diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
index bd07bec900f..d2788408e09 100644
--- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
+++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
@@ -1185,6 +1185,18 @@ def test_vertex_ai_map_thinking_param_with_budget_tokens_0():
     }
 
 
+def test_vertex_ai_map_thinking_param_without_budget_tokens_for_gemini_3():
+    v = VertexGeminiConfig()
+    result = v.map_openai_params(
+        non_default_params={"thinking": {"type": "enabled"}},
+        optional_params={},
+        model="gemini-3.5-flash",
+        drop_params=False,
+    )
+
+    assert result["thinkingConfig"] == {"includeThoughts": True}
+
+
 def test_vertex_ai_map_tools():
     v = VertexGeminiConfig()
     optional_params = {}
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
index e36bef229f6..0480bbc40a7 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
@@ -1431,7 +1431,11 @@ class TestListToolsRestAPI:
     async def test_aggregate_list_absorbs_one_server_auth_failure(self, monkeypatch):
         """The multi-server aggregate listing degrades a server whose upstream
         rejects auth to an empty contribution and still returns the healthy
-        server's tools with a 200, rather than surfacing a 401."""
+        server's tools with a 200, rather than surfacing a 401. The absorbed
+        server must still show up as a classified per-server outcome so a REST
+        caller can tell "needs upstream auth" apart from "has no tools"."""
+        from pydantic import TypeAdapter
+
         from litellm.proxy._experimental.mcp_server.exceptions import (
             MCPUpstreamAuthError,
         )
@@ -1497,6 +1501,11 @@ class TestListToolsRestAPI:
 
         assert result["tools"] == ["good-tool"]
         assert result["error"] is None
+        wire_body = json.loads(TypeAdapter(dict).dump_json(result))
+        assert wire_body["server_outcomes"] == {
+            "good": {"status": "ok", "tool_count": 1},
+            "bad": {"status": "auth_required", "http_status": 401},
+        }
 
     async def test_name_resolution_finds_server_by_uuid(self, monkeypatch):
         """When server_id is a name string, it should be resolved to its UUID
diff --git a/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py b/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py
index 2ff38af80b1..43034f889f6 100644
--- a/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py
+++ b/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py
@@ -918,6 +918,62 @@ async def test_task_method_failure_hook_uses_enriched_request_data():
     assert failure_data.get("agent_id") == "test-agent"
 
 
+@pytest.mark.asyncio
+async def test_agentcore_invalid_context_id_returns_jsonrpc_invalid_params_400():
+    from litellm.proxy._types import UserAPIKeyAuth
+
+    agent = _make_agent_mock()
+    agent.litellm_params = {
+        "custom_llm_provider": "bedrock",
+        "model": "bedrock/agentcore/arn:aws:bedrock-agentcore:us-west-2:123456789012:runtime/demo",
+        "api_key": "test-jwt-token",
+    }
+    mock_request = _make_request_mock(
+        "message/send",
+        {
+            "message": {
+                "role": "user",
+                "parts": [{"kind": "text", "text": "Hello"}],
+                "messageId": "msg-1",
+                "contextId": "too-short",
+            }
+        },
+    )
+    user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1")
+
+    mock_proxy_logging = MagicMock()
+    mock_proxy_logging.pre_call_hook = AsyncMock(
+        side_effect=lambda user_api_key_dict, data, call_type: data
+    )
+    mock_proxy_logging.post_call_failure_hook = AsyncMock(return_value=None)
+
+    with ExitStack() as stack:
+        for p in _base_patches(agent):
+            stack.enter_context(p)
+        stack.enter_context(
+            patch(  # test-quality-ok: same proxy_logging_obj injection the sibling failure-hook test uses; no HTTP call is made because the request is rejected before signing
+                "litellm.proxy.proxy_server.proxy_logging_obj", mock_proxy_logging
+            )
+        )
+
+        from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a
+
+        response = await invoke_agent_a2a(
+            agent_id="test-agent",
+            request=mock_request,
+            fastapi_response=MagicMock(),
+            user_api_key_dict=user_api_key_dict,
+        )
+
+    body = json.loads(response.body.decode())
+    assert response.status_code == 400
+    assert body["id"] == "req-1"
+    assert body["error"]["code"] == -32602
+    assert "Invalid AgentCore runtime session id" in body["error"]["message"]
+    assert "Internal error" not in body["error"]["message"]
+    mock_proxy_logging.post_call_failure_hook.assert_awaited_once()
+
+
 @pytest.mark.asyncio
 async def test_get_extended_agent_card_rewrites_url():
     from litellm.proxy._types import UserAPIKeyAuth
diff --git a/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
new file mode 100644
index 00000000000..b7bc670c7f8
--- /dev/null
+++ b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
@@ -0,0 +1,288 @@
+"""
+Tests for restamping the public model on Anthropic Messages streaming chunks.
+"""
+
+import json
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from litellm.proxy.anthropic_endpoints.streaming_model_restamp import (
+    AnthropicStreamModelRestamper,
+    restamp_anthropic_stream_chunk_model,
+)
+from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
+
+
+def _message_start_frame(model: str, line_end: str = "\n") -> bytes:
+    payload = {
+        "type": "message_start",
+        "message": {"id": "msg_1", "type": "message", "role": "assistant", "model": model, "content": []},
+    }
+    return f"event: message_start{line_end}data: {json.dumps(payload)}{line_end}{line_end}".encode()
+
+
+def _proxy_logging_obj_streaming(frames: list[bytes]) -> MagicMock:
+    async def _iterator_hook(**_kwargs):
+        for frame in frames:
+            yield frame
+
+    proxy_logging_obj = MagicMock()
+    proxy_logging_obj.async_post_call_streaming_iterator_hook = _iterator_hook
+    proxy_logging_obj.async_post_call_streaming_hook = AsyncMock(side_effect=lambda **kwargs: kwargs["response"])
+    return proxy_logging_obj
+
+
+def _model_from_frame(frame: bytes | str) -> str:
+    text = frame.decode("utf-8") if isinstance(frame, bytes) else frame
+    data_line = next(line for line in text.split("\n") if line.startswith("data:"))
+    return json.loads(data_line[len("data:") :])["message"]["model"]
+
+
+def test_restamps_sse_bytes_frame():
+    restamped = restamp_anthropic_stream_chunk_model(
+        _message_start_frame("claude-haiku-4-5-20251001"), "claude-auto-1"
+    )
+
+    assert isinstance(restamped, bytes)
+    assert _model_from_frame(restamped) == "claude-auto-1"
+    assert b"event: message_start" in restamped
+
+
+def test_restamps_event_dict():
+    chunk = {"type": "message_start", "message": {"id": "msg_1", "model": "claude-sonnet-4-6"}}
+
+    restamped = restamp_anthropic_stream_chunk_model(chunk, "claude-auto-2")
+
+    assert restamped == {"type": "message_start", "message": {"id": "msg_1", "model": "claude-auto-2"}}
+    assert chunk["message"]["model"] == "claude-sonnet-4-6"
+
+
+@pytest.mark.parametrize(
+    "chunk",
+    [
+        b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n',
+        {"type": "content_block_delta", "delta": {"text": "hi"}},
+        {"type": "message_start", "message": "not-a-dict"},
+        b"event: message_start\ndata: not-json\n\n",
+        b"data: [DONE]\n\n",
+    ],
+)
+def test_leaves_chunks_without_a_model_untouched(chunk):
+    assert restamp_anthropic_stream_chunk_model(chunk, "claude-auto-1") == chunk
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_publishes_requested_model_on_message_start():
+    """The message_start event reports the requested model, not the provider's."""
+    delta_frame = b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n'
+    proxy_logging_obj = _proxy_logging_obj_streaming([_message_start_frame("claude-haiku-4-5-20251001"), delta_frame])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    assert _model_from_frame(chunks[0]) == "claude-auto-1"
+    assert chunks[1] == delta_frame
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_keeps_provider_model_when_restamping_is_off():
+    proxy_logging_obj = _proxy_logging_obj_streaming([_message_start_frame("claude-haiku-4-5-20251001")])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+        )
+    ]
+
+    assert _model_from_frame(chunks[0]) == "claude-haiku-4-5-20251001"
+
+
+def test_restamps_message_start_split_across_transport_chunks():
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    held = restamper.process(frame[:25])
+    emitted = restamper.process(frame[25:])
+
+    assert held == b""
+    assert isinstance(emitted, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+
+
+def test_emits_coalesced_frames_with_only_message_start_rewritten():
+    delta = b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n'
+    combined = _message_start_frame("claude-haiku-4-5-20251001") + delta
+
+    emitted = restamper_output = AnthropicStreamModelRestamper("claude-auto-1").process(combined)
+
+    assert isinstance(restamper_output, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+    assert emitted.endswith(delta)
+
+
+def test_ping_frames_keep_the_restamper_armed():
+    ping = b'event: ping\ndata: {"type": "ping"}\n\n'
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(ping) == ping
+    reassembled = restamper.process(frame[:10])
+    reassembled += restamper.process(frame[10:])
+
+    assert _model_from_frame(reassembled) == "claude-auto-1"
+
+
+def test_first_non_ping_event_disarms_the_restamper():
+    delta = b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n'
+    late_message_start = _message_start_frame("claude-haiku-4-5-20251001")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(delta) == delta
+    assert restamper.process(late_message_start) == late_message_start
+
+
+def test_oversized_unterminated_chunk_flushes_unmodified():
+    blob = b"data: " + b"x" * 70000
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(blob) == blob
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    assert restamper.process(frame) == frame
+
+
+def test_dict_message_start_disarms_after_restamp():
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+    first = restamper.process({"type": "message_start", "message": {"id": "msg_1", "model": "claude-sonnet-4-6"}})
+    second = {"type": "message_start", "message": {"id": "msg_2", "model": "claude-sonnet-4-6"}}
+
+    assert first == {"type": "message_start", "message": {"id": "msg_1", "model": "claude-auto-1"}}
+    assert restamper.process(second) == second
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_restamps_message_start_split_across_chunks():
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    proxy_logging_obj = _proxy_logging_obj_streaming([frame[:30], frame[30:]])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    joined = b"".join(chunk if isinstance(chunk, bytes) else chunk.encode("utf-8") for chunk in chunks)
+    assert _model_from_frame(joined) == "claude-auto-1"
+
+
+def test_restamps_crlf_terminated_message_start_frame():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r\n")
+    delta = b'event: content_block_delta\r\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\r\n\r\n'
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    emitted = restamper.process(frame)
+
+    assert isinstance(emitted, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+    assert emitted.endswith(b"\r\n\r\n")
+    assert restamper.process(delta) == delta
+
+
+def test_restamps_cr_terminated_message_start_frame():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    emitted = restamper.process(frame)
+
+    assert isinstance(emitted, bytes)
+    assert b'"model":"claude-auto-1"' in emitted
+    assert emitted.endswith(b"\r\r")
+
+
+def test_restamps_crlf_message_start_split_across_transport_chunks():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r\n")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    held = restamper.process(frame[:25])
+    emitted = restamper.process(frame[25:])
+
+    assert held == b""
+    assert isinstance(emitted, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+
+
+def test_flush_returns_restamped_held_tail():
+    unterminated = _message_start_frame("claude-haiku-4-5-20251001")[:-2]
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(unterminated) == b""
+    flushed = restamper.flush()
+
+    assert b'"model":"claude-auto-1"' in flushed
+    assert restamper.flush() == b""
+
+
+def test_flush_disarms_the_restamper():
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+
+    assert restamper.flush() == b""
+    assert restamper.process(frame) == frame
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_flushes_held_tail_at_end_of_stream():
+    unterminated = _message_start_frame("claude-haiku-4-5-20251001")[:-2]
+    proxy_logging_obj = _proxy_logging_obj_streaming([unterminated])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    joined = b"".join(chunk if isinstance(chunk, bytes) else chunk.encode("utf-8") for chunk in chunks)
+    assert b'"model":"claude-auto-1"' in joined
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_restamps_crlf_stream():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r\n")
+    delta = b'event: content_block_delta\r\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\r\n\r\n'
+    proxy_logging_obj = _proxy_logging_obj_streaming([frame, delta])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    assert _model_from_frame(chunks[0]) == "claude-auto-1"
+    assert chunks[1] == delta
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
index 8bc367b6b59..953e3de1519 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
@@ -5524,7 +5524,9 @@ async def test_streaming_end_of_stream_block_emits_error_frame_instead_of_trunca
     """Regression for PR #38722: a topicPolicy DENY caught by the end-of-stream
     scan used to raise after SSE headers were flushed, so the client saw a
     silently truncated stream. The unified hook must emit the chat in-stream
-    error frame instead."""
+    error frame instead. The finish chunk is withheld while the end-of-stream
+    scan runs, so on a block it is dropped rather than relayed before the
+    frame."""
     from litellm.llms import load_guardrail_translation_mappings
     from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail import (
         unified_guardrail as unified_module,
@@ -5582,8 +5584,9 @@ async def test_streaming_end_of_stream_block_emits_error_frame_instead_of_trunca
     finally:
         unified_module.endpoint_guardrail_translation_mappings = None
 
-    assert len(out) == 3
+    assert len(out) == 2
     assert isinstance(out[0], ModelResponseStream)
+    assert out[0].choices[0].finish_reason is None
     frame = out[-1]
     assert isinstance(frame, bytes)
     payload = json.loads(frame.decode()[len("data: ") :])
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py
index 1fbc975e40a..c04fb7b30ec 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py
@@ -2199,6 +2199,164 @@ async def test_history_is_still_compressed(guardrail: HeadroomGuardrail):
     assert has_headroom_retrieve_tool(result.get("tools") or [])
 
 
+# ---------------------------------------------------------------------------
+# #38558: a client that runs its own tool loop (e.g. Claude Code via the MCP
+# gateway) executes headroom_retrieve and echoes the recovered original content
+# back as a tool result. Compressing that row re-derives the same content hash
+# it was just retrieved from -- the marker returns and the agent loops. The
+# retrieved row must be held back from the compression service.
+# ---------------------------------------------------------------------------
+
+RETRIEVE_ECHO_MESSAGES = [
+    {"role": "system", "content": "You are Claude Code. " + "S" * 5000},
+    {"role": "user", "content": "H" * 5000},
+    {
+        "role": "assistant",
+        "content": "Expanding the marker.",
+        "tool_calls": [
+            {
+                "id": "hr_1",
+                "type": "function",
+                "function": {
+                    "name": "mcp__headroom__headroom_retrieve",
+                    "arguments": '{"hash": "b573993006976af767214fac"}',
+                },
+            }
+        ],
+    },
+    {"role": "tool", "tool_call_id": "hr_1", "content": "RETRIEVED BODY " + "R" * 5000},
+    {"role": "assistant", "content": "Older answer. " + "O" * 5000},
+    {"role": "user", "content": "now summarize the description"},
+]
+
+
+@pytest.mark.asyncio
+async def test_retrieved_content_is_never_recompressed(guardrail: HeadroomGuardrail):
+    """The tool result carrying headroom_retrieve output is held back, so it can
+    never collapse back to the hash it was just retrieved from."""
+    wire, result = await _wire_and_result(guardrail, RETRIEVE_ECHO_MESSAGES)
+
+    assert not any(row.get("tool_call_id") == "hr_1" for row in wire)
+    assert not any("RETRIEVED BODY" in json.dumps(row) for row in wire)
+    # Reaches the model byte-identical, so no marker stands in for the expansion.
+    assert result["structured_messages"][3] == RETRIEVE_ECHO_MESSAGES[3]
+    # Negative control: unrelated history is still compressed, not a no-op.
+    assert any(row.get("content") == "H" * 5000 for row in wire)
+
+
+@pytest.mark.asyncio
+async def test_retrieved_content_guard_matches_direct_tool_name(guardrail: HeadroomGuardrail):
+    """Server-side the tool is named headroom_retrieve (no MCP prefix); its
+    result must be protected the same way."""
+    messages = [
+        {"role": "system", "content": "sys " + "S" * 5000},
+        {"role": "user", "content": "H" * 5000},
+        {
+            "role": "assistant",
+            "content": "",
+            "tool_calls": [
+                {
+                    "id": "hr_direct",
+                    "type": "function",
+                    "function": {"name": HEADROOM_RETRIEVE_TOOL_NAME, "arguments": "{}"},
+                }
+            ],
+        },
+        {"role": "tool", "tool_call_id": "hr_direct", "content": "RETRIEVED BODY " + "R" * 5000},
+        {"role": "assistant", "content": "Older. " + "O" * 5000},
+        {"role": "user", "content": "summarize"},
+    ]
+    wire, result = await _wire_and_result(guardrail, messages)
+
+    assert not any(row.get("tool_call_id") == "hr_direct" for row in wire)
+    assert result["structured_messages"][3] == messages[3]
+
+
+@pytest.mark.asyncio
+async def test_retrieved_content_protected_when_mcp_tool_name_is_truncated(guardrail: HeadroomGuardrail):
+    """A long mcp__<server>__headroom_retrieve name is truncated past 64 chars in
+    the OpenAI-translated view the guardrail scans, dropping the suffix. The call
+    id read from the request's own Anthropic tool_use (never truncated) still
+    pairs the retrieved row so it is held back."""
+    from litellm.llms.anthropic.experimental_pass_through.adapters.transformation import (
+        truncate_tool_name,
+    )
+
+    long_name = "mcp__" + "s" * 45 + "__" + HEADROOM_RETRIEVE_TOOL_NAME
+    assert len(long_name) > 64
+    truncated = truncate_tool_name(long_name)
+    assert not truncated.endswith(HEADROOM_RETRIEVE_TOOL_NAME)
+
+    # What the guardrail scans: OpenAI-translated messages with the truncated name.
+    structured = [
+        {"role": "system", "content": "sys " + "S" * 5000},
+        {"role": "user", "content": "H" * 5000},
+        {
+            "role": "assistant",
+            "content": "",
+            "tool_calls": [{"id": "hr_long", "type": "function", "function": {"name": truncated, "arguments": "{}"}}],
+        },
+        {"role": "tool", "tool_call_id": "hr_long", "content": "RETRIEVED BODY " + "R" * 5000},
+        {"role": "assistant", "content": "Older. " + "O" * 5000},
+        {"role": "user", "content": "summarize"},
+    ]
+    # The request's own messages, untranslated: Anthropic tool_use carries the full name.
+    raw_messages = [
+        {"role": "assistant", "content": [{"type": "tool_use", "id": "hr_long", "name": long_name, "input": {}}]},
+        {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "hr_long", "content": "RETRIEVED BODY"}]},
+    ]
+
+    inputs = GenericGuardrailAPIInputs(texts=["x"], structured_messages=json.loads(json.dumps(structured)))
+    sent: dict = {}
+
+    def _echo(**kwargs):
+        sent["messages"] = kwargs["json"]["messages"]
+        return _make_compress_response(json.loads(json.dumps(kwargs["json"]["messages"])))
+
+    with patch.object(guardrail.async_handler, "post", new_callable=AsyncMock, side_effect=_echo):
+        result = await guardrail.apply_guardrail(
+            inputs=inputs,
+            request_data={"model": "claude-sonnet-4-5-20250929", "messages": raw_messages},
+            input_type="request",
+        )
+
+    assert not any(row.get("tool_call_id") == "hr_long" for row in sent["messages"])
+    assert result["structured_messages"][3] == structured[3]
+    assert any(row.get("content") == "H" * 5000 for row in sent["messages"])
+
+
+def test_raw_retrieve_call_ids_covers_both_shapes_and_ignores_others():
+    """Retrieve ids are read from OpenAI tool_calls and Anthropic tool_use blocks;
+    non-retrieve calls, non-tool_use blocks, string content, and non-list inputs
+    yield nothing."""
+    from litellm.proxy.guardrails.guardrail_hooks.headroom.headroom import _raw_retrieve_call_ids
+
+    messages = [
+        {
+            "role": "assistant",
+            "tool_calls": [
+                {"id": "oa1", "function": {"name": HEADROOM_RETRIEVE_TOOL_NAME}},
+                {"id": "other", "function": {"name": "get_weather"}},
+                {"id": "malformed", "function": {"name": 123}},
+                {"id": "nofunc"},
+            ],
+        },
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "tool_use", "id": "an1", "name": "mcp__hr__headroom_retrieve", "input": {}},
+                {"type": "tool_use", "id": "an2", "name": "jira_get_issue", "input": {}},
+                {"type": "text", "text": "noise"},
+            ],
+        },
+        {"role": "user", "content": "plain string content, not a list"},
+    ]
+
+    assert _raw_retrieve_call_ids(messages) == frozenset({"oa1", "an1"})
+    assert _raw_retrieve_call_ids("not a list") == frozenset()
+    assert _raw_retrieve_call_ids(None) == frozenset()
+
+
 @pytest.mark.asyncio
 async def test_nothing_compressible_returns_inputs_untouched(guardrail: HeadroomGuardrail):
     """A single-turn request is all protected, so there is nothing to send and
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py
new file mode 100644
index 00000000000..42bdf41bc88
--- /dev/null
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py
@@ -0,0 +1,327 @@
+"""
+Regression tests for blocking an OpenAI-format streaming response from the
+unified guardrail post-call streaming iterator hook.
+
+When a guardrail's ``apply_guardrail`` raises ``ModifyResponseException``
+while (or at the end of) a chat completions or Responses API stream is being
+relayed, the hook must emit a well-formed SSE termination sequence carrying
+the block message - NOT a bare ``data: {"error": ...}`` blob that surfaces as
+an HTTP 500 error frame and truncates the stream.
+"""
+
+import json
+from typing import Any, AsyncGenerator, Dict, Literal, Optional, Tuple, Union
+
+import pytest
+
+from litellm.integrations.custom_guardrail import (
+    CustomGuardrail,
+    ModifyResponseException,
+)
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import (
+    UnifiedLLMGuardrails,
+)
+from litellm.types.utils import (
+    Delta,
+    GenericGuardrailAPIInputs,
+    ModelResponseStream,
+    StreamingChoices,
+)
+
+BLOCK_MESSAGE = "This response was replaced by policy."
+
+JsonPayload = Dict[str, object]
+StreamChunk = Union[ModelResponseStream, JsonPayload, bytes]
+
+
+class _BlockingGuardrail(CustomGuardrail):
+    """Mock guardrail that always blocks response scans by raising ModifyResponseException."""
+
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict,
+        input_type: Literal["request", "response"],
+        logging_obj: Optional[Any] = None,
+    ) -> GenericGuardrailAPIInputs:
+        raise ModifyResponseException(
+            message=BLOCK_MESSAGE,
+            model="gpt-5.4-mini",
+            request_data=request_data,
+            guardrail_name=self.guardrail_name,
+        )
+
+
+class _PassingGuardrail(CustomGuardrail):
+    """Mock guardrail that always lets response scans through unchanged."""
+
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict,
+        input_type: Literal["request", "response"],
+        logging_obj: Optional[Any] = None,
+    ) -> GenericGuardrailAPIInputs:
+        return inputs
+
+
+def _chat_chunk(delta: Delta, finish_reason: Optional[str] = None) -> ModelResponseStream:
+    return ModelResponseStream(
+        id="chatcmpl-live",
+        created=1724900000,
+        model="gpt-5.4-mini",
+        choices=[StreamingChoices(index=0, delta=delta, finish_reason=finish_reason)],
+    )
+
+
+async def _chat_stream(end: bool) -> AsyncGenerator[ModelResponseStream, None]:
+    yield _chat_chunk(Delta(role="assistant", content="This "))
+    for text in ["is ", "the ", "original ", "answer."]:
+        yield _chat_chunk(Delta(content=text))
+    if end:
+        yield _chat_chunk(Delta(), finish_reason="stop")
+
+
+async def _responses_stream(end: bool) -> AsyncGenerator[JsonPayload, None]:
+    original_text = "This is the original answer."
+    response_envelope = {"id": "resp_live", "model": "gpt-5.4-mini", "status": "in_progress", "output": []}
+    yield {"type": "response.created", "response": response_envelope}
+    yield {"type": "response.in_progress", "response": response_envelope}
+    yield {
+        "type": "response.output_item.added",
+        "output_index": 0,
+        "item": {"id": "msg_orig", "type": "message", "role": "assistant", "content": []},
+    }
+    yield {
+        "type": "response.content_part.added",
+        "item_id": "msg_orig",
+        "output_index": 0,
+        "content_index": 0,
+        "part": {"type": "output_text", "text": "", "annotations": []},
+    }
+    for delta in ["This ", "is ", "the ", "original ", "answer."]:
+        yield {
+            "type": "response.output_text.delta",
+            "item_id": "msg_orig",
+            "output_index": 0,
+            "content_index": 0,
+            "delta": delta,
+        }
+    yield {
+        "type": "response.output_text.done",
+        "item_id": "msg_orig",
+        "output_index": 0,
+        "content_index": 0,
+        "text": original_text,
+    }
+    if end:
+        yield {
+            "type": "response.completed",
+            "response": {
+                "id": "resp_live",
+                "model": "gpt-5.4-mini",
+                "status": "completed",
+                "output": [
+                    {
+                        "id": "msg_orig",
+                        "type": "message",
+                        "role": "assistant",
+                        "status": "completed",
+                        "content": [{"type": "output_text", "text": original_text, "annotations": []}],
+                    }
+                ],
+                "usage": {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28},
+            },
+        }
+
+
+async def _run_hook(
+    route: str,
+    stream: AsyncGenerator[Union[ModelResponseStream, JsonPayload], None],
+    sampling_rate: int = 1,
+    end_of_stream_only: bool = False,
+    buffer_until_moderated: bool = False,
+    blocks: bool = True,
+) -> Tuple[StreamChunk, ...]:
+    guardrail = (
+        _BlockingGuardrail(guardrail_name="test-blocking-guardrail", event_hook="post_call")
+        if blocks
+        else _PassingGuardrail(guardrail_name="test-passing-guardrail", event_hook="post_call")
+    )
+    guardrail.streaming_sampling_rate = sampling_rate
+    guardrail.streaming_end_of_stream_only = end_of_stream_only
+    guardrail.streaming_buffer_until_moderated = buffer_until_moderated
+
+    unified_guardrail = UnifiedLLMGuardrails()
+    user_api_key_dict = UserAPIKeyAuth(api_key="test", request_route=route)
+    request_data = {
+        "messages": [{"role": "user", "content": "hi"}],
+        "guardrail_to_apply": guardrail,
+        "metadata": {"guardrails": [guardrail.guardrail_name]},
+    }
+
+    return tuple(
+        [
+            chunk
+            async for chunk in unified_guardrail.async_post_call_streaming_iterator_hook(
+                user_api_key_dict=user_api_key_dict,
+                response=stream,
+                request_data=request_data,
+            )
+        ]
+    )
+
+
+def _sse_payloads(collected: Tuple[StreamChunk, ...]) -> Tuple[JsonPayload, ...]:
+    return tuple(
+        json.loads(line[len("data:") :].strip())
+        for chunk in collected
+        if isinstance(chunk, bytes)
+        for block in chunk.decode().split("\n\n")
+        for line in block.strip().split("\n")
+        if line.startswith("data:")
+    )
+
+
+def _assert_no_error_frame(collected: Tuple[StreamChunk, ...]) -> None:
+    raw = "".join(chunk.decode() for chunk in collected if isinstance(chunk, bytes))
+    assert '"error"' not in raw, f"unexpected error blob in stream: {raw!r}"
+
+
+@pytest.mark.asyncio
+async def test_chat_pre_stream_block_emits_standalone_completion():
+    """Block on the first chunk: a standalone completion opens with a role delta
+    and ends with finish_reason content_filter."""
+    collected = await _run_hook("/v1/chat/completions", _chat_stream(end=False))
+    _assert_no_error_frame(collected)
+    payloads = _sse_payloads(collected)
+    assert payloads, "no block SSE chunks were emitted"
+    assert payloads[0]["choices"][0]["delta"] == {"role": "assistant", "content": BLOCK_MESSAGE}
+    assert payloads[-1]["choices"][0]["finish_reason"] == "content_filter"
+
+
+@pytest.mark.asyncio
+async def test_chat_mid_stream_block_continues_the_completion():
+    """Regression for the LIT-6496 500 error frame: after chunks were already
+    forwarded, the block continues the same completion id and terminates with
+    finish_reason content_filter instead of raising into an error blob."""
+    collected = await _run_hook("/v1/chat/completions", _chat_stream(end=False), sampling_rate=5)
+    _assert_no_error_frame(collected)
+    forwarded = [chunk for chunk in collected if isinstance(chunk, ModelResponseStream)]
+    assert forwarded, "original chunks should have streamed before the block"
+    payloads = _sse_payloads(collected)
+    assert payloads, "no block SSE chunks were emitted"
+    assert all(payload["id"] == "chatcmpl-live" for payload in payloads), (
+        "block chunks must continue the in-progress completion, not start a new one"
+    )
+    assert payloads[0]["choices"][0]["delta"] == {"content": BLOCK_MESSAGE}
+    assert payloads[-1]["choices"][0]["finish_reason"] == "content_filter"
+
+
+@pytest.mark.asyncio
+async def test_chat_end_of_stream_block_terminates_cleanly():
+    """Regression for bugbot's finish-ordering finding: in end_of_stream_only
+    mode the original finish chunk must be withheld until moderation decides,
+    so a block's content_filter finish is the only stream terminator a client
+    ever sees - never policy text trailing after finish_reason stop."""
+    collected = await _run_hook("/v1/chat/completions", _chat_stream(end=True), end_of_stream_only=True)
+    _assert_no_error_frame(collected)
+    forwarded = [chunk for chunk in collected if isinstance(chunk, ModelResponseStream)]
+    assert forwarded, "content chunks still stream to the client before end-of-stream moderation"
+    assert all(choice.finish_reason is None for chunk in forwarded for choice in chunk.choices), (
+        "the original finish chunk must be withheld until moderation decides"
+    )
+    payloads = _sse_payloads(collected)
+    assert BLOCK_MESSAGE in json.dumps(payloads)
+    assert payloads[-1]["choices"][0]["finish_reason"] == "content_filter"
+
+
+@pytest.mark.asyncio
+async def test_chat_end_of_stream_pass_releases_withheld_finish_chunk():
+    """When end-of-stream moderation passes, the withheld finish chunk is
+    released so a clean stream still terminates normally."""
+    collected = await _run_hook(
+        "/v1/chat/completions", _chat_stream(end=True), end_of_stream_only=True, blocks=False
+    )
+    assert not [chunk for chunk in collected if isinstance(chunk, bytes)], (
+        "a clean stream must carry no synthetic block frames"
+    )
+    forwarded = [chunk for chunk in collected if isinstance(chunk, ModelResponseStream)]
+    finish_reasons = [choice.finish_reason for chunk in forwarded for choice in chunk.choices]
+    assert finish_reasons[-1] == "stop", "the withheld finish chunk must be released after moderation passes"
+    assert all(reason is None for reason in finish_reasons[:-1])
+
+
+@pytest.mark.asyncio
+async def test_responses_buffered_block_emits_full_event_sequence():
+    """Buffered moderation blocks before anything streams: a complete synthetic
+    Responses stream from response.created through response.completed carrying
+    the block message, with the original content never released."""
+    collected = await _run_hook("/v1/responses", _responses_stream(end=True), buffer_until_moderated=True)
+    _assert_no_error_frame(collected)
+    assert not [chunk for chunk in collected if isinstance(chunk, dict)], (
+        "buffered original chunks must never be released after a block"
+    )
+    payloads = _sse_payloads(collected)
+    event_types = [payload["type"] for payload in payloads]
+    assert event_types[0] == "response.created"
+    assert "response.output_text.delta" in event_types
+    assert event_types[-1] == "response.completed"
+    completed = payloads[-1]["response"]
+    assert completed["status"] == "completed"
+    assert completed["output"][0]["content"][0]["text"] == BLOCK_MESSAGE
+    assert completed["usage"] == {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28}
+    assert "original answer" not in json.dumps(payloads)
+
+
+@pytest.mark.asyncio
+async def test_responses_mid_stream_block_continues_the_response():
+    """Regression for the LIT-6496 500 error frame and bugbot's unclosed-item
+    finding: after events were already forwarded, the block first closes the
+    output item still open on the wire, then appends the replacement item under
+    the same response id, and closes with response.completed - never a second
+    response.created and never a completed response with an item left open."""
+    collected = await _run_hook("/v1/responses", _responses_stream(end=False))
+    _assert_no_error_frame(collected)
+    forwarded = [chunk for chunk in collected if isinstance(chunk, dict)]
+    forwarded_types = [chunk["type"] for chunk in forwarded]
+    assert "response.created" in forwarded_types, "original events should have streamed before the block"
+    payloads = _sse_payloads(collected)
+    assert payloads, "no block SSE chunks were emitted"
+    block_types = [payload["type"] for payload in payloads]
+    assert "response.created" not in block_types, "a mid-stream block must not restart the response"
+    assert block_types[-1] == "response.completed"
+
+    all_events = forwarded + list(payloads)
+    opened = sorted(event["output_index"] for event in all_events if event["type"] == "response.output_item.added")
+    closed = sorted(event["output_index"] for event in all_events if event["type"] == "response.output_item.done")
+    assert opened == closed, "every output item opened on the stream must be closed before response.completed"
+    original_done_position = block_types.index("response.output_item.done")
+    block_item_position = block_types.index("response.output_item.added")
+    assert original_done_position < block_item_position, (
+        "the in-progress original item must be closed before the block item is appended"
+    )
+    assert payloads[original_done_position]["item"]["id"] == "msg_orig"
+    assert payloads[block_item_position]["output_index"] == 1, (
+        "the block item must continue after the original output item"
+    )
+    completed = payloads[-1]["response"]
+    assert completed["id"] == "resp_live"
+    assert completed["output"][0]["content"][0]["text"] == BLOCK_MESSAGE
+
+
+@pytest.mark.asyncio
+async def test_responses_end_of_stream_block_reports_original_usage():
+    collected = await _run_hook("/v1/responses", _responses_stream(end=True), end_of_stream_only=True)
+    _assert_no_error_frame(collected)
+    forwarded_types = [chunk["type"] for chunk in collected if isinstance(chunk, dict)]
+    assert "response.completed" not in forwarded_types, (
+        "the original terminal event must be withheld and replaced by the block sequence"
+    )
+    payloads = _sse_payloads(collected)
+    completed = payloads[-1]["response"]
+    assert payloads[-1]["type"] == "response.completed"
+    assert completed["id"] == "resp_live"
+    assert completed["output"][0]["content"][0]["text"] == BLOCK_MESSAGE
+    assert completed["usage"] == {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28}
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py
index 0b32558a00a..8cad1c634a9 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py
@@ -1844,7 +1844,8 @@ class TestStreamingHttpErrorFrames:
 
         out = await _drive_stream(UnifiedLLMGuardrails(), guardrail, chunks)
 
-        assert out[:2] == chunks
+        assert out[0] == chunks[0]
+        assert chunks[1] not in out
         frame = out[-1]
         assert isinstance(frame, bytes)
         text = frame.decode()
diff --git a/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py b/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py
index 957f9fde645..1697b77b99a 100644
--- a/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py
@@ -1,7 +1,8 @@
 import logging
 import time
-from collections.abc import Mapping
+from collections.abc import Callable, Mapping, Sequence
 from itertools import chain
+from types import MappingProxyType
 from typing import Final
 from unittest.mock import AsyncMock, MagicMock, call
 
@@ -38,6 +39,7 @@ from litellm.proxy.management_endpoints.scim.scim_v2 import (
     get_groups,
     get_users,
     get_service_provider_config,
+    merge_placeholder,
     patch_group,
     patch_team_membership,
     patch_user,
@@ -52,6 +54,7 @@ from litellm.types.proxy.management_endpoints.scim_v2 import (
     SCIMMember,
     SCIMPatchOp,
     SCIMPatchOperation,
+    SCIMPlaceholderMergeResult,
     SCIMServiceProviderConfig,
     SCIMUser,
     SCIMUserEmail,
@@ -778,13 +781,17 @@ async def test_handle_existing_user_by_email_without_teams_preserves_memberships
         "litellm.proxy.management_endpoints.scim.scim_v2.ScimTransformations.transform_litellm_user_to_scim_user",
         AsyncMock(return_value=None),
     )
-    mock_team_member_add = mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
-        "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add",
-        AsyncMock(),
+    mock_team_member_add = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add",
+            AsyncMock(),
+        )
     )
-    mock_team_member_delete = mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
-        "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete",
-        AsyncMock(),
+    mock_team_member_delete = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete",
+            AsyncMock(),
+        )
     )
 
     new_user_request = NewUserRequest(
@@ -1645,6 +1652,25 @@ async def test_update_group_e2e(mocker):
     ScimTransformations.transform_litellm_team_to_scim_group.assert_called_once_with(updated_team)
 
 
+def _rows_by_exact_id(
+    user_row: Callable[[Mapping[str, str]], LiteLLM_UserTable | MagicMock | None],
+) -> Callable[..., tuple[LiteLLM_UserTable | MagicMock, ...]]:
+    """``find_many`` stand-in for the classifier's cross-field read on a table where a
+    member value only ever matches as an exact ``user_id``."""
+
+    def rows(where: Mapping[str, object], take: int | None = None) -> tuple[LiteLLM_UserTable | MagicMock, ...]:
+        clauses: Final = where["OR"]
+        assert isinstance(clauses, list)
+        found: Final = tuple(user_row(clause) for clause in clauses if "user_id" in clause)
+        return tuple(row for row in found if row is not None)
+
+    return rows
+
+
+def _user_row_for(where: Mapping[str, str]) -> LiteLLM_UserTable:
+    return LiteLLM_UserTable(user_id=where["user_id"])
+
+
 @pytest.mark.asyncio
 async def test_create_group_with_nonexistent_users_rejects(mocker, monkeypatch):
     """
@@ -1696,9 +1722,8 @@ async def test_create_group_with_nonexistent_users_rejects(mocker, monkeypatch):
             return mock_user
         return None  # new-user-1 and new-user-2 don't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock dependencies
     mocker.patch(
@@ -1782,9 +1807,8 @@ async def test_update_group_with_nonexistent_users_rejects(mocker, monkeypatch):
             return mock_user
         return None  # new-user-3 and new-user-4 don't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock dependencies
     mocker.patch(
@@ -1853,9 +1877,8 @@ async def test_create_group_with_nonexistent_users_creates_when_flag_true(mocker
             return mock_user
         return None  # new-user-1 and new-user-2 don't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock user creation
     created_user_1 = NewUserResponse(user_id="new-user-1", key="test-key-1")
@@ -1943,9 +1966,8 @@ async def test_extract_group_member_ids_with_flag_true_creates_users(mocker, mon
             return mock_user
         return None  # new-user-1 doesn't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock user creation
     created_user = NewUserResponse(user_id="new-user-1", key="test-key-1")
@@ -2013,9 +2035,8 @@ async def test_extract_group_member_ids_with_flag_false_rejects(mocker, monkeypa
             return mock_user
         return None  # new-user-1 doesn't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock dependencies
     mocker.patch(
@@ -3121,8 +3142,7 @@ async def test_process_group_patch_operations_add_retains_existing_members(mocke
     mock_prisma_client.db = mocker.MagicMock()
     mock_prisma_client.db.litellm_usertable = mocker.MagicMock()
     # new-user already exists in the DB
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=mocker.MagicMock(user_id="new-user"))
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=(mocker.MagicMock(user_id="new-user"),))
 
     _, final_members, _ = await _process_group_patch_operations(
         patch_ops=patch_ops,
@@ -3415,8 +3435,7 @@ async def test_patch_group_add_applies_delta_and_keeps_concurrent_add(mocker):
     )
     mock_prisma_client.db.litellm_teamtable.update = AsyncMock(return_value=final_team)
     mock_prisma_client.db.litellm_usertable = mocker.MagicMock()
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=mocker.MagicMock())
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(_user_row_for))
 
     mocker.patch(
         "litellm.proxy.management_endpoints.scim.scim_v2._get_prisma_client_or_raise_exception",
@@ -3509,8 +3528,7 @@ async def test_patch_group_replace_stays_absolute_against_concurrent_roster(mock
     )
     mock_prisma_client.db.litellm_teamtable.update = AsyncMock(return_value=final_team)
     mock_prisma_client.db.litellm_usertable = mocker.MagicMock()
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=mocker.MagicMock())
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(_user_row_for))
 
     mocker.patch(
         "litellm.proxy.management_endpoints.scim.scim_v2._get_prisma_client_or_raise_exception",
@@ -3640,8 +3658,7 @@ async def test_process_group_patch_add_filtered_path_without_value(mocker):
     prisma_client = mocker.MagicMock()
     prisma_client.db = mocker.MagicMock()
     prisma_client.db.litellm_usertable = mocker.MagicMock()
-    prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=LiteLLM_UserTable(user_id="user-3"))
-    prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=(LiteLLM_UserTable(user_id="user-3"),))
 
     _, final_members, _ = await _process_group_patch_operations(
         patch_ops=patch_ops,
@@ -3733,12 +3750,14 @@ def _member_resolution_prisma(
         starts folding it, fails here instead of passing.
 
         A caller that must know which accounts match rather than merely how many
-        passes take=None, so an unbounded read returns every match.
+        passes take=None, so an unbounded read returns every match. The row keyed by
+        the value comes last, the order a bounded read is least prepared for, since
+        the database promises no order at all.
         """
         clauses: Final = where["OR"]
         assert isinstance(clauses, list)
         fields: Final = tuple(next(iter(clause)) for clause in clauses)
-        assert fields == ("sso_user_id", "user_email"), fields
+        assert fields in (("user_id", "sso_user_id", "user_email"), ("sso_user_id", "user_email")), fields
 
         def comparison(clause: Mapping[str, object]) -> tuple[str, bool]:
             """The needle and whether production asked for a case-insensitive compare,
@@ -3749,8 +3768,9 @@ def _member_resolution_prisma(
             assert isinstance(criterion, dict), criterion
             return criterion["equals"], criterion.get("mode") == "insensitive"
 
-        sso_needle, sso_insensitive = comparison(clauses[0])
-        email_needle, email_insensitive = comparison(clauses[1])
+        by_field: Final = dict(zip(fields, (comparison(clause) for clause in clauses)))
+        sso_needle, sso_insensitive = by_field["sso_user_id"]
+        email_needle, email_insensitive = by_field["user_email"]
 
         def same(stored: str, needle: str, insensitive: bool) -> bool:
             return stored.casefold() == needle.casefold() if insensitive else stored == needle
@@ -3768,6 +3788,11 @@ def _member_resolution_prisma(
                     if same(email, email_needle, email_insensitive)
                     for user_id in user_ids
                 ),
+                (
+                    user_id
+                    for user_id in users
+                    if "user_id" in by_field and same(user_id, by_field["user_id"][0], by_field["user_id"][1])
+                ),
             )
         )
         found: Final = tuple(dict.fromkeys(matched))
@@ -4452,9 +4477,11 @@ async def test_create_group_applies_default_team_params(
         "litellm.proxy.management_endpoints.scim.scim_v2._get_prisma_client_or_raise_exception",
         AsyncMock(return_value=_member_resolution_prisma(mocker, users=set(), teams=set())),
     )
-    new_team_mock = mocker.patch(  # test-quality-ok: endpoint collaborators are module-level, not injectable into create_group
-        "litellm.proxy.management_endpoints.scim.scim_v2.new_team",
-        AsyncMock(return_value=mocker.MagicMock()),
+    new_team_mock = (
+        mocker.patch(  # test-quality-ok: endpoint collaborators are module-level, not injectable into create_group
+            "litellm.proxy.management_endpoints.scim.scim_v2.new_team",
+            AsyncMock(return_value=mocker.MagicMock()),
+        )
     )
     mocker.patch(  # test-quality-ok: endpoint collaborators are module-level, not injectable into create_group
         "litellm.proxy.management_endpoints.scim.scim_v2.ScimTransformations.transform_litellm_team_to_scim_group",
@@ -4611,9 +4638,15 @@ async def test_resolve_group_member_ids_dedupes_repeated_member(mocker, scim_ups
 
 
 def _identity_lookup(value: str) -> object:
-    """The single cross-field lookup the classifier is expected to issue."""
+    """The single cross-field lookup the classifier is expected to issue per member."""
     return call(
-        where={"OR": [{"sso_user_id": value}, {"user_email": {"equals": value, "mode": "insensitive"}}]},
+        where={
+            "OR": [
+                {"user_id": value},
+                {"sso_user_id": value},
+                {"user_email": {"equals": value, "mode": "insensitive"}},
+            ]
+        },
         take=2,
     )
 
@@ -4903,9 +4936,7 @@ async def test_process_group_patch_remove_by_the_id_the_directory_added_with(
 
 
 @pytest.mark.asyncio
-async def test_process_group_patch_remove_still_drops_a_placeholder_by_its_literal_id(
-    mocker, scim_upsert_user_enabled
-):
+async def test_process_group_patch_remove_still_drops_a_placeholder_by_its_literal_id(mocker, scim_upsert_user_enabled):
     """An earlier release put unmatched ids on the roster verbatim, so a remove has to
     keep clearing the id as written even once it also resolves."""
     patch_ops = SCIMPatchOp(
@@ -4916,7 +4947,10 @@ async def test_process_group_patch_remove_still_drops_a_placeholder_by_its_liter
         team_id="parent-group",
         team_alias="Parent Group",
         members=[],
-        members_with_roles=[Member(user_id="legacy@example.com", role="user"), Member(user_id="keep-user", role="user")],
+        members_with_roles=[
+            Member(user_id="legacy@example.com", role="user"),
+            Member(user_id="keep-user", role="user"),
+        ],
     )
 
     _, final_members, _ = await _process_group_patch_operations(
@@ -5081,11 +5115,8 @@ async def test_process_group_patch_remove_refuses_when_two_members_share_the_id(
     assert "more than one member of this group" in str(exc_info.value.detail)
 
 
-
 @pytest.mark.asyncio
-async def test_resolve_group_member_ids_exact_user_id_wins_when_it_names_nobody_else(
-    mocker, scim_upsert_user_enabled
-):
+async def test_resolve_group_member_ids_exact_user_id_wins_when_it_names_nobody_else(mocker, scim_upsert_user_enabled):
     """The canonical user id stays authoritative, including when the same account also
     holds that value as its email, which is how a SCIM-provisioned account is keyed."""
     prisma_client = _member_resolution_prisma(
@@ -5147,10 +5178,79 @@ async def test_resolve_group_member_ids_refuses_a_user_id_that_names_another_acc
     assert exc_info.value.status_code == 400
     assert "member-id" in str(exc_info.value.detail)
     create_user_mock.assert_not_called()
-    assert any(
-        record.levelno >= logging.WARNING and "someone-else" in record.getMessage() for record in caplog.records
+    assert any(record.levelno >= logging.WARNING and "someone-else" in record.getMessage() for record in caplog.records)
+
+
+@pytest.mark.asyncio
+async def test_resolve_group_member_ids_reads_the_exact_id_when_two_other_accounts_fill_the_lookup(
+    mocker, scim_upsert_user_enabled
+):
+    """A value that is one account's id and two other accounts' identities fills the
+    bounded lookup with the other two. The account keyed by the value must still be
+    found, or the id would lose its precedence and a non-canonical type would skip
+    a member that names a real user."""
+    prisma_client = _member_resolution_prisma(
+        mocker,
+        users={"shared"},
+        teams=set(),
+        sso_user_id_to_user_id={"shared": "by-sso"},
+        email_to_user_id={"shared": "by-email"},
+    )
+    create_user_mock = mocker.patch(  # test-quality-ok: user creation is module-level, not injectable into the resolver
+        "litellm.proxy.management_endpoints.scim.scim_v2._create_user_if_not_exists",
+        AsyncMock(return_value=None),
     )
 
+    with pytest.raises(HTTPException) as exc_info:
+        await _resolve_group_member_ids(
+            members=[SCIMMember(value="shared", type="direct")],
+            created_via="scim_group_membership",
+            prisma_client=prisma_client,
+        )
+
+    assert exc_info.value.status_code == 400
+    assert "shared" in str(exc_info.value.detail)
+    create_user_mock.assert_not_called()
+    assert prisma_client.db.litellm_usertable.find_many.await_args_list == [_identity_lookup("shared")]
+    prisma_client.db.litellm_usertable.find_unique.assert_awaited_once_with(where={"user_id": "shared"})
+
+
+@pytest.mark.asyncio
+async def test_resolve_group_member_ids_reads_the_user_table_once_per_member(mocker, scim_upsert_user_enabled):
+    """Every member costs one read of the user table, however it resolves: by its exact
+    id (which still outranks a non-canonical type), by identity, as a SCIM team, or not
+    at all. Looking the exact id up on its own before the identity read doubled the
+    reads of a push, and the identity read is a scan."""
+    prisma_client = _member_resolution_prisma(
+        mocker,
+        users={"by-id"},
+        teams={"by-team"},
+        email_to_user_id={"by-email@example.com": "email-user"},
+    )
+    mocker.patch(  # test-quality-ok: user creation is module-level, not injectable into the resolver
+        "litellm.proxy.management_endpoints.scim.scim_v2._create_user_if_not_exists",
+        AsyncMock(return_value=NewUserResponse(user_id="nobody", key="key")),
+    )
+
+    result = await _resolve_group_member_ids(
+        members=[
+            SCIMMember(value="by-id", type="direct"),
+            SCIMMember(value="by-email@example.com"),
+            SCIMMember(value="by-team"),
+            SCIMMember(value="nobody"),
+        ],
+        created_via="scim_group_membership",
+        prisma_client=prisma_client,
+    )
+
+    assert result.all_member_ids == ["by-id", "email-user", "nobody"]
+    prisma_client.db.litellm_usertable.find_unique.assert_not_awaited()
+    assert prisma_client.db.litellm_usertable.find_many.await_args_list == [
+        _identity_lookup("by-id"),
+        _identity_lookup("by-email@example.com"),
+        _identity_lookup("by-team"),
+        _identity_lookup("nobody"),
+    ]
 
 
 @pytest.mark.asyncio
@@ -5536,10 +5636,7 @@ async def test_resolve_group_member_ids_admits_member_created_concurrently(mocke
     the member is still admitted: the id resolves to a real user row, so failing
     or dropping it would be wrong either way."""
     prisma_client = _member_resolution_prisma(mocker, users=set(), teams=set())
-    prisma_client.db.litellm_usertable.find_unique = AsyncMock(
-        side_effect=[None, LiteLLM_UserTable(user_id="raced-user")]
-    )
-    prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=LiteLLM_UserTable(user_id="raced-user"))
     mocker.patch(
         "litellm.proxy.management_endpoints.scim.scim_v2._create_user_if_not_exists",
         AsyncMock(return_value=None),
@@ -5619,3 +5716,196 @@ async def test_patch_group_404s_when_team_deleted_mid_request(mocker):
 
     assert exc_info.value.code == "404"
     assert f"Group not found with ID: {group_id}" in exc_info.value.message
+
+
+_SHADOW_MEMBER_VALUE: Final = "00u1shadow"
+_SHADOWED_ACCOUNT: Final = "real-1"
+_SHADOWED_GROUP: Final = "grp-eng"
+
+
+def _shadowed_tenant_rows() -> tuple[LiteLLM_UserTable, ...]:
+    """A placeholder keyed by the raw member value, and the real account that value names by SSO id."""
+    return (
+        LiteLLM_UserTable(user_id=_SHADOW_MEMBER_VALUE, user_email=_SHADOW_MEMBER_VALUE, teams=[_SHADOWED_GROUP]),
+        LiteLLM_UserTable(user_id=_SHADOWED_ACCOUNT, user_email="alice@example.com", sso_user_id=_SHADOW_MEMBER_VALUE),
+    )
+
+
+def _shadow_tenant_prisma(
+    mocker: MockerFixture,
+    *,
+    rows: Sequence[LiteLLM_UserTable],
+    keys_owned_by: Mapping[str, int] = MappingProxyType({}),
+) -> MagicMock:
+    """Prisma fake whose user rows are live: deleting one removes it from every later lookup."""
+    users: Final[dict[str, LiteLLM_UserTable]] = {row.user_id: row for row in rows}
+    team: Final = LiteLLM_TeamTable(
+        team_id=_SHADOWED_GROUP,
+        members=[_SHADOW_MEMBER_VALUE],
+        members_with_roles=[Member(user_id=_SHADOW_MEMBER_VALUE, role="user")],
+        metadata={SCIM_MANAGED_TEAM_METADATA_KEY: True},
+    )
+
+    async def find_unique(where: Mapping[str, str]) -> LiteLLM_UserTable | None:
+        return users.get(where["user_id"])
+
+    def clause_matches(row: LiteLLM_UserTable, clause: Mapping[str, object]) -> bool:
+        if "user_id" in clause:
+            return row.user_id == clause["user_id"]
+        if "sso_user_id" in clause:
+            return row.sso_user_id == clause["sso_user_id"]
+        email_filter: Final = clause["user_email"]
+        assert isinstance(email_filter, dict)
+        return (row.user_email or "").casefold() == str(email_filter["equals"]).casefold()
+
+    async def identity_rows(where: Mapping[str, object], take: int | None = None) -> tuple[LiteLLM_UserTable, ...]:
+        clauses: Final = where["OR"]
+        assert isinstance(clauses, list)
+        matched: Final = tuple(row for row in users.values() if any(clause_matches(row, clause) for clause in clauses))
+        return matched[:take] if take else matched
+
+    async def delete(where: Mapping[str, str]) -> LiteLLM_UserTable | None:
+        return users.pop(where["user_id"], None)
+
+    async def keys_for(where: Mapping[str, object]) -> tuple[MagicMock, ...]:
+        return tuple(mocker.MagicMock() for _ in range(keys_owned_by.get(str(where["user_id"]), 0)))
+
+    async def team_lookup(where: Mapping[str, str]) -> LiteLLM_TeamTable | None:
+        return team if where["team_id"] == team.team_id else None
+
+    prisma_client = mocker.MagicMock()
+    prisma_client.db = mocker.MagicMock()
+    prisma_client.db.litellm_usertable = mocker.MagicMock()
+    prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=find_unique)
+    prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=identity_rows)
+    prisma_client.db.litellm_usertable.delete = AsyncMock(side_effect=delete)
+    prisma_client.db.litellm_teamtable = mocker.MagicMock()
+    prisma_client.db.litellm_teamtable.find_unique = AsyncMock(side_effect=team_lookup)
+    prisma_client.db.litellm_teamtable.update = AsyncMock(return_value=team)
+    prisma_client.db.litellm_verificationtoken = mocker.MagicMock()
+    prisma_client.db.litellm_verificationtoken.find_many = AsyncMock(side_effect=keys_for)
+    prisma_client.db.litellm_invitationlink = mocker.MagicMock(delete_many=AsyncMock(return_value=0))
+    prisma_client.db.litellm_organizationmembership = mocker.MagicMock(delete_many=AsyncMock(return_value=0))
+    prisma_client.db.litellm_teammembership = mocker.MagicMock(delete_many=AsyncMock(return_value=0))
+    return prisma_client
+
+
+@pytest.fixture
+def shadowed_tenant(mocker, monkeypatch, scim_upsert_user_enabled) -> MagicMock:
+    from litellm.proxy import proxy_server
+
+    prisma_client: Final = _shadow_tenant_prisma(mocker, rows=_shadowed_tenant_rows())
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma_client)
+    return prisma_client
+
+
+async def _push_shadow_member(prisma_client: MagicMock):
+    return await _resolve_group_member_ids(
+        members=[SCIMMember(value=_SHADOW_MEMBER_VALUE)],
+        created_via="scim_group_membership",
+        prisma_client=prisma_client,
+    )
+
+
+@pytest.mark.asyncio
+async def test_merge_placeholder_hands_the_group_to_the_shadowed_account(mocker, shadowed_tenant):
+    """Every group push of the shadowing value is refused until the placeholder is folded into
+    the real account; after the merge the same push resolves to that account."""
+    team_member_add_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add", AsyncMock()
+        )
+    )
+    team_member_delete_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete", AsyncMock()
+        )
+    )
+
+    with pytest.raises(HTTPException) as before:
+        await _push_shadow_member(shadowed_tenant)
+    assert before.value.status_code == 400
+
+    result: Final = await merge_placeholder(user_id=_SHADOW_MEMBER_VALUE)
+
+    assert result == SCIMPlaceholderMergeResult(
+        placeholder_user_id=_SHADOW_MEMBER_VALUE,
+        merged_into_user_id=_SHADOWED_ACCOUNT,
+        team_ids=(_SHADOWED_GROUP,),
+    )
+    added: Final = team_member_add_mock.call_args.kwargs["data"]
+    assert (added.team_id, added.member.user_id) == (_SHADOWED_GROUP, _SHADOWED_ACCOUNT)
+    dropped: Final = team_member_delete_mock.call_args.kwargs["data"]
+    assert (dropped.team_id, dropped.user_id) == (_SHADOWED_GROUP, _SHADOW_MEMBER_VALUE)
+    shadowed_tenant.db.litellm_teammembership.delete_many.assert_awaited_once_with(
+        where={"user_id": _SHADOW_MEMBER_VALUE}
+    )
+    shadowed_tenant.db.litellm_usertable.delete.assert_awaited_once_with(where={"user_id": _SHADOW_MEMBER_VALUE})
+
+    after: Final = await _push_shadow_member(shadowed_tenant)
+    assert after.all_member_ids == [_SHADOWED_ACCOUNT]
+    assert after.created_users == []
+
+
+@pytest.mark.asyncio
+async def test_merge_placeholder_keeps_the_placeholder_when_the_roster_write_fails(mocker, shadowed_tenant):
+    """If the real account cannot join the team, the placeholder stays on it, or the membership is gone
+    from both accounts."""
+    mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+        "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add",
+        AsyncMock(side_effect=Exception("database connection lost")),
+    )
+    team_member_delete_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete", AsyncMock()
+        )
+    )
+
+    with pytest.raises(ProxyException):
+        await merge_placeholder(user_id=_SHADOW_MEMBER_VALUE)
+
+    team_member_delete_mock.assert_not_awaited()
+    shadowed_tenant.db.litellm_usertable.delete.assert_not_awaited()
+    assert await shadowed_tenant.db.litellm_usertable.find_unique(where={"user_id": _SHADOW_MEMBER_VALUE}) is not None
+
+
+@pytest.mark.parametrize(
+    ("rows", "keys_owned_by", "merged", "reason"),
+    [
+        pytest.param(_shadowed_tenant_rows(), {}, _SHADOWED_ACCOUNT, "SSO identity of its own", id="real-account"),
+        pytest.param(
+            _shadowed_tenant_rows(), {_SHADOW_MEMBER_VALUE: 2}, _SHADOW_MEMBER_VALUE, "2 virtual keys", id="owns-keys"
+        ),
+        pytest.param(_shadowed_tenant_rows()[:1], {}, _SHADOW_MEMBER_VALUE, "shadows no account", id="names-nobody"),
+        pytest.param(
+            (*_shadowed_tenant_rows(), LiteLLM_UserTable(user_id="real-2", user_email=_SHADOW_MEMBER_VALUE.upper())),
+            {},
+            _SHADOW_MEMBER_VALUE,
+            "names 2 accounts (real-1, real-2)",
+            id="names-two-accounts",
+        ),
+    ],
+)
+@pytest.mark.asyncio
+async def test_merge_placeholder_refuses_rows_that_are_not_a_lone_placeholder(
+    mocker, monkeypatch, scim_upsert_user_enabled, rows, keys_owned_by, merged, reason
+):
+    """Only a row with no SSO identity and no keys whose id names exactly one other account is folded;
+    anything else could move memberships to the wrong person, so nothing is written."""
+    from litellm.proxy import proxy_server
+
+    prisma_client: Final = _shadow_tenant_prisma(mocker, rows=rows, keys_owned_by=keys_owned_by)
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma_client)
+    team_member_add_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add", AsyncMock()
+        )
+    )
+
+    with pytest.raises(ProxyException) as exc_info:
+        await merge_placeholder(user_id=merged)
+
+    assert int(exc_info.value.code) == 409
+    assert reason in str(exc_info.value.message)
+    team_member_add_mock.assert_not_awaited()
+    prisma_client.db.litellm_usertable.delete.assert_not_awaited()
diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py
index a81c6b4c656..7e2e680743f 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py
@@ -17489,3 +17489,49 @@ async def test_check_project_key_limits_still_rejects_real_model_outside_project
 
     assert exc_info.value.status_code == 400
     assert "Model 'gpt-5.4-mini' not in project's allowed models" in exc_info.value.detail["error"]
+
+
+def test_generate_key_request_blank_team_id_is_personal():
+    """The UI Team-field clear submits team_id=""; it must count as no team (LIT-3925)."""
+    from litellm.proxy._types import RegenerateKeyRequest
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        _is_team_key,
+    )
+
+    cleared = GenerateKeyRequest(team_id="")
+    assert cleared.team_id is None
+    assert _is_team_key(data=cleared) is False
+    assert RegenerateKeyRequest(team_id="").team_id is None
+    assert GenerateKeyRequest(team_id="team-1").team_id == "team-1"
+
+
+def test_key_generation_check_blank_team_id_uses_personal_permissions(monkeypatch):
+    """key_generation_check with team_id="" must take the personal-key path instead
+    of failing the team lookup with "Unable to find team object" (LIT-3925)."""
+    from litellm.proxy._types import KeyManagementRoutes
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        key_generation_check,
+    )
+
+    monkeypatch.setattr(
+        litellm,
+        "key_generation_settings",
+        {
+            "team_key_generation": {"allowed_team_member_roles": ["admin"]},
+            "personal_key_generation": {"allowed_user_roles": ["proxy_admin", "internal_user"]},
+        },
+    )
+
+    assert (
+        key_generation_check(
+            team_table=None,
+            user_api_key_dict=UserAPIKeyAuth(
+                user_role=LitellmUserRoles.INTERNAL_USER,
+                api_key="sk-alice",
+                user_id="alice",
+            ),
+            data=GenerateKeyRequest(key_alias="personal", team_id=""),
+            route=KeyManagementRoutes.KEY_GENERATE,
+        )
+        is True
+    )
diff --git a/tests/test_litellm/proxy/management_helpers/test_access_group_key_sync.py b/tests/test_litellm/proxy/management_helpers/test_access_group_key_sync.py
new file mode 100644
index 00000000000..60c36e33e09
--- /dev/null
+++ b/tests/test_litellm/proxy/management_helpers/test_access_group_key_sync.py
@@ -0,0 +1,57 @@
+from types import SimpleNamespace
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from litellm.proxy.db.prisma_client import PrismaWrapper
+from litellm.proxy.db.routing_prisma_wrapper import RoutingPrismaWrapper
+from litellm.proxy.management_helpers.access_group_key_sync import (
+    sync_key_access_group_membership,
+    sync_key_regeneration_access_group_membership,
+)
+
+
+def _routed_prisma_client():
+    writer_inner = MagicMock(name="writer_prisma")
+    reader_inner = MagicMock(name="reader_prisma")
+    writer_inner.query_raw = AsyncMock(return_value=[])
+    reader_inner.query_raw = AsyncMock(return_value=[])
+    writer = PrismaWrapper(original_prisma=writer_inner, iam_token_db_auth=False)
+    reader = PrismaWrapper(original_prisma=reader_inner, iam_token_db_auth=False)
+    routing = RoutingPrismaWrapper(writer=writer, reader=reader)
+    return SimpleNamespace(db=routing), writer_inner, reader_inner
+
+
+@pytest.mark.asyncio
+async def test_regeneration_repoint_update_runs_on_the_writer():
+    prisma_client, writer_inner, reader_inner = _routed_prisma_client()
+
+    await sync_key_regeneration_access_group_membership(
+        prisma_client=prisma_client,
+        previous_key_token="old-token",
+        new_key_token="new-token",
+        data=None,
+        existing_key_row=MagicMock(),
+    )
+
+    writer_inner.query_raw.assert_awaited_once()
+    assert writer_inner.query_raw.await_args.args[0].startswith('UPDATE "LiteLLM_AccessGroupTable"')
+    reader_inner.query_raw.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_membership_attach_and_detach_updates_run_on_the_writer():
+    prisma_client, writer_inner, reader_inner = _routed_prisma_client()
+
+    await sync_key_access_group_membership(
+        prisma_client=prisma_client,
+        key_token="token",
+        previous_access_group_ids=["ag-old"],
+        updated_access_group_ids=["ag-new"],
+    )
+
+    assert writer_inner.query_raw.await_count == 2
+    assert all(
+        call.args[0].startswith('UPDATE "LiteLLM_AccessGroupTable"') for call in writer_inner.query_raw.await_args_list
+    )
+    reader_inner.query_raw.assert_not_awaited()
diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py
index f5ae0fe5977..d3f17c73499 100644
--- a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py
+++ b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py
@@ -2,6 +2,7 @@ import asyncio
 import json
 import logging
 import os
+from collections.abc import Callable
 from contextlib import ExitStack, contextmanager
 from io import BytesIO
 from types import SimpleNamespace
@@ -29,6 +30,7 @@ from litellm.proxy.pass_through_endpoints.pass_through_endpoints import (
     websocket_passthrough_request,
 )
 from litellm.integrations.custom_logger import CustomLogger
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.proxy._types import ProxyException, UserAPIKeyAuth
 from litellm.types.passthrough_endpoints.pass_through_endpoints import (
     LITELLM_PASS_THROUGH_RAW_BODY_STATE_KEY,
@@ -5464,7 +5466,10 @@ def test_the_marker_check_distinguishes_the_two_route_kinds():
     assert request_dispatched_to_pass_through_endpoint(builtin) is False
 
 
-async def _drive_passthrough_request_and_capture_logging(user_api_key_dict: UserAPIKeyAuth) -> tuple[int, object]:
+async def _drive_passthrough_request_and_capture_logging(
+    user_api_key_dict: UserAPIKeyAuth,
+    on_pre_call: Callable[[LiteLLMLoggingObj | None], None] | None = None,
+) -> tuple[int, LiteLLMLoggingObj | None]:
     import litellm
     from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
     from litellm.types.llms.custom_http import httpxSpecialProvider
@@ -5487,10 +5492,12 @@ async def _drive_passthrough_request_and_capture_logging(user_api_key_dict: User
     mock_request.query_params = QueryParams({})
     mock_request.body = AsyncMock(return_value=b'{"model": "gemini-2.0-flash"}')
 
-    captured_data: dict = {}
+    captured_data: dict = {}  # mutable-ok: the pre-call hook records the request data into it
 
     async def capture_pre_call_hook(user_api_key_dict, data, call_type):
         captured_data.update(data)
+        if on_pre_call is not None:
+            on_pre_call(data.get("litellm_logging_obj"))
         return data
 
     mock_proxy_logging = MagicMock()
@@ -5623,3 +5630,103 @@ async def test_resolve_team_callback_wiring_fails_open_on_operational_error():
     assert wiring.success_callbacks is None
     assert wiring.failure_callbacks is None
     assert wiring.logging_kwargs is None
+
+
+@pytest.mark.asyncio
+async def test_pass_through_request_leaves_guardrail_readable_metadata():
+    """A pre-call guardrail reads the request headers off the passthrough logging
+    params without raising."""
+    from litellm.proxy.guardrails.guardrail_hooks.hiddenlayer.hiddenlayer import (
+        _logged_request_headers,
+    )
+
+    user_api_key_dict = UserAPIKeyAuth(
+        api_key="test-key",
+        team_id="test-team",
+        team_metadata={
+            "logging": [
+                {
+                    "callback_name": "langfuse",
+                    "callback_type": "success_and_failure",
+                    "callback_vars": {
+                        "langfuse_public_key": "pk_test",
+                        "langfuse_secret_key": "sk_test",
+                    },
+                }
+            ]
+        },
+    )
+
+    observed: dict[str, dict[str, str] | BaseException] = {}  # mutable-ok: the pre-call hook records into it
+
+    def read_headers_the_way_a_guardrail_does(logging_obj: LiteLLMLoggingObj | None) -> None:
+        assert logging_obj is not None
+        try:
+            observed["headers"] = _logged_request_headers(logging_obj)
+        except Exception as exc:  # noqa: BLE001 - the regression is that this used to raise
+            observed["headers"] = exc
+
+    status_code, logging_obj = await _drive_passthrough_request_and_capture_logging(
+        user_api_key_dict, on_pre_call=read_headers_the_way_a_guardrail_does
+    )
+
+    assert "headers" in observed, "the pre-call hook never ran, so nothing was observed"
+    assert observed["headers"] == {}, f"guardrail header read failed: {observed['headers']!r}"
+    assert status_code == 200
+    assert logging_obj is not None
+    assert logging_obj.dynamic_success_callbacks, "team success callbacks must stay wired"
+    assert logging_obj.standard_callback_dynamic_params.get("langfuse_public_key") == "pk_test"
+
+
+@pytest.mark.asyncio
+async def test_pass_through_request_leaves_cost_router_logger_working():
+    """The cost router's logger reads the deployment id off the passthrough logging
+    params without raising. least_busy shares the read but swallows the exception,
+    so this is the strategy where the break is observable."""
+    from litellm._logging import verbose_logger
+    from litellm.caching.caching import DualCache
+    from litellm.router_strategy.lowest_cost import LowestCostLoggingHandler
+
+    handler = LowestCostLoggingHandler(router_cache=DualCache())
+
+    user_api_key_dict = UserAPIKeyAuth(
+        api_key="test-key",
+        team_id="test-team",
+        team_metadata={
+            "logging": [
+                {
+                    "callback_name": "langfuse",
+                    "callback_type": "success_and_failure",
+                    "callback_vars": {
+                        "langfuse_public_key": "pk_test",
+                        "langfuse_secret_key": "sk_test",
+                    },
+                }
+            ]
+        },
+    )
+
+    status_code, logging_obj = await _drive_passthrough_request_and_capture_logging(user_api_key_dict)
+    assert status_code == 200
+    assert logging_obj is not None
+
+    raised: list[logging.LogRecord] = []  # mutable-ok: logging.Handler records into it
+
+    class _RecordTracebacks(logging.Handler):
+        def emit(self, record: logging.LogRecord) -> None:
+            if record.exc_info is not None:
+                raised.append(record)
+
+    recorder = _RecordTracebacks()
+    verbose_logger.addHandler(recorder)
+    try:
+        await handler.async_log_success_event(
+            kwargs=logging_obj.model_call_details,
+            response_obj=None,
+            start_time=None,
+            end_time=None,
+        )
+    finally:
+        verbose_logger.removeHandler(recorder)
+
+    assert not raised, f"cost router logger raised on the passthrough logging params: {raised[0].exc_info}"
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_config.py b/tests/test_litellm/proxy/proxy_server/test_routes_config.py
index ad3c470acf3..dcb63b8ca82 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_config.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_config.py
@@ -60,6 +60,141 @@ def test_config_update_happy_admin(client, auth_as, mock_prisma, monkeypatch):
     assert normalize(response.json()) == {"message": "Config updated successfully"}
 
 
+def test_config_update_persists_optional_pre_call_checks(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+    fake_proxy_config = MagicMock()
+    fake_proxy_config.add_deployment = AsyncMock()
+    monkeypatch.setattr(ps, "proxy_config", fake_proxy_config)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"optional_pre_call_checks": ["prompt_caching"]}},
+        )
+
+    assert response.status_code == 200
+    persisted = json.loads(table.upsert.call_args.kwargs["data"]["create"]["param_value"])
+    assert persisted["optional_pre_call_checks"] == ["prompt_caching"]
+
+
+def test_config_update_persists_model_group_affinity_config(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+    fake_proxy_config = MagicMock()
+    fake_proxy_config.add_deployment = AsyncMock()
+    monkeypatch.setattr(ps, "proxy_config", fake_proxy_config)
+
+    model_group_affinity_config = {"gpt-4": ["session_affinity"]}
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"model_group_affinity_config": model_group_affinity_config}},
+        )
+
+    assert response.status_code == 200
+    persisted = json.loads(table.upsert.call_args.kwargs["data"]["create"]["param_value"])
+    assert persisted["model_group_affinity_config"] == model_group_affinity_config
+
+
+def test_config_update_persists_disable_cooldowns(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+    fake_proxy_config = MagicMock()
+    fake_proxy_config.add_deployment = AsyncMock()
+    monkeypatch.setattr(ps, "proxy_config", fake_proxy_config)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"disable_cooldowns": True}},
+        )
+
+    assert response.status_code == 200
+    persisted = json.loads(table.upsert.call_args.kwargs["data"]["create"]["param_value"])
+    assert persisted["disable_cooldowns"] is True
+
+
+def test_config_update_rejects_assistants_config(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"assistants_config": {"enabled": True}}},
+        )
+
+    assert response.status_code == 400
+    assert "assistants_config" in response.json()["error"]["message"]
+    table.upsert.assert_not_called()
+
+
+def test_config_update_rejects_router_general_settings(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"router_general_settings": {"async_only_mode": True}}},
+        )
+
+    assert response.status_code == 400
+    assert "router_general_settings" in response.json()["error"]["message"]
+    table.upsert.assert_not_called()
+
+
+def test_config_update_rejects_unknown_router_setting(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"optional_precall_checks": ["prompt_caching"]}},
+        )
+
+    assert response.status_code == 400
+    assert "optional_precall_checks" in response.json()["error"]["message"]
+    table.upsert.assert_not_called()
+
+
+def test_config_update_unknown_router_setting_non_admin_forbidden(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.INTERNAL_USER):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"optional_precall_checks": ["prompt_caching"]}},
+        )
+
+    assert response.status_code == 403
+    assert "admin" in response.json()["error"]["message"].lower()
+
+
 def test_config_update_non_admin_forbidden(client, auth_as, mock_prisma, monkeypatch):
     """POST /config/update by a non-admin caller is rejected; the error
     surfaces as a ProxyException with the admin-only message."""
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_models.py b/tests/test_litellm/proxy/proxy_server/test_routes_models.py
index 2b126b1ea95..bc6106a06f8 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_models.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_models.py
@@ -45,6 +45,7 @@ def patched_models(monkeypatch):
     deployment = MagicMock()
     deployment.litellm_params.model = "gpt-4"
     router.get_deployment_by_model_group_name = MagicMock(return_value=deployment)
+    router.get_configured_display_name = MagicMock(return_value=None)
 
     monkeypatch.setattr(proxy_server, "llm_router", router)
     monkeypatch.setattr(proxy_server, "prisma_client", MagicMock())
@@ -187,6 +188,83 @@ def test_anthropic_format_carries_router_configured_token_limits(client, auth_as
     assert (claude["max_input_tokens"], claude["max_tokens"]) == (500000, 4096)
 
 
+@pytest.mark.parametrize("path", ["/v1/models", "/models"])
+def test_anthropic_format_uses_configured_display_name(client, auth_as, patched_models, path):
+    """A deployment's ``model_info.display_name`` becomes the Anthropic-native
+    ``display_name`` so Claude Code's picker shows a clean name while the id keeps
+    routing; models without one keep the id fallback, and the OpenAI-shaped
+    listing carries no display_name either way."""
+
+    def _configured(model_name):
+        return "Kimi K3" if model_name == "gpt-4" else None
+
+    patched_models.get_configured_display_name = MagicMock(side_effect=_configured)
+
+    with auth_as():
+        anthropic_response = client.get(path, headers={"anthropic-version": "2023-06-01"})
+        openai_response = client.get(path)
+
+    assert anthropic_response.status_code == 200
+    gpt_4, claude = anthropic_response.json()["data"]
+    assert (gpt_4["id"], gpt_4["display_name"]) == ("gpt-4", "Kimi K3")
+    assert (claude["id"], claude["display_name"]) == ("claude-sonnet", "claude-sonnet")
+
+    assert openai_response.status_code == 200
+    openai_models = openai_response.json()["data"]
+    assert [m["id"] for m in openai_models] == ["gpt-4", "claude-sonnet"]
+    assert all("display_name" not in m for m in openai_models)
+
+
+@pytest.mark.parametrize("params", [{}, {"scope": "expand"}])
+def test_anthropic_display_name_resolved_via_internal_team_key(
+    client, auth_as, patched_models, monkeypatch, params
+):
+    """For a team-scoped row the configured display name must be looked up by the
+    internal routing key while the entry itself is keyed by the public name, so
+    the clean name lands on the id the client actually sees."""
+    from litellm.proxy import utils as proxy_utils
+    from litellm.proxy.auth import model_checks
+
+    internal_name = "model_name_team-1_c0ffee"
+
+    patched_models.get_model_list = MagicMock(
+        return_value=[
+            {
+                "model_name": internal_name,
+                "model_info": {
+                    "team_id": "team-1",
+                    "team_public_model_name": "gpt-4-team",
+                },
+            }
+        ]
+    )
+    patched_models.get_model_names = MagicMock(return_value=[internal_name])
+    patched_models.get_configured_display_name = MagicMock(
+        side_effect=lambda model_name: "Team GPT" if model_name == internal_name else None
+    )
+
+    async def _fake_get_available_models_for_user(**kwargs):
+        return [internal_name]
+
+    monkeypatch.setattr(
+        proxy_utils,
+        "get_available_models_for_user",
+        _fake_get_available_models_for_user,
+    )
+    monkeypatch.setattr(
+        model_checks, "get_complete_model_list", lambda **kwargs: [internal_name]
+    )
+
+    with auth_as():
+        response = client.get(
+            "/v1/models", params=params, headers={"anthropic-version": "2023-06-01"}
+        )
+
+    assert response.status_code == 200
+    (entry,) = response.json()["data"]
+    assert (entry["id"], entry["display_name"]) == ("gpt-4-team", "Team GPT")
+
+
 @pytest.mark.parametrize("path", ["/v1/models", "/models"])
 def test_get_models_invalid_scope_returns_400(client, auth_as, patched_models, path):
     """Pins: ``GET /v1/models``, ``GET /models`` (error path: invalid scope)."""
diff --git a/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py b/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py
index aa35fd64f18..0fb9b1a6d88 100644
--- a/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py
+++ b/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py
@@ -19,7 +19,10 @@ from litellm.proxy._types import (
     LitellmUserRoles,
     UserAPIKeyAuth,
 )
-from litellm.proxy.common_utils.model_listing_utils import TeamModelNameTranslator
+from litellm.proxy.common_utils.model_listing_utils import (
+    TeamModelNameTranslator,
+    configured_display_names,
+)
 from litellm.proxy.proxy_server import (
     _get_proxy_model_info,
     _translate_model_name_for_response,
@@ -1391,6 +1394,27 @@ def test_resolve_public_name_respects_legacy_flag():
     )
 
 
+def test_configured_display_names_keyed_by_response_id():
+    """The map is keyed by the public response id while the router lookup uses
+    the internal routing key, and entries without a configured name are omitted."""
+    router = MagicMock()
+    router.get_configured_display_name = MagicMock(
+        side_effect=lambda model_name: "Team Sonnet" if model_name == "model_name_team-abc-123_4a6b8" else None
+    )
+
+    assert configured_display_names(
+        entries=[
+            ("team-claude-sonnet", "model_name_team-abc-123_4a6b8"),
+            ("gpt-4o", "gpt-4o"),
+        ],
+        llm_router=router,
+    ) == {"team-claude-sonnet": "Team Sonnet"}
+
+
+def test_configured_display_names_empty_without_router():
+    assert configured_display_names(entries=[("gpt-4o", "gpt-4o")], llm_router=None) == {}
+
+
 @pytest.mark.asyncio
 async def test_retrieve_model_by_public_name_returns_200(monkeypatch):
     """Regression: `GET /v1/models/{public_name}` must NOT 404. The listing
diff --git a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py
index 31430da71e8..8006f64ba41 100644
--- a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py
+++ b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py
@@ -1,3 +1,4 @@
+import re
 from datetime import datetime, timezone
 from unittest.mock import AsyncMock, MagicMock, patch
 
@@ -756,6 +757,45 @@ def test_public_agent_hub_returns_empty_when_no_public_groups():
     assert response.json() == []
 
 
+# ---------------------------------------------------------------------------
+# /public/agents/fields
+# ---------------------------------------------------------------------------
+
+
+def test_bedrock_agentcore_runtime_arn_validation_pattern_accepts_full_resource_path():
+    """Regression for LIT-6737: the AgentCore agent_runtime_arn field's
+    validation_pattern must accept a complete runtime ARN whose resource part
+    is itself multi-segment (``runtime/<runtime-id>``), and reject the exact
+    truncated shape a naive split("/")-by-position parse used to produce (the
+    ARN cut off right after the ``runtime`` resource type).
+    """
+    app_instance = FastAPI()
+    app_instance.include_router(router)
+    test_client = TestClient(app_instance)
+
+    response = test_client.get("/public/agents/fields")
+    assert response.status_code == 200
+    agents = response.json()
+
+    bedrock_agentcore = next((a for a in agents if a["agent_type"] == "bedrock_agentcore"), None)
+    assert bedrock_agentcore is not None, "bedrock_agentcore agent type not found"
+    assert bedrock_agentcore["model_template"] == "bedrock/agentcore/{agent_runtime_arn}"
+
+    fields_by_key = {f["key"]: f for f in bedrock_agentcore["credential_fields"]}
+    arn_field = fields_by_key["agent_runtime_arn"]
+    assert arn_field["required"] is True
+    assert arn_field["include_in_litellm_params"] is False
+
+    pattern = arn_field.get("validation_pattern")
+    assert pattern, "agent_runtime_arn must ship a validation_pattern so the UI can reject a truncated ARN"
+
+    full_arn = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime/hosted_agent_4vm3i-BaTdfOELAs"
+    truncated_arn = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime"
+
+    assert re.match(pattern, full_arn), "the validator must accept a complete runtime ARN"
+    assert not re.match(pattern, truncated_arn), "the validator must reject the truncated ARN"
+
+
 # ---------------------------------------------------------------------------
 # /public/endpoints
 # ---------------------------------------------------------------------------
diff --git a/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py b/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py
index abbf6892a98..0085b6ebd36 100644
--- a/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py
+++ b/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py
@@ -324,6 +324,127 @@ def test_rag_query_stream_returns_event_stream(client_internal_user):
     assert "data: [DONE]" in response.text
 
 
+def test_rag_query_merges_managed_store_params(client_internal_user):
+    """
+    Regression: /v1/rag/query must consult the managed vector store registry
+    (like the direct /v1/vector_stores/{id}/search endpoint does) so that
+    provider, region, embedding model, etc. don't have to be repeated in
+    retrieval_config. Pre-fix the registry was never read, so managed S3
+    Vectors stores failed with "aws_region_name is required".
+    """
+    import litellm
+    from litellm.types.utils import ModelResponse
+
+    mock_vector_store = {
+        "vector_store_id": "s3-store",
+        "custom_llm_provider": "s3_vectors",
+        "litellm_params": {
+            "aws_region_name": "eu-west-1",
+            "embedding_model": "my-embed",
+            "vector_bucket_name": "bkt",
+        },
+    }
+    mock_registry = MagicMock()
+    mock_registry.get_litellm_managed_vector_store_from_registry.return_value = mock_vector_store
+
+    mock_response = ModelResponse(
+        id="chatcmpl-test",
+        choices=[{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}],
+        model="gpt-4o-mini",
+    )
+
+    with patch(  # test-quality-ok: aquery is the endpoint's downstream boundary; the forwarded config is what the test asserts
+        "litellm.proxy.rag_endpoints.endpoints.litellm.aquery",
+        new_callable=AsyncMock,
+        return_value=mock_response,
+    ) as mock_aquery, patch.object(litellm, "vector_store_registry", mock_registry), patch(  # test-quality-ok: seeds the managed-store registry the merge under test reads and grants access so real store resolution runs
+        "litellm.proxy.vector_store_endpoints.utils.can_user_access_vector_store",
+        new=AsyncMock(return_value=True),
+    ):
+        response = client_internal_user.post(
+            "/v1/rag/query",
+            json={
+                "model": "gpt-4o-mini",
+                "messages": [{"role": "user", "content": "hello"}],
+                "retrieval_config": {"vector_store_id": "s3-store"},
+            },
+        )
+
+    assert response.status_code == 200, response.json()
+    mock_aquery.assert_awaited_once()
+    forwarded_config = mock_aquery.await_args.kwargs["retrieval_config"]
+    assert forwarded_config["vector_store_id"] == "s3-store"
+    assert forwarded_config["custom_llm_provider"] == "s3_vectors"
+    assert forwarded_config["aws_region_name"] == "eu-west-1"
+    assert forwarded_config["embedding_model"] == "my-embed"
+    assert forwarded_config["vector_bucket_name"] == "bkt"
+
+
+def test_rag_query_store_params_win_over_user_retrieval_config(client_internal_user):
+    """Registry values must win over user-supplied retrieval_config keys so callers cannot override store credentials."""
+    import litellm
+    from litellm.types.utils import ModelResponse
+
+    mock_vector_store = {
+        "vector_store_id": "s3-store",
+        "custom_llm_provider": "s3_vectors",
+        "litellm_params": {"aws_region_name": "eu-west-1"},
+    }
+    mock_registry = MagicMock()
+    mock_registry.get_litellm_managed_vector_store_from_registry.return_value = mock_vector_store
+
+    mock_response = ModelResponse(
+        id="chatcmpl-test",
+        choices=[{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}],
+        model="gpt-4o-mini",
+    )
+
+    with patch(  # test-quality-ok: aquery is the endpoint's downstream boundary; the forwarded config is what the test asserts
+        "litellm.proxy.rag_endpoints.endpoints.litellm.aquery",
+        new_callable=AsyncMock,
+        return_value=mock_response,
+    ) as mock_aquery, patch.object(litellm, "vector_store_registry", mock_registry), patch(  # test-quality-ok: seeds the managed-store registry the merge under test reads and grants access so real store resolution runs
+        "litellm.proxy.vector_store_endpoints.utils.can_user_access_vector_store",
+        new=AsyncMock(return_value=True),
+    ):
+        response = client_internal_user.post(
+            "/v1/rag/query",
+            json={
+                "model": "gpt-4o-mini",
+                "messages": [{"role": "user", "content": "hello"}],
+                "retrieval_config": {"vector_store_id": "s3-store", "aws_region_name": "us-east-1"},
+            },
+        )
+
+    assert response.status_code == 200, response.json()
+    forwarded_config = mock_aquery.await_args.kwargs["retrieval_config"]
+    assert forwarded_config["aws_region_name"] == "eu-west-1"
+
+
+@pytest.mark.parametrize(
+    "blocked_key",
+    ["embedding_model", "litellm_embedding_model", "litellm_embedding_config", "litellm_credential_name"],
+)
+def test_rag_query_rejects_caller_embedding_selection_params(client_internal_user, blocked_key):
+    """
+    Regression: a caller must not pick the embedding model or credential used at
+    search time. Those resolve through the Router with the proxy's credentials,
+    bypassing the key's model permissions, so they may only come from the
+    managed store's server-side registration.
+    """
+    response = client_internal_user.post(
+        "/v1/rag/query",
+        json={
+            "model": "gpt-4o-mini",
+            "messages": [{"role": "user", "content": "hello"}],
+            "retrieval_config": {"vector_store_id": "s3-store", blocked_key: "attacker-choice"},
+        },
+    )
+
+    assert response.status_code == 400, response.json()
+    assert blocked_key in str(response.json())
+
+
 EICAR = r"X5O!P%@AP[4\PZX54(P^)7CC)7}$EICAR-STANDARD-ANTIVIRUS-TEST-FILE!$H+H*"
 INGEST_REQUEST = '{"ingest_options":{"vector_store":{"custom_llm_provider":"openai"}}}'
 
diff --git a/tests/test_litellm/proxy/test_budget_reservation.py b/tests/test_litellm/proxy/test_budget_reservation.py
index 95067929ac1..b8fb6170d34 100644
--- a/tests/test_litellm/proxy/test_budget_reservation.py
+++ b/tests/test_litellm/proxy/test_budget_reservation.py
@@ -819,6 +819,94 @@ async def test_should_cap_known_estimate_to_remaining_budget(
     ) == pytest.approx(0.9)
 
 
+@pytest.mark.asyncio
+async def test_fail_closed_rejects_known_estimate_exceeding_remaining_budget(
+    spend_counter_state,
+):
+    """LIT-5922: with strict enforcement on, a request whose known estimate does
+    not fit the remaining budget must be rejected before dispatch instead of
+    having its reservation shrunk to the headroom and admitted, and the counter
+    must be restored to the pre-request spend."""
+    counter_cache, key_cache = spend_counter_state
+    proxy_logging_obj = ProxyLogging(user_api_key_cache=key_cache)
+    valid_token = UserAPIKeyAuth(
+        token="key-budget-known-estimate-fail-closed",
+        spend=0.9,
+        max_budget=1.0,
+    )
+    counter_cache.in_memory_cache.set_cache(
+        key="spend:key:key-budget-known-estimate-fail-closed",
+        value=0.9,
+    )
+
+    with patch(  # test-quality-ok: reserve_budget_for_request takes no estimator, so pinning the estimate needs this attribute
+        "litellm.proxy.spend_tracking.budget_reservation.estimate_request_max_cost",
+        return_value=0.6,
+    ):
+        with pytest.raises(litellm.BudgetExceededError) as exc_info:
+            await reserve_budget_for_request(
+                request_body=_request_body(),
+                route="/chat/completions",
+                llm_router=None,
+                valid_token=valid_token,
+                team_object=None,
+                user_object=None,
+                prisma_client=None,
+                user_api_key_cache=key_cache,
+                proxy_logging_obj=proxy_logging_obj,
+                fail_closed_budget_enforcement=True,
+            )
+
+    assert exc_info.value.current_cost == pytest.approx(0.9)
+    assert exc_info.value.max_budget == pytest.approx(1.0)
+    assert "Current cost: 0.9, Estimated request cost: 0.6, Max budget: 1.0" in str(exc_info.value)
+    assert counter_cache.in_memory_cache.get_cache(
+        key="spend:key:key-budget-known-estimate-fail-closed"
+    ) == pytest.approx(0.9)
+
+
+@pytest.mark.asyncio
+async def test_fail_closed_tolerates_float_noise_when_estimate_exactly_fits(
+    spend_counter_state,
+):
+    """0.1 + 0.2 lands a hair above 0.3 in floating point. Strict enforcement
+    must treat that as fitting the budget, not reject it."""
+    counter_cache, key_cache = spend_counter_state
+    proxy_logging_obj = ProxyLogging(user_api_key_cache=key_cache)
+    valid_token = UserAPIKeyAuth(
+        token="key-budget-fail-closed-float-noise",
+        spend=0.1,
+        max_budget=0.3,
+    )
+    counter_cache.in_memory_cache.set_cache(
+        key="spend:key:key-budget-fail-closed-float-noise",
+        value=0.1,
+    )
+
+    with patch(  # test-quality-ok: reserve_budget_for_request takes no estimator, so pinning the estimate needs this attribute
+        "litellm.proxy.spend_tracking.budget_reservation.estimate_request_max_cost",
+        return_value=0.2,
+    ):
+        reservation = await reserve_budget_for_request(
+            request_body=_request_body(),
+            route="/chat/completions",
+            llm_router=None,
+            valid_token=valid_token,
+            team_object=None,
+            user_object=None,
+            prisma_client=None,
+            user_api_key_cache=key_cache,
+            proxy_logging_obj=proxy_logging_obj,
+            fail_closed_budget_enforcement=True,
+        )
+
+    assert reservation is not None
+    assert reservation["reserved_cost"] == pytest.approx(0.2)
+    assert counter_cache.in_memory_cache.get_cache(
+        key="spend:key:key-budget-fail-closed-float-noise"
+    ) == pytest.approx(0.3)
+
+
 @pytest.mark.asyncio
 async def test_should_clamp_reservation_to_default_when_output_cap_missing(
     spend_counter_state,
diff --git a/tests/test_litellm/proxy/test_redis_auth_cache_flag.py b/tests/test_litellm/proxy/test_redis_auth_cache_flag.py
index 772b08bc9d0..573bfc40c96 100644
--- a/tests/test_litellm/proxy/test_redis_auth_cache_flag.py
+++ b/tests/test_litellm/proxy/test_redis_auth_cache_flag.py
@@ -5,7 +5,7 @@ Verifies that _init_cache attaches Redis to user_api_key_cache only when
 the flag is explicitly set to True, and leaves it in-memory-only otherwise.
 """
 
-from contextlib import contextmanager
+from contextlib import ExitStack, contextmanager
 import json
 from unittest.mock import MagicMock, patch
 
@@ -167,3 +167,25 @@ class TestRedisAuthCacheFlag:
                     f"cli_sso_session_cache must always get Redis "
                     f"(enable_redis_auth_cache={flag_value!r})"
                 )
+
+    def test_flag_absent_still_shares_the_model_budget_counters_over_redis(self):
+        """
+        Per-model budget counters are spend counters: the limiter must be able to
+        push and read them through Redis without the auth-cache opt-in, or every
+        worker enforces and reports its own share of a key's spend
+        """
+        fake_redis = _FakeRedisCache()
+        limiter_cache = ps.model_max_budget_limiter.dual_cache
+        touched_caches = (
+            limiter_cache,
+            ps.spend_counter_cache,
+            ps.cli_sso_session_cache,
+            ps.user_api_key_cache,
+            ps.litellm_config_cache,
+        )
+        with ExitStack() as detached:
+            for cache in touched_caches:
+                detached.enter_context(patch.object(cache, "redis_cache", None))
+            ps._attach_redis_usage_cache(fake_redis, enable_redis_auth_cache=False)
+            assert limiter_cache.redis_cache is fake_redis
+            assert ps.user_api_key_cache.redis_cache is None
diff --git a/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py b/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py
index 903d5cb55f3..854ce351f2d 100644
--- a/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py
+++ b/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py
@@ -87,13 +87,15 @@ def test_router_vector_store_search_injects_executor_and_request_metadata():
     assert fallback.call_args.kwargs["model"] == "vector-alias"
     assert fallback.call_args.kwargs["original_function"] is original
 
-    create_original = MagicMock()
+    create_original = MagicMock(return_value="created")
     wrapped_create = router.factory_function(create_original, call_type="vector_store_create")
+    assert wrapped_create(name="store") == "created"
+    create_original.assert_called_once_with(name="store")
     with patch.object(  # test-quality-ok: fallback dispatch is the boundary this wrapper delegates to
-        router, "_generic_api_call_with_fallbacks", return_value="created"
+        router, "_generic_api_call_with_fallbacks", return_value="created-through-router"
     ) as fallback:
-        assert wrapped_create(name="store") == "created"
-    fallback.assert_called_once_with(original_function=create_original, name="store")
+        assert wrapped_create(model="vector-alias", name="store") == "created-through-router"
+    fallback.assert_called_once_with(original_function=create_original, model="vector-alias", name="store")
 
 
 @pytest.mark.asyncio
@@ -2919,3 +2921,35 @@ class TestAzureAIAnalyzeNamedIndexClassification:
             user_api_key_dict=self._team_member("analyze", ["read"]),
         )
         assert result is True
+
+
+@pytest.mark.parametrize(
+    "blocked_key",
+    ["embedding_model", "litellm_embedding_model", "litellm_embedding_config", "litellm_credential_name"],
+)
+def test_vector_store_search_rejects_caller_embedding_selection_params(blocked_key):
+    """
+    Regression: the search request body must not pick the embedding model or
+    credential used to embed the query. Those resolve through the Router with
+    the proxy's credentials, bypassing the key's model permissions, so they may
+    only come from the managed store's server-side registration.
+    """
+    from fastapi.testclient import TestClient
+
+    from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+    from litellm.proxy.proxy_server import app
+
+    mock_auth = UserAPIKeyAuth(user_id="test_internal_user", user_role=LitellmUserRoles.INTERNAL_USER.value)
+    original_overrides = app.dependency_overrides.copy()
+    app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
+    try:
+        client = TestClient(app)
+        response = client.post(
+            "/v1/vector_stores/s3-store/search",
+            json={"query": "hello", blocked_key: "attacker-choice"},
+        )
+    finally:
+        app.dependency_overrides = original_overrides
+
+    assert response.status_code == 400, response.json()
+    assert blocked_key in str(response.json())
diff --git a/tests/test_litellm/rag/test_main.py b/tests/test_litellm/rag/test_main.py
index 2d1b460513f..51d03544910 100644
--- a/tests/test_litellm/rag/test_main.py
+++ b/tests/test_litellm/rag/test_main.py
@@ -259,6 +259,135 @@ async def test_aquery_streaming_bills_sub_call_costs_into_final_event():
     assert standard_logging_object["response_cost"] >= 0.003
 
 
+@pytest.mark.asyncio
+async def test_aquery_forwards_provider_retrieval_config_and_router_to_search():
+    """
+    Regression: provider-specific retrieval_config keys (aws_region_name,
+    embedding_model, vector_bucket_name, ...) and the router must be forwarded
+    to the vector store search call. Pre-fix they were silently dropped, so
+    /v1/rag/query failed with provider config errors (e.g. S3 Vectors
+    "aws_region_name is required") even when the caller supplied them.
+    """
+    from unittest.mock import AsyncMock
+
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "gpt-4o-mini",
+                "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "test-key"},
+            }
+        ]
+    )
+
+    fake_search = AsyncMock(
+        return_value=VectorStoreSearchResponse(
+            object="vector_store.search_results.page", search_query="q", data=[]
+        )
+    )
+    with patch("litellm.vector_stores.asearch", new=fake_search):  # test-quality-ok: asearch is the boundary the forwarding contract under test targets
+        response = await litellm.aquery(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": "hello"}],
+            retrieval_config={
+                "vector_store_id": "bkt:idx",
+                "custom_llm_provider": "s3_vectors",
+                "top_k": 5,
+                "aws_region_name": "eu-west-1",
+                "embedding_model": "my-embed",
+                "vector_bucket_name": "bkt",
+            },
+            router=router,
+            mock_response="hi",
+        )
+
+    assert isinstance(response, ModelResponse)
+    fake_search.assert_awaited_once()
+    search_kwargs = fake_search.await_args.kwargs
+    assert search_kwargs["vector_store_id"] == "bkt:idx"
+    assert search_kwargs["custom_llm_provider"] == "s3_vectors"
+    assert search_kwargs["max_num_results"] == 5
+    assert search_kwargs["router"] is router
+    # provider-specific extras forwarded
+    assert search_kwargs["aws_region_name"] == "eu-west-1"
+    assert search_kwargs["embedding_model"] == "my-embed"
+    assert search_kwargs["vector_bucket_name"] == "bkt"
+    # consumed keys are not duplicated into the spread
+    assert "top_k" not in search_kwargs
+
+
+@pytest.mark.asyncio
+async def test_aquery_minimal_retrieval_config_forwards_no_extras():
+    """
+    A minimal retrieval_config must not leak consumed keys (or invent extras)
+    into the vector store search call.
+    """
+    from unittest.mock import AsyncMock
+
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    fake_search = AsyncMock(
+        return_value=VectorStoreSearchResponse(
+            object="vector_store.search_results.page", search_query="q", data=[]
+        )
+    )
+    with patch("litellm.vector_stores.asearch", new=fake_search):  # test-quality-ok: asearch is the boundary the forwarding contract under test targets
+        await litellm.aquery(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": "hello"}],
+            retrieval_config={"vector_store_id": "vs_test_123", "custom_llm_provider": "openai"},
+            mock_response="hi",
+        )
+
+    fake_search.assert_awaited_once()
+    search_kwargs = fake_search.await_args.kwargs
+    assert search_kwargs["vector_store_id"] == "vs_test_123"
+    assert search_kwargs["custom_llm_provider"] == "openai"
+    assert search_kwargs["router"] is None
+    leaked = {"top_k", "filters", "retrieval_filter", "aws_region_name", "embedding_model", "vector_bucket_name"}
+    assert not (leaked & set(search_kwargs.keys()))
+
+
+@pytest.mark.asyncio
+async def test_aquery_does_not_forward_connection_override_keys_to_search():
+    """
+    Only allowlisted retrieval_config keys may reach the vector store search
+    call. Caller-controlled connection overrides (api_base, api_key, arbitrary
+    extras) must be dropped, otherwise a caller could redirect store
+    credentials to an attacker-chosen host.
+    """
+    from unittest.mock import AsyncMock
+
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    fake_search = AsyncMock(
+        return_value=VectorStoreSearchResponse(
+            object="vector_store.search_results.page", search_query="q", data=[]
+        )
+    )
+    with patch("litellm.vector_stores.asearch", new=fake_search):  # test-quality-ok: asearch is the boundary the forwarding contract under test targets
+        await litellm.aquery(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": "hello"}],
+            retrieval_config={
+                "vector_store_id": "bkt:idx",
+                "custom_llm_provider": "s3_vectors",
+                "aws_region_name": "eu-west-1",
+                "api_base": "https://attacker.example.com",
+                "api_key": "attacker-key",
+                "arbitrary_extra": "nope",
+            },
+            mock_response="hi",
+        )
+
+    fake_search.assert_awaited_once()
+    search_kwargs = fake_search.await_args.kwargs
+    assert search_kwargs["aws_region_name"] == "eu-west-1"
+    blocked = {"api_base", "api_key", "arbitrary_extra"}
+    assert not (blocked & set(search_kwargs.keys()))
+
+
 def test_rag_call_types_are_registered():
     """
     query/aquery/ingest/aingest are @client-decorated entry points, so their
diff --git a/tests/test_litellm/rerank_api/test_main.py b/tests/test_litellm/rerank_api/test_main.py
index 587be59c550..2b6cfeda2c2 100644
--- a/tests/test_litellm/rerank_api/test_main.py
+++ b/tests/test_litellm/rerank_api/test_main.py
@@ -111,6 +111,99 @@ def test_together_rerank_honors_api_base(respx_mock: respx.MockRouter):
     assert mock_route.calls[0].request.headers["authorization"] == "Bearer fake-together-key"
 
 
+DASHSCOPE_404_BODY = {
+    "error": {
+        "message": "The model `does-not-exist` does not exist or you do not have access to it.",
+        "type": "invalid_request_error",
+        "param": None,
+        "code": "model_not_found",
+    },
+    "request_id": "mock-request-id",
+}
+
+
+def test_rerank_error_names_provider_and_keeps_body(respx_mock: respx.MockRouter, monkeypatch):
+    """Regression for the rerank error path mapping with the unresolved provider param:
+    a provider 404 surfaced as 'None - ' instead of naming the provider and its error body."""
+    monkeypatch.delenv("DASHSCOPE_API_BASE", raising=False)
+    monkeypatch.delenv("DASHSCOPE_API_BASE_RERANK", raising=False)
+
+    mock_route = respx_mock.post("https://dashscope.example/v1/reranks")
+    mock_route.return_value = httpx.Response(404, json=DASHSCOPE_404_BODY)
+
+    with pytest.raises(litellm.NotFoundError) as exc_info:
+        litellm.rerank(
+            model="dashscope/does-not-exist",
+            query=MARKER_QUERY,
+            documents=[MARKER_DOC],
+            api_key="fake-dashscope-key",
+            api_base="https://dashscope.example/v1",
+        )
+
+    assert mock_route.called
+    assert "DashscopeException" in str(exc_info.value)
+    assert "does not exist or you do not have access to it" in str(exc_info.value)
+    assert "None - " not in str(exc_info.value)
+
+
+@pytest.mark.asyncio
+async def test_arerank_error_is_mapped_to_litellm_exception(respx_mock: respx.MockRouter, monkeypatch):
+    """Regression for arerank's bare re-raise: provider errors escaped as raw
+    provider exception classes instead of the mapped litellm exception contract."""
+    monkeypatch.delenv("DASHSCOPE_API_BASE", raising=False)
+    monkeypatch.delenv("DASHSCOPE_API_BASE_RERANK", raising=False)
+    monkeypatch.setenv("DISABLE_AIOHTTP_TRANSPORT", "True")
+
+    mock_route = respx_mock.post("https://dashscope.example/v1/reranks")
+    mock_route.return_value = httpx.Response(404, json=DASHSCOPE_404_BODY)
+
+    with pytest.raises(litellm.NotFoundError) as exc_info:
+        await litellm.arerank(
+            model="dashscope/does-not-exist",
+            query=MARKER_QUERY,
+            documents=[MARKER_DOC],
+            api_key="fake-dashscope-key",
+            api_base="https://dashscope.example/v1",
+        )
+
+    assert mock_route.called
+    assert "DashscopeException" in str(exc_info.value)
+    assert "does not exist or you do not have access to it" in str(exc_info.value)
+    assert "None - " not in str(exc_info.value)
+
+
+@pytest.mark.asyncio
+async def test_arerank_declared_authenticating_provider_skips_resolution(monkeypatch):
+    """Regression for the event-loop hazard in arerank's provider pre-resolution:
+    get_llm_provider runs the blocking OAuth device flow for github_copilot/chatgpt,
+    so arerank must adopt the declared provider instead of resolving it, while the
+    except path still maps with that declared provider."""
+    from litellm.llms.base_llm.chat.transformation import BaseLLMException
+
+    resolution_calls = []
+
+    def record_resolution(*args, **kwargs):
+        resolution_calls.append((args, kwargs))
+        return "gpt-4o", "github_copilot", None, None
+
+    def rerank_raises_provider_error(*args, **kwargs):
+        raise BaseLLMException(status_code=401, message='{"error":"bad key"}')
+
+    monkeypatch.setattr(litellm, "get_llm_provider", record_resolution)
+    monkeypatch.setattr("litellm.rerank_api.main.rerank", rerank_raises_provider_error)
+
+    with pytest.raises(litellm.AuthenticationError) as exc_info:
+        await litellm.arerank(
+            model="github_copilot/gpt-4o",
+            query=MARKER_QUERY,
+            documents=[MARKER_DOC],
+        )
+
+    assert resolution_calls == []
+    assert "Github_copilotException" in str(exc_info.value)
+    assert "None - " not in str(exc_info.value)
+
+
 @pytest.mark.asyncio
 async def test_together_rerank_async_honors_env_api_base(respx_mock: respx.MockRouter, monkeypatch):
     """Regression: TOGETHER_AI_API_BASE was honored by chat but ignored by rerank."""
diff --git a/tests/test_litellm/responses/test_streaming_iterator.py b/tests/test_litellm/responses/test_streaming_iterator.py
index 677faf7f655..9edcaaef034 100644
--- a/tests/test_litellm/responses/test_streaming_iterator.py
+++ b/tests/test_litellm/responses/test_streaming_iterator.py
@@ -326,3 +326,55 @@ def test_run_post_success_hooks_does_not_report_generation_time_as_overhead():
 
     assert iterator.completed_response._hidden_params["_response_ms"] == 10000.0
     assert "litellm_overhead_time_ms" not in iterator.completed_response._hidden_params
+
+
+def _responses_api_response_with_usage() -> ResponsesAPIResponse:
+    from litellm.types.llms.openai import ResponseAPIUsage
+
+    return ResponsesAPIResponse(
+        id="resp_lit6427",
+        created_at=int(datetime(2025, 1, 1).timestamp()),
+        status="completed",
+        model="mantle-claude",
+        object="response",
+        output=[],
+        usage=ResponseAPIUsage(input_tokens=20, output_tokens=60, total_tokens=80),
+    )
+
+
+def test_stamp_responses_usage_cost_stamps_computed_cost():
+    from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
+
+    response = _responses_api_response_with_usage()
+    logging_obj = Mock(spec=LiteLLMLoggingObj)
+    logging_obj._response_cost_calculator.return_value = 0.000704
+
+    _stamp_responses_usage_cost(response, logging_obj)
+
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.000704)
+    logging_obj._response_cost_calculator.assert_called_once_with(result=response)
+
+
+def test_stamp_responses_usage_cost_keeps_provider_reported_cost():
+    from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
+
+    response = _responses_api_response_with_usage()
+    setattr(response.usage, "cost", 0.5)
+    logging_obj = Mock(spec=LiteLLMLoggingObj)
+
+    _stamp_responses_usage_cost(response, logging_obj)
+
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.5)
+    logging_obj._response_cost_calculator.assert_not_called()
+
+
+def test_stamp_responses_usage_cost_survives_calculator_failure():
+    from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
+
+    response = _responses_api_response_with_usage()
+    logging_obj = Mock(spec=LiteLLMLoggingObj)
+    logging_obj._response_cost_calculator.side_effect = RuntimeError("cost map unavailable")
+
+    _stamp_responses_usage_cost(response, logging_obj)
+
+    assert getattr(response.usage, "cost", None) is None
diff --git a/tests/test_litellm/router_utils/test_fallback_event_handlers.py b/tests/test_litellm/router_utils/test_fallback_event_handlers.py
index 8336926c050..894b2d9e74f 100644
--- a/tests/test_litellm/router_utils/test_fallback_event_handlers.py
+++ b/tests/test_litellm/router_utils/test_fallback_event_handlers.py
@@ -11,7 +11,10 @@ from litellm.router_utils.fallback_event_handlers import (
     AttemptedFallbackTargets,
     _trigger_cooldown_for_failed_deployment,
     fallback_attempt_key,
+    clear_pre_routing_selection,
     get_fallback_model_group,
+    get_pre_routing_selection,
+    record_pre_routing_selection,
     run_async_fallback,
 )
 
@@ -1090,3 +1093,119 @@ async def test_run_async_fallback_preserves_original_model_group_on_nested_fallb
     metadata = router.received_kwargs["metadata"]
     assert metadata["attempted_fallbacks"] == 2
     assert metadata["original_model_group"] == "primary-model"
+
+
+class TestPreRoutingSelectionCarriesToFallbacks:
+    """#38832: a complexity/auto router picks a tier behind the router name, but fallback
+    lookup kept using the router name, so the tier's configured chain never ran."""
+
+    def test_selection_is_recorded_in_the_metadata_bucket(self):
+        kwargs = {"model": "smart-router", "metadata": {}}
+        record_pre_routing_selection(kwargs, "tier1")
+        assert kwargs["metadata"]["pre_routing_selected_model"] == "tier1"
+        assert get_pre_routing_selection(kwargs) == "tier1"
+
+    def test_selection_is_recorded_in_the_litellm_metadata_bucket(self):
+        kwargs = {"model": "smart-router", "litellm_metadata": {}}
+        record_pre_routing_selection(kwargs, "tier2")
+        assert get_pre_routing_selection(kwargs) == "tier2"
+
+    def test_a_bucket_survives_the_kwargs_copy_that_fallbacks_run_on(self):
+        """The bucket is shared by reference, which is the whole reason this works."""
+        outer = {"model": "smart-router", "metadata": {}}
+        inner = {**outer}
+        record_pre_routing_selection(inner, "tier1")
+        assert get_pre_routing_selection(outer) == "tier1"
+
+    def test_no_selection_reads_as_none(self):
+        assert get_pre_routing_selection({"model": "smart-router", "metadata": {}}) is None
+        assert get_pre_routing_selection({"model": "smart-router"}) is None
+
+    def test_missing_kwargs_is_a_no_op(self):
+        """A caller with no kwargs must not raise, and must not leak the selection anywhere."""
+        record_pre_routing_selection(None, "tier1")
+
+        assert get_pre_routing_selection({}) is None
+
+    def test_a_non_dict_bucket_is_ignored(self):
+        kwargs = {"model": "smart-router", "metadata": "not-a-dict"}
+        record_pre_routing_selection(kwargs, "tier1")
+        assert get_pre_routing_selection(kwargs) is None
+
+    def test_fallbacks_resolve_against_the_selected_tier(self):
+        """The lookup the router performs, keyed on the tier rather than the router name."""
+        fallbacks = [{"tier1": ["backup-a", "backup-b"]}, {"tier2": ["backup-c"]}]
+        assert get_fallback_model_group(fallbacks=fallbacks, model_group="tier1")[0] == ["backup-a", "backup-b"]
+        assert get_fallback_model_group(fallbacks=fallbacks, model_group="smart-router")[0] is None
+
+
+class TestPreRoutingSelectionIsPerHop:
+    """#38832 review: the buckets also carry whatever the caller sent, and a fallback hop
+    inherits the previous hop's tier, so a hop must start without a selection."""
+
+    def test_a_caller_supplied_selection_is_dropped(self):
+        kwargs = {"model": "plain", "metadata": {"pre_routing_selected_model": "tier1"}}
+
+        clear_pre_routing_selection(kwargs)
+
+        assert get_pre_routing_selection(kwargs) is None
+        assert "pre_routing_selected_model" not in kwargs["metadata"]
+
+    def test_both_buckets_are_cleared(self):
+        kwargs = {
+            "metadata": {"pre_routing_selected_model": "tier1"},
+            "litellm_metadata": {"pre_routing_selected_model": "tier2"},
+        }
+
+        clear_pre_routing_selection(kwargs)
+
+        assert get_pre_routing_selection(kwargs) is None
+
+    def test_the_rest_of_the_bucket_is_left_alone(self):
+        kwargs = {"metadata": {"pre_routing_selected_model": "tier1", "tags": ["a"]}}
+
+        clear_pre_routing_selection(kwargs)
+
+        assert kwargs["metadata"] == {"tags": ["a"]}
+
+    def test_clearing_is_a_no_op_without_a_usable_bucket(self):
+        kwargs = {"model": "plain", "metadata": "not-a-dict"}
+
+        clear_pre_routing_selection(None)
+        clear_pre_routing_selection(kwargs)
+
+        assert kwargs == {"model": "plain", "metadata": "not-a-dict"}
+
+    def test_a_selection_recorded_after_clearing_is_kept(self):
+        """Clearing runs before routing, so the hook's own write must survive it."""
+        kwargs = {"model": "smart-router", "metadata": {"pre_routing_selected_model": "stale"}}
+
+        clear_pre_routing_selection(kwargs)
+        record_pre_routing_selection(kwargs, "tier1")
+
+        assert get_pre_routing_selection(kwargs) == "tier1"
+
+
+class TestOrderedFallbackLookupGroups:
+    def test_tier_first_then_requested_group_deduped(self):
+        from litellm.router_utils.fallback_event_handlers import (
+            PRE_ROUTING_SELECTED_MODEL_KEY,
+            fallback_lookup_groups,
+        )
+
+        kwargs = {"litellm_metadata": {PRE_ROUTING_SELECTED_MODEL_KEY: "tier1"}}
+        assert fallback_lookup_groups(kwargs, "smart-router") == ("tier1", "smart-router")
+        assert fallback_lookup_groups(kwargs, "tier1") == ("tier1",)
+        assert fallback_lookup_groups({}, "smart-router") == ("smart-router",)
+        assert fallback_lookup_groups({}, None) == ()
+
+    def test_first_resolving_group_wins_and_generic_idx_survives_a_miss(self):
+        from litellm.router_utils.fallback_event_handlers import (
+            get_fallback_model_group_for_lookup_groups,
+        )
+
+        fallbacks = [{"tier1": ["backup-a"]}, {"smart-router": ["backup-b"]}, {"*": ["backup-c"]}]
+        assert get_fallback_model_group_for_lookup_groups(fallbacks, ("tier1", "smart-router")) == (["backup-a"], None)
+        assert get_fallback_model_group_for_lookup_groups(fallbacks, ("tier9", "smart-router")) == (["backup-b"], None)
+        assert get_fallback_model_group_for_lookup_groups(fallbacks, ("tier9", "no-such")) == (["backup-c"], 2)
+        assert get_fallback_model_group_for_lookup_groups([{"tier1": ["backup-a"]}], ("no", "nope")) == (None, None)
diff --git a/tests/test_litellm/rust_bridge/test_verify_linux_native_wheel.py b/tests/test_litellm/rust_bridge/test_verify_linux_native_wheel.py
new file mode 100644
index 00000000000..e449d4392d8
--- /dev/null
+++ b/tests/test_litellm/rust_bridge/test_verify_linux_native_wheel.py
@@ -0,0 +1,197 @@
+from __future__ import annotations
+
+import importlib.util
+import subprocess
+import sys
+import zipfile
+from collections.abc import Callable, Mapping, Sequence
+from pathlib import Path
+from types import MappingProxyType, ModuleType
+from typing import Final, Protocol, cast
+
+import pytest
+
+
+class _CommandRunner(Protocol):
+    def __call__(
+        self,
+        command: tuple[str, ...],
+        *,
+        check: bool,
+        capture_output: bool,
+        text: bool,
+    ) -> subprocess.CompletedProcess[str]: ...
+
+
+class _VerifierModule(Protocol):
+    main: Callable[
+        [
+            Sequence[str] | None,
+            Mapping[str, str] | None,
+            Callable[[Path], ModuleType | None],
+            _CommandRunner,
+        ],
+        int,
+    ]
+
+
+_REPO_ROOT: Final = Path(__file__).resolve().parents[3]
+_MODULE_PATH: Final = _REPO_ROOT / ".github" / "scripts" / "verify_linux_native_wheel.py"
+_SPEC: Final = importlib.util.spec_from_file_location("verify_linux_native_wheel", _MODULE_PATH)
+assert _SPEC is not None and _SPEC.loader is not None
+_LOADED_VERIFIER: Final = importlib.util.module_from_spec(_SPEC)
+sys.modules[_SPEC.name] = _LOADED_VERIFIER
+_SPEC.loader.exec_module(_LOADED_VERIFIER)
+verifier: Final = cast(_VerifierModule, _LOADED_VERIFIER)
+
+_EXPECTED_TAG: Final = "cp310-abi3-linux_x86_64"
+_NATIVE_MEMBER: Final = "litellm/rust_bridge/_native.abi3.so"
+_DIST_INFO: Final = "litellm-1.100.0.dist-info"
+
+
+def _write_wheel(
+    tmp_path: Path,
+    *,
+    filename_tag: str,
+    metadata_tags: tuple[str, ...] | None = (_EXPECTED_TAG,),
+    dist_info: str = _DIST_INFO,
+    duplicate_wheel: bool = False,
+) -> Path:
+    wheel: Final = tmp_path / f"litellm-1.100.0-{filename_tag}.whl"
+    with zipfile.ZipFile(wheel, "w", compression=zipfile.ZIP_DEFLATED) as archive:
+        archive.writestr(_NATIVE_MEMBER, b"synthetic native extension")
+        archive.writestr(
+            f"{dist_info}/METADATA",
+            "Metadata-Version: 2.1\nName: litellm\nVersion: 1.100.0\n",
+        )
+        archive.writestr(
+            f"{dist_info}/RECORD",
+            f"{_NATIVE_MEMBER},,\n{dist_info}/WHEEL,,\n",
+        )
+        if metadata_tags is not None:
+            wheel_metadata: Final = (
+                "Wheel-Version: 1.0\nGenerator: regression-test\nRoot-Is-Purelib: false\n"
+                + "".join(f"Tag: {tag}\n" for tag in metadata_tags)
+            )
+            archive.writestr(f"{dist_info}/WHEEL", wheel_metadata)
+            if duplicate_wheel:
+                archive.writestr(f"{dist_info}/WHEEL", wheel_metadata)
+    return wheel
+
+
+def _fake_subprocess_run(
+    command: tuple[str, ...],
+    *,
+    check: bool,
+    capture_output: bool,
+    text: bool,
+) -> subprocess.CompletedProcess[str]:
+    assert check and capture_output and text
+    if command == ("rustc", "--version"):
+        return subprocess.CompletedProcess(command, 0, stdout="rustc 1.98.0 (regression-test)\n", stderr="")
+    if "--sections" in command:
+        return subprocess.CompletedProcess(command, 0, stdout="[ 1] .text PROGBITS\n", stderr="")
+    if "--dyn-syms" in command:
+        return subprocess.CompletedProcess(command, 0, stdout="PyInit__native\n", stderr="")
+    raise AssertionError(f"unexpected subprocess command: {command}")
+
+
+class _NativeModuleWithPanicHook(ModuleType):
+    def _panic_for_test(self) -> None:
+        return None
+
+
+def _run_verifier(
+    wheel: Path,
+    *,
+    exposes_panic: bool = False,
+) -> int:
+    native_module: Final = (
+        _NativeModuleWithPanicHook("litellm.rust_bridge._native")
+        if exposes_panic
+        else ModuleType("litellm.rust_bridge._native")
+    )
+
+    def _fake_load_native_module(_: Path) -> ModuleType:
+        return native_module
+
+    environment: Final = MappingProxyType({"GITHUB_STEP_SUMMARY": str(wheel.parent / "summary.md")})
+    return verifier.main(
+        (str(_MODULE_PATH), str(wheel)),
+        environment,
+        _fake_load_native_module,
+        _fake_subprocess_run,
+    )
+
+
+def test_accepts_expected_release_wheel_tags(tmp_path: Path) -> None:
+    wheel: Final = _write_wheel(tmp_path, filename_tag=_EXPECTED_TAG)
+
+    assert _run_verifier(wheel) == 0
+
+
+def test_rejects_cp312_version_specific_wheel(tmp_path: Path) -> None:
+    tag: Final = "cp312-cp312-linux_x86_64"
+    wheel: Final = _write_wheel(tmp_path, filename_tag=tag, metadata_tags=(tag,))
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_non_linux_platform_tag(tmp_path: Path) -> None:
+    tag: Final = "cp310-abi3-win_amd64"
+    wheel: Final = _write_wheel(tmp_path, filename_tag=tag, metadata_tags=(tag,))
+
+    assert _run_verifier(wheel) == 1
+
+
+@pytest.mark.parametrize(
+    "metadata_tags",
+    (None, ("cp312-cp312-linux_x86_64",)),
+    ids=("missing", "mismatched"),
+)
+def test_rejects_missing_or_mismatched_wheel_metadata_tag(
+    tmp_path: Path,
+    metadata_tags: tuple[str, ...] | None,
+) -> None:
+    wheel: Final = _write_wheel(tmp_path, filename_tag=_EXPECTED_TAG, metadata_tags=metadata_tags)
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_wheel_metadata_from_wrong_dist_info_directory(
+    tmp_path: Path,
+) -> None:
+    wheel: Final = _write_wheel(
+        tmp_path,
+        filename_tag=_EXPECTED_TAG,
+        dist_info="decoy-1.0.0.dist-info",
+    )
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_duplicate_wheel_metadata_tags(tmp_path: Path) -> None:
+    wheel: Final = _write_wheel(
+        tmp_path,
+        filename_tag=_EXPECTED_TAG,
+        metadata_tags=(_EXPECTED_TAG, _EXPECTED_TAG),
+    )
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_duplicate_wheel_metadata_file(tmp_path: Path) -> None:
+    with pytest.warns(UserWarning, match="Duplicate name"):
+        wheel: Final = _write_wheel(
+            tmp_path,
+            filename_tag=_EXPECTED_TAG,
+            duplicate_wheel=True,
+        )
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_production_module_exposing_panic_hook(tmp_path: Path) -> None:
+    wheel: Final = _write_wheel(tmp_path, filename_tag=_EXPECTED_TAG)
+
+    assert _run_verifier(wheel, exposes_panic=True) == 1
diff --git a/tests/test_litellm/test_bedrock_usgov_pricing.py b/tests/test_litellm/test_bedrock_usgov_pricing.py
index 6b3312b5cc4..f7d95ecda01 100644
--- a/tests/test_litellm/test_bedrock_usgov_pricing.py
+++ b/tests/test_litellm/test_bedrock_usgov_pricing.py
@@ -26,9 +26,7 @@ import pytest
 
 @pytest.fixture(scope="module")
 def model_data():
-    json_path = os.path.join(
-        os.path.dirname(__file__), "../../model_prices_and_context_window.json"
-    )
+    json_path = os.path.join(os.path.dirname(__file__), "../../model_prices_and_context_window.json")
     with open(json_path) as f:
         return json.load(f)
 
@@ -51,21 +49,14 @@ def test_usgov_sonnet_4_5_pricing(model_data, model_key):
     info = model_data[model_key]
 
     assert info["input_cost_per_token"] == 3.6e-06, (
-        f"{model_key}: input_cost_per_token should be $3.60/MTok "
-        f"(got {info['input_cost_per_token']})"
+        f"{model_key}: input_cost_per_token should be $3.60/MTok (got {info['input_cost_per_token']})"
     )
-    assert (
-        info["output_cost_per_token"] == 1.8e-05
-    ), f"{model_key}: output_cost_per_token should be $18.00/MTok"
-    assert (
-        info["cache_creation_input_token_cost"] == 4.5e-06
-    ), f"{model_key}: 5m cache write should be $4.50/MTok"
-    assert (
-        info["cache_creation_input_token_cost_above_1hr"] == 7.2e-06
-    ), f"{model_key}: 1h cache write should be $7.20/MTok"
-    assert (
-        info["cache_read_input_token_cost"] == 3.6e-07
-    ), f"{model_key}: cache read should be $0.36/MTok"
+    assert info["output_cost_per_token"] == 1.8e-05, f"{model_key}: output_cost_per_token should be $18.00/MTok"
+    assert info["cache_creation_input_token_cost"] == 4.5e-06, f"{model_key}: 5m cache write should be $4.50/MTok"
+    assert info["cache_creation_input_token_cost_above_1hr"] == 7.2e-06, (
+        f"{model_key}: 1h cache write should be $7.20/MTok"
+    )
+    assert info["cache_read_input_token_cost"] == 3.6e-07, f"{model_key}: cache read should be $0.36/MTok"
 
 
 def test_usgov_carries_20_percent_premium_over_global(model_data):
@@ -84,9 +75,7 @@ def test_usgov_carries_20_percent_premium_over_global(model_data):
         "cache_read_input_token_cost",
     ):
         ratio = usgov_info[field] / global_info[field]
-        assert (
-            abs(ratio - 1.2) < 1e-9
-        ), f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
+        assert abs(ratio - 1.2) < 1e-9, f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
 
 
 # The us-gov.anthropic.* cross-region inference profile is the only us-gov
@@ -112,9 +101,7 @@ def test_usgov_cross_region_above_200k_carries_gov_premium(model_data, field, ex
     """
     info = model_data[USGOV_CROSS_REGION_KEY]
     assert field in info, f"{USGOV_CROSS_REGION_KEY}: missing field {field}"
-    assert (
-        info[field] == expected
-    ), f"{USGOV_CROSS_REGION_KEY}: {field} should be {expected} (got {info[field]})"
+    assert info[field] == expected, f"{USGOV_CROSS_REGION_KEY}: {field} should be {expected} (got {info[field]})"
 
 
 def test_usgov_cross_region_above_200k_ratio_to_global(model_data):
@@ -127,6 +114,176 @@ def test_usgov_cross_region_above_200k_ratio_to_global(model_data):
     usgov_info = model_data[USGOV_CROSS_REGION_KEY]
     for field in EXPECTED_USGOV_ABOVE_200K:
         ratio = usgov_info[field] / global_info[field]
-        assert (
-            abs(ratio - 1.2) < 1e-9
-        ), f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
+        assert abs(ratio - 1.2) < 1e-9, f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
+
+
+CLAUDE_GOV_EXPECTED = {
+    "anthropic.claude-sonnet-5": {
+        "input_cost_per_token": 2.4e-06,
+        "output_cost_per_token": 1.2e-05,
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+    },
+    "anthropic.claude-opus-4-8": {
+        "input_cost_per_token": 6e-06,
+        "output_cost_per_token": 3e-05,
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+    },
+}
+
+
+USGOV_CLAUDE_KEY_TEMPLATES = {
+    "bedrock/us-gov-east-1/{base_key}": "bedrock",
+    "bedrock/us-gov-west-1/{base_key}": "bedrock",
+    "us-gov.{base_key}": "bedrock_converse",
+}
+
+
+@pytest.mark.parametrize("base_key", CLAUDE_GOV_EXPECTED)
+@pytest.mark.parametrize("key_template,expected_provider", USGOV_CLAUDE_KEY_TEMPLATES.items())
+def test_usgov_claude_sonnet5_opus48_pricing(model_data, key_template, expected_provider, base_key):
+    """Sonnet 5 and Opus 4.8 gov entries, both in-region keys and the us-gov.
+    geo inference profile the model cards list for GovCloud, must match the
+    rates AWS publishes on the Bedrock pricing page (1.2x global).
+    """
+    gov_key = key_template.format(base_key=base_key)
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    assert info["litellm_provider"] == expected_provider
+    for field, expected in CLAUDE_GOV_EXPECTED[base_key].items():
+        assert info[field] == expected, f"{gov_key}: {field} should be {expected} (got {info[field]})"
+        ratio = info[field] / model_data[base_key][field]
+        assert abs(ratio - 1.2) < 1e-9, f"{gov_key}: {field} gov/global ratio is {ratio}, expected 1.2"
+
+
+CONVERSE_GOV_EXPECTED = {
+    "nvidia.nemotron-nano-3-30b": (7.2e-08, 2.88e-07),
+    "nvidia.nemotron-nano-12b-v2": (2.4e-07, 7.2e-07),
+    "nvidia.nemotron-super-3-120b": (1.8e-07, 7.8e-07),
+    "openai.gpt-oss-20b-1:0": (8.4e-08, 3.6e-07),
+    "openai.gpt-oss-120b-1:0": (1.8e-07, 7.2e-07),
+}
+
+
+@pytest.mark.parametrize("base_key", CONVERSE_GOV_EXPECTED)
+@pytest.mark.parametrize("region", ["us-gov-east-1", "us-gov-west-1"])
+def test_usgov_converse_model_pricing(model_data, region, base_key):
+    """Nemotron and gpt-oss gov entries must match the AWS Bedrock offer file,
+    which prices both GovCloud regions identically at 1.2x commercial.
+    """
+    gov_key = f"bedrock/{region}/{base_key}"
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    expected_input, expected_output = CONVERSE_GOV_EXPECTED[base_key]
+    assert info["input_cost_per_token"] == expected_input
+    assert info["output_cost_per_token"] == expected_output
+    assert info["litellm_provider"] == "bedrock"
+    base = model_data[base_key]
+    assert abs(info["input_cost_per_token"] / base["input_cost_per_token"] - 1.2) < 1e-9
+    assert abs(info["output_cost_per_token"] / base["output_cost_per_token"] - 1.2) < 1e-9
+
+
+def test_usgov_west_llama3_8b_output_price_fixed(model_data):
+    """The us-gov-west-1 llama3-8b entry carried the 70B output rate ($2.65/MTok);
+    the AWS Bedrock offer file prices output at $0.60/MTok. AWS lists the model
+    in us-gov-west-1 only, so there is no east entry to check.
+    """
+    info = model_data["bedrock/us-gov-west-1/meta.llama3-8b-instruct-v1:0"]
+    assert info["input_cost_per_token"] == 3e-07
+    assert info["output_cost_per_token"] == 6e-07
+
+
+MANTLE_GOV_TIERED_EXPECTED = {
+    "openai.gpt-5.6-luna": {
+        "input_cost_per_token": 2.64e-07,
+        "input_cost_per_token_above_272k_tokens": 5.28e-07,
+        "cache_creation_input_token_cost": 3.3e-07,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-07,
+        "cache_read_input_token_cost": 2.64e-08,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-08,
+        "output_cost_per_token": 1.584e-06,
+        "output_cost_per_token_above_272k_tokens": 2.376e-06,
+    },
+    "openai.gpt-5.6-terra": {
+        "input_cost_per_token": 2.64e-06,
+        "input_cost_per_token_above_272k_tokens": 5.28e-06,
+        "cache_creation_input_token_cost": 3.3e-06,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-06,
+        "cache_read_input_token_cost": 2.64e-07,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-07,
+        "output_cost_per_token": 1.584e-05,
+        "output_cost_per_token_above_272k_tokens": 2.376e-05,
+    },
+}
+
+
+@pytest.mark.parametrize("model", MANTLE_GOV_TIERED_EXPECTED)
+def test_usgov_west_mantle_terra_luna_pricing(model_data, model):
+    """Terra and Luna carry 1.2x commercial across every tier in the
+    us-gov-west-1 offer file; the us-gov-east-1 offer file has no SKUs for them.
+    """
+    gov_key = f"bedrock_mantle/us-gov-west-1/{model}"
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    for field, expected in MANTLE_GOV_TIERED_EXPECTED[model].items():
+        assert info[field] == expected, f"{gov_key}: {field} should be {expected} (got {info[field]})"
+    assert info["litellm_provider"] == "bedrock_mantle"
+    assert f"bedrock_mantle/us-gov-east-1/{model}" not in model_data
+
+
+@pytest.mark.parametrize("region", ["us-gov-east-1", "us-gov-west-1"])
+def test_usgov_mantle_gpt_5_4_pricing_has_no_long_context_tier(model_data, region):
+    """gpt-5.4 gov rates come from the offer file, which publishes only the
+    standard tier in GovCloud: no long-context SKUs exist there, unlike commercial.
+    """
+    gov_key = f"bedrock_mantle/{region}/openai.gpt-5.4"
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    assert info["input_cost_per_token"] == 3.3e-06
+    assert info["cache_read_input_token_cost"] == 3.3e-07
+    assert info["output_cost_per_token"] == 1.98e-05
+    assert not any(field.endswith("_above_272k_tokens") for field in info)
+
+
+def test_usgov_mantle_grok_4_3_west_only(model_data):
+    """grok-4.3 is priced in the us-gov-west-1 offer file only; the east offer
+    file carries grok-4.6 instead.
+    """
+    info = model_data["bedrock_mantle/us-gov-west-1/xai.grok-4.3"]
+    assert info["input_cost_per_token"] == 1.5e-06
+    assert info["output_cost_per_token"] == 3e-06
+    assert info["cache_read_input_token_cost"] == 2.4e-07
+    assert "bedrock_mantle/us-gov-east-1/xai.grok-4.3" not in model_data
+
+
+AZURE_GOV_EXPECTED = {
+    "azure/us-gov/gpt-5.1": {
+        "input_cost_per_token": 1.71875e-06,
+        "cache_read_input_token_cost": 1.71875e-07,
+        "output_cost_per_token": 1.375e-05,
+    },
+    "azure/us-gov/o3-mini": {
+        "input_cost_per_token": 1.513e-06,
+        "cache_read_input_token_cost": 7.57e-07,
+        "output_cost_per_token": 6.05e-06,
+    },
+    "azure/us-gov/text-embedding-3-large": {"input_cost_per_token": 1.63e-07},
+    "azure/us-gov/text-embedding-3-small": {"input_cost_per_token": 2.5e-08},
+}
+
+
+@pytest.mark.parametrize("gov_key", AZURE_GOV_EXPECTED)
+def test_azure_usgov_pricing(model_data, gov_key):
+    """Azure Government meters from the Azure retail prices API
+    (usgovvirginia/usgovarizona, serviceName 'Foundry Models'). No Government
+    retirement schedule is published, so these entries carry no deprecation_date.
+    """
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    for field, expected in AZURE_GOV_EXPECTED[gov_key].items():
+        assert info[field] == expected, f"{gov_key}: {field} should be {expected} (got {info[field]})"
+    assert info["litellm_provider"] == "azure"
+    assert "deprecation_date" not in info
diff --git a/tests/test_litellm/test_circleci_rust_toolchain.py b/tests/test_litellm/test_circleci_rust_toolchain.py
index c35ced51e16..800ca21b95d 100644
--- a/tests/test_litellm/test_circleci_rust_toolchain.py
+++ b/tests/test_litellm/test_circleci_rust_toolchain.py
@@ -17,28 +17,27 @@ Two invariants are pinned here:
      Windows job, so the check accepts either. A new job that syncs without one
      falls back to the unpinned path, which is exactly the regression a static
      check catches at PR time and a green CI run does not.
-  2. `install_rust` itself pins what it downloads: an explicit rustup version in
-     the URL, a verified SHA-256, and an exact toolchain version rather than a
-     channel name.
-
-The Windows job predates `install_rust` and provisions its toolchain inline, so
-invariant 2 is scoped to `install_rust`; invariant 1 covers both.
+  2. Both installers pin what they download: an explicit rustup version, a
+     verified SHA-256, and the exact toolchain in `rust-toolchain.toml`.
 """
 
 from __future__ import annotations
 
 import re
 from pathlib import Path
+from typing import Final
 
 import pytest
 import yaml
 
 REPO_ROOT = Path(__file__).resolve().parents[2]
 CONFIG = REPO_ROOT / ".circleci" / "config.yml"
+TOOLCHAIN: Final = REPO_ROOT / "rust-toolchain.toml"
 
 BUILDS_WORKSPACE = re.compile(r"\buv\s+(?:sync|build)\b")
 RUSTUP_ARCHIVE_URL = re.compile(r"https://static\.rust-lang\.org/rustup/archive/\d+\.\d+\.\d+/")
-EXACT_TOOLCHAIN = re.compile(r"--default-toolchain\s+\"?\d+\.\d+\.\d+\"?")
+EXACT_TOOLCHAIN = re.compile(r"--default-toolchain\s+\"?(\d+\.\d+\.\d+)\"?")
+TOOLCHAIN_CHANNEL: Final = re.compile(r'^channel = "(\d+\.\d+\.\d+)"$', re.MULTILINE)
 
 
 def _config() -> dict[str, object]:
@@ -57,6 +56,12 @@ def _step_text(step: object) -> str:
     return ""
 
 
+def _pinned_toolchain() -> str:
+    match: Final = TOOLCHAIN_CHANNEL.search(TOOLCHAIN.read_text())
+    assert match is not None, "rust-toolchain.toml must pin an exact channel"
+    return match.group(1)
+
+
 def _without_comments(text: str) -> str:
     return "\n".join(line for line in text.splitlines() if not line.lstrip().startswith("#"))
 
@@ -142,7 +147,17 @@ def test_install_rust_verifies_the_installer_checksum(install_rust_command: str)
 
 
 def test_install_rust_pins_an_exact_toolchain_version(install_rust_command: str) -> None:
-    assert EXACT_TOOLCHAIN.search(install_rust_command), (
-        "install_rust must pin an exact toolchain version (e.g. 1.97.1); a channel name like "
+    match: Final = EXACT_TOOLCHAIN.search(install_rust_command)
+    assert match is not None, (
+        "install_rust must pin an exact toolchain version (e.g. 1.98.0); a channel name like "
         "stable/beta/nightly makes the compiler drift with whatever upstream published that day"
     )
+    assert match.group(1) == _pinned_toolchain()
+
+
+def test_windows_installer_matches_the_repo_toolchain() -> None:
+    windows_steps: Final = _step_lists()["job using_litellm_on_windows"]
+    windows_command: Final = "\n".join(_step_text(step) for step in windows_steps)
+    match: Final = EXACT_TOOLCHAIN.search(windows_command)
+    assert match is not None
+    assert match.group(1) == _pinned_toolchain()
diff --git a/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py b/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py
index 9ca4515239a..e33bcfb8378 100644
--- a/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py
+++ b/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py
@@ -75,6 +75,22 @@ def test_additional_current_models_are_present():
         assert entry["output_cost_per_token"] > 0
 
 
+@pytest.mark.parametrize(
+    "key, published_price_per_audio_minute",
+    [
+        ("cloudflare/@cf/openai/whisper", 0.00045),
+        ("cloudflare/@cf/openai/whisper-large-v3-turbo", 0.00051),
+    ],
+)
+def test_whisper_transcription_pricing_is_stored_per_second(key, published_price_per_audio_minute):
+    entry = litellm.model_cost[key]
+    assert entry["litellm_provider"] == "cloudflare"
+    assert entry["mode"] == "audio_transcription"
+    assert entry["supported_endpoints"] == ["/v1/audio/transcriptions"]
+    assert entry["output_cost_per_second"] == 0.0
+    assert entry["input_cost_per_second"] == pytest.approx(published_price_per_audio_minute / 60)
+
+
 def test_root_and_backup_have_identical_cloudflare_keys():
     if not os.path.exists(ROOT_MAP):
         pytest.skip("root cost map only ships in source checkouts")
diff --git a/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py b/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py
new file mode 100644
index 00000000000..44572aed08e
--- /dev/null
+++ b/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py
@@ -0,0 +1,56 @@
+"""
+Static checks that every proxy Docker image installs the `bedrock-realtime` extra.
+
+Bedrock Nova Sonic speech-to-speech (`/v1/realtime`) needs `aws-sdk-bedrock-runtime`,
+which only ships in the `bedrock-realtime` extra. An image whose `uv sync` stages
+omit the extra fails every Nova Sonic realtime session with
+"Missing aws_sdk_bedrock_runtime. Install with: pip install aws-sdk-bedrock-runtime".
+"""
+
+import os
+import re
+from typing import Final
+
+import pytest
+
+REPO_ROOT: Final = os.path.join(os.path.dirname(__file__), "..", "..")
+
+PROXY_DOCKERFILES: Final = (
+    "Dockerfile",
+    os.path.join("docker", "Dockerfile.non_root"),
+    os.path.join("docker", "Dockerfile.database"),
+    os.path.join("gateway", "Dockerfile"),
+)
+
+CONTINUED_LINE_RE: Final = re.compile(r"(?:\\\n|[^\n])+")
+UV_SYNC_BOUNDARY_RE: Final = re.compile(r"(?=uv sync)")
+
+
+def _uv_sync_invocations(dockerfile_text: str) -> tuple[str, ...]:
+    """Return each `uv sync ...` command, split apart when one RUN holds several (if/else branches)."""
+    return tuple(
+        part
+        for line in CONTINUED_LINE_RE.finditer(dockerfile_text)
+        for part in UV_SYNC_BOUNDARY_RE.split(line.group(0))
+        if part.startswith("uv sync")
+    )
+
+
+@pytest.mark.parametrize("relative_path", PROXY_DOCKERFILES)
+def test_every_uv_sync_installs_bedrock_realtime_extra(relative_path: str):
+    dockerfile_path: Final = os.path.join(REPO_ROOT, relative_path)
+    if not os.path.exists(dockerfile_path):
+        pytest.skip(f"{relative_path} not present in this checkout")
+
+    with open(dockerfile_path, "r", encoding="utf-8") as f:
+        contents: Final = f.read()
+
+    invocations: Final = _uv_sync_invocations(contents)
+    assert invocations, f"{relative_path} has no `uv sync` invocation"
+
+    missing: Final = tuple(invocation for invocation in invocations if "--extra bedrock-realtime" not in invocation)
+    assert not missing, (
+        f"{relative_path}: {len(missing)} of {len(invocations)} `uv sync` invocations omit "
+        "`--extra bedrock-realtime`, so aws-sdk-bedrock-runtime is absent and Bedrock Nova Sonic "
+        "/v1/realtime sessions fail with 'Missing aws_sdk_bedrock_runtime'"
+    )
diff --git a/tests/test_litellm/test_main.py b/tests/test_litellm/test_main.py
index 8cf878d05d9..7c2b9d0be05 100644
--- a/tests/test_litellm/test_main.py
+++ b/tests/test_litellm/test_main.py
@@ -3150,8 +3150,8 @@ def _stream_builder_logging_obj() -> LiteLLMLogging:
     return logging_obj
 
 
-def test_stream_chunk_builder_reports_streaming_usage_cost_when_enabled(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setattr(litellm, "include_cost_in_streaming_usage", True)
+def test_stream_chunk_builder_stamps_streaming_usage_cost_by_default(monkeypatch: pytest.MonkeyPatch):
+    monkeypatch.setattr(litellm, "include_cost_in_streaming_usage", False)
     chunks: Final = [
         _stream_builder_text_chunk("gpt-4o", "Hello "),
         _stream_builder_text_chunk("gpt-4o", "world.", finish_reason="stop"),
@@ -3168,11 +3168,45 @@ def test_stream_chunk_builder_reports_streaming_usage_cost_when_enabled(monkeypa
     assert response._hidden_params["response_cost"] == pytest.approx(usage_cost)
 
 
-def test_stream_chunk_builder_defers_cost_to_logging_obj_when_usage_cost_absent(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setattr(litellm, "include_cost_in_streaming_usage", False)
+def test_stream_chunk_builder_skips_stamp_when_cost_is_unpriceable():
+    import time as time_module
+
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
+
+    logging_obj: Final = LiteLLMLogging(
+        model="us.anthropic.claude-opus-5",
+        messages=[{"role": "user", "content": "hi"}],
+        stream=True,
+        call_type="completion",
+        start_time=time_module.time(),
+        litellm_call_id="stream-builder-alias-unpriceable",
+        function_id="1",
+    )
+    logging_obj.model_call_details["custom_llm_provider"] = "bedrock"
+    logging_obj.optional_params = {}
+    usage_chunk: Final = _stream_builder_text_chunk("bedrock-claude-opus-5", "")
+    usage_chunk.usage = Usage(prompt_tokens=40, completion_tokens=5, total_tokens=45)
+    chunks: Final = [
+        _stream_builder_text_chunk("bedrock-claude-opus-5", "Hello ", finish_reason="stop"),
+        usage_chunk,
+    ]
+
+    response: Final = litellm.stream_chunk_builder(
+        chunks=chunks, messages=[{"role": "user", "content": "hi"}], logging_obj=logging_obj
+    )
+
+    assert response is not None
+    assert getattr(response.usage, "cost", None) is None
+    assert response._hidden_params.get("response_cost") is None
+
+
+def test_stream_chunk_builder_keeps_provider_reported_usage_cost():
+    usage_chunk: Final = _stream_builder_text_chunk("gpt-4o", "")
+    usage_chunk.usage = Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15, cost=0.5)
     chunks: Final = [
         _stream_builder_text_chunk("gpt-4o", "Hello "),
         _stream_builder_text_chunk("gpt-4o", "world.", finish_reason="stop"),
+        usage_chunk,
     ]
 
     response: Final = litellm.stream_chunk_builder(
@@ -3180,4 +3214,26 @@ def test_stream_chunk_builder_defers_cost_to_logging_obj_when_usage_cost_absent(
     )
 
     assert response is not None
-    assert response._hidden_params.get("response_cost") is None
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.5)
+    assert response._hidden_params["response_cost"] == pytest.approx(0.5)
+
+
+def test_stream_chunk_builder_prices_alias_from_openai_sdk_usage_chunk():
+    from openai.types.completion_usage import CompletionUsage
+
+    usage_chunk: Final = _stream_builder_text_chunk("mantle-claude", "")
+    usage_chunk.usage = CompletionUsage(prompt_tokens=20, completion_tokens=60, total_tokens=80, cost=0.000704)
+    assert type(usage_chunk.usage) is CompletionUsage
+    chunks: Final = [
+        _stream_builder_text_chunk("mantle-claude", "Hello "),
+        _stream_builder_text_chunk("mantle-claude", "world.", finish_reason="stop"),
+        usage_chunk,
+    ]
+
+    response: Final = litellm.stream_chunk_builder(chunks=chunks, messages=[{"role": "user", "content": "hi"}])
+
+    assert response is not None
+    assert response.usage.prompt_tokens == 20
+    assert response.usage.completion_tokens == 60
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.000704)
+    assert response._hidden_params["response_cost"] == pytest.approx(0.000704)
diff --git a/tests/test_litellm/test_openai_service_tier_long_context_pricing.py b/tests/test_litellm/test_openai_service_tier_long_context_pricing.py
new file mode 100644
index 00000000000..c0860a5b55f
--- /dev/null
+++ b/tests/test_litellm/test_openai_service_tier_long_context_pricing.py
@@ -0,0 +1,156 @@
+import json
+from functools import lru_cache
+from pathlib import Path
+
+import pytest
+
+import litellm
+
+REPO_ROOT = Path(__file__).parents[2]
+MAIN_PATH = REPO_ROOT / "model_prices_and_context_window.json"
+BACKUP_PATH = REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json"
+
+FLEX_LONG_CONTEXT = {
+    "gpt-5.4": {
+        "input_cost_per_token_above_272k_tokens_flex": 2.5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 1.125e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07,
+    },
+    "gpt-5.4-pro": {
+        "input_cost_per_token_above_272k_tokens_flex": 3e-05,
+        "output_cost_per_token_above_272k_tokens_flex": 0.000135,
+    },
+    "gpt-5.5": {
+        "input_cost_per_token_above_272k_tokens_flex": 5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 2.25e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07,
+    },
+}
+
+PRIORITY_LONG_CONTEXT = {
+    "gpt-5.6": {
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
+    },
+    "gpt-5.6-sol": {
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
+    },
+    "gpt-5.6-terra": {
+        "input_cost_per_token_above_272k_tokens_priority": 8e-06,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-05,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-05,
+    },
+    "gpt-5.6-luna": {
+        "input_cost_per_token_above_272k_tokens_priority": 8e-07,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-06,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-06,
+    },
+}
+
+EXPECTED = {**FLEX_LONG_CONTEXT, **PRIORITY_LONG_CONTEXT}
+
+NO_PUBLISHED_PRIORITY_LONG_CONTEXT = ("gpt-5.4", "gpt-5.5")
+
+
+@pytest.fixture(autouse=True)
+def _local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+
+@lru_cache(maxsize=2)
+def _load(path: Path) -> dict[str, dict[str, object]]:
+    with open(path) as f:
+        return json.load(f)
+
+
+@pytest.mark.parametrize("path", [MAIN_PATH, BACKUP_PATH], ids=["main", "backup"])
+@pytest.mark.parametrize("model", sorted(EXPECTED))
+def test_service_tier_long_context_rates_are_published(model: str, path: Path) -> None:
+    """Each tier must carry its own above-272K rates, in both price files."""
+    info = _load(path).get(model)
+    assert info is not None, f"{model} not found in {path.name}"
+    for key, expected in EXPECTED[model].items():
+        assert info.get(key) == pytest.approx(expected), f"{model}.{key} is {info.get(key)!r}, expected {expected!r}"
+
+
+@pytest.mark.parametrize("model", sorted(EXPECTED))
+def test_tier_long_context_rate_is_half_or_double_the_standard(model: str) -> None:
+    """Flex is half the standard long-context rate; priority is double it."""
+    info = _load(MAIN_PATH)[model]
+    tier = "flex" if model in FLEX_LONG_CONTEXT else "priority"
+    ratio = 0.5 if tier == "flex" else 2.0
+    for base in ("input_cost_per_token", "output_cost_per_token"):
+        standard = info[f"{base}_above_272k_tokens"]
+        tiered = info[f"{base}_above_272k_tokens_{tier}"]
+        assert tiered == pytest.approx(standard * ratio), (
+            f"{model}.{base}_above_272k_tokens_{tier} is {tiered!r}, "
+            f"expected {ratio}x the standard long-context rate {standard!r}"
+        )
+
+
+@pytest.mark.parametrize("model", NO_PUBLISHED_PRIORITY_LONG_CONTEXT)
+def test_no_priority_long_context_rates_where_openai_publishes_none(model: str) -> None:
+    """Guard against back-filling a rate OpenAI does not publish."""
+    info = _load(MAIN_PATH)[model]
+    assert "input_cost_per_token_above_272k_tokens_priority" not in info
+
+
+LONG_CONTEXT_PROMPT_TOKENS = 300_000
+COMPLETION_TOKENS = 1_000
+
+TIERED_COST_CASES = [
+    ("gpt-5.4", "flex", 2.5e-06, 1.125e-05),
+    ("gpt-5.4-pro", "flex", 3e-05, 0.000135),
+    ("gpt-5.5", "flex", 5e-06, 2.25e-05),
+    ("gpt-5.6", "priority", 1.6e-05, 6e-05),
+    ("gpt-5.6-sol", "priority", 1.6e-05, 6e-05),
+    ("gpt-5.6-terra", "priority", 8e-06, 3.6e-05),
+    ("gpt-5.6-luna", "priority", 8e-07, 3.6e-06),
+]
+
+
+@pytest.mark.parametrize("model,tier,input_rate,output_rate", TIERED_COST_CASES)
+def test_cost_per_token_bills_long_context_at_the_tier_rate(
+    model: str, tier: str, input_rate: float, output_rate: float
+) -> None:
+    """A prompt over 272K on flex or priority must bill at that tier's long-context rate."""
+    input_cost, output_cost = litellm.cost_per_token(
+        model=model,
+        prompt_tokens=LONG_CONTEXT_PROMPT_TOKENS,
+        completion_tokens=COMPLETION_TOKENS,
+        service_tier=tier,
+    )
+    assert input_cost == pytest.approx(LONG_CONTEXT_PROMPT_TOKENS * input_rate)
+    assert output_cost == pytest.approx(COMPLETION_TOKENS * output_rate)
+
+
+@pytest.mark.parametrize("model,tier,input_rate,output_rate", TIERED_COST_CASES)
+def test_cost_per_token_tier_differs_from_the_standard_long_context_cost(
+    model: str, tier: str, input_rate: float, output_rate: float
+) -> None:
+    """Flex halves the standard long-context bill and priority doubles it."""
+    ratio = 0.5 if tier == "flex" else 2.0
+    standard = sum(
+        litellm.cost_per_token(
+            model=model,
+            prompt_tokens=LONG_CONTEXT_PROMPT_TOKENS,
+            completion_tokens=COMPLETION_TOKENS,
+        )
+    )
+    tiered = sum(
+        litellm.cost_per_token(
+            model=model,
+            prompt_tokens=LONG_CONTEXT_PROMPT_TOKENS,
+            completion_tokens=COMPLETION_TOKENS,
+            service_tier=tier,
+        )
+    )
+    assert tiered == pytest.approx(standard * ratio)
diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py
index 44c1cdbff06..ff5db18a3ea 100644
--- a/tests/test_litellm/test_router.py
+++ b/tests/test_litellm/test_router.py
@@ -7271,6 +7271,71 @@ def test_get_configured_token_limits_coerces_numeric_strings():
     assert router.get_configured_token_limits("quoted-limits-model") == (32000, 8000)
 
 
+def test_get_configured_display_name_reads_deployment_model_info():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "Kimi K3-claude-compatible",
+                "litellm_params": {"model": "openai/some-unmapped-model"},
+                "model_info": {"display_name": "Kimi K3"},
+            }
+        ]
+    )
+
+    assert router.get_configured_display_name("Kimi K3-claude-compatible") == "Kimi K3"
+
+
+def test_get_configured_display_name_returns_none_for_unset_or_unknown():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "no-display-model",
+                "litellm_params": {"model": "openai/some-unmapped-model"},
+            }
+        ]
+    )
+
+    assert router.get_configured_display_name("no-display-model") is None
+    assert router.get_configured_display_name("not-a-real-model") is None
+
+
+def test_get_configured_display_name_skips_wildcard_pattern_matching():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "bedrock/*",
+                "litellm_params": {"model": "bedrock/*"},
+                "model_info": {"display_name": "Bedrock"},
+            }
+        ]
+    )
+
+    with patch.object(
+        router.pattern_router, "route", side_effect=AssertionError("pattern route called")
+    ):
+        assert (
+            router.get_configured_display_name("bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0")
+            is None
+        )
+
+
+def test_get_configured_display_name_treats_malformed_values_as_absent():
+    malformed = ["", "   ", 12345, ["Kimi K3"], {"name": "Kimi K3"}, True]
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": f"bad-display-{i}",
+                "litellm_params": {"model": "openai/some-unmapped-model"},
+                "model_info": {"display_name": bad},
+            }
+            for i, bad in enumerate(malformed)
+        ]
+    )
+
+    for i in range(len(malformed)):
+        assert router.get_configured_display_name(f"bad-display-{i}") is None
+
+
 @pytest.mark.asyncio
 async def test_acreate_batch_disable_fallbacks_surfaces_owning_provider_error():
     router = litellm.Router(
@@ -7510,6 +7575,118 @@ async def test_acreate_batch_request_bedrock_tags_override_deployment_tags():
         assert mock_sign.call_args.kwargs["data"]["tags"] == request_tags
 
 
+@pytest.mark.asyncio
+async def test_avector_store_search_injects_router():
+    """
+    Regression: router.avector_store_search must pass the router down to the
+    SDK search call so provider transforms can resolve router-managed
+    embedding models (e.g. S3 Vectors query embeddings).
+    """
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    expected_response = VectorStoreSearchResponse(
+        object="vector_store.search_results.page", search_query="q", data=[]
+    )
+    mock_asearch = AsyncMock(return_value=expected_response)
+    # Router.__init__ binds asearch via a local import, so patch the module
+    # attribute before constructing the Router.
+    with patch("litellm.vector_stores.main.asearch", new=mock_asearch):  # test-quality-ok: the SDK call is the only place the injected router kwarg is observable
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "gpt-3.5-turbo",
+                    "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+                }
+            ]
+        )
+        search_response = await router.avector_store_search(
+            vector_store_id="v", query="q", custom_llm_provider="s3_vectors"
+        )
+
+    assert search_response is expected_response
+    mock_asearch.assert_awaited_once()
+    assert mock_asearch.await_args.kwargs["router"] is router
+
+
+@pytest.mark.asyncio
+async def test_avector_store_create_does_not_inject_router():
+    """The router injection is gated on the search call type: the create path
+    must keep calling the SDK without a router kwarg."""
+    expected_response = {"id": "vs_1", "object": "vector_store"}
+    mock_acreate = AsyncMock(return_value=expected_response)
+    # avector_store_create(model=None) resolves acreate via a local import at
+    # call time, so patching after Router construction works here.
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+            }
+        ]
+    )
+    with patch("litellm.vector_stores.main.acreate", new=mock_acreate):  # test-quality-ok: the SDK call is the only place a leaked router kwarg would surface
+        create_response = await router.avector_store_create(model=None, custom_llm_provider="openai")
+
+    assert create_response is expected_response
+    mock_acreate.assert_awaited_once()
+    assert "router" not in mock_acreate.await_args.kwargs
+
+
+def test_vector_store_search_injects_router():
+    """
+    Sync parity for the router injection: router.vector_store_search must pass
+    the router down to the SDK search call so provider transforms can resolve
+    router-managed embedding models, same as avector_store_search.
+    """
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    expected_response = VectorStoreSearchResponse(
+        object="vector_store.search_results.page", search_query="q", data=[]
+    )
+    mock_search = MagicMock(return_value=expected_response)
+    # Router.__init__ binds search via a local import, so patch the module
+    # attribute before constructing the Router.
+    with patch("litellm.vector_stores.main.search", new=mock_search):  # test-quality-ok: the SDK call is the only place the injected router kwarg is observable
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "gpt-3.5-turbo",
+                    "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+                }
+            ]
+        )
+        search_response = router.vector_store_search(
+            vector_store_id="v", query="q", custom_llm_provider="s3_vectors"
+        )
+
+    assert search_response is expected_response
+    mock_search.assert_called_once()
+    assert mock_search.call_args.kwargs["router"] is router
+    assert mock_search.call_args.kwargs["custom_llm_provider"] == "s3_vectors"
+
+
+def test_vector_store_create_does_not_inject_router():
+    """The sync create path must keep calling the SDK without a router kwarg."""
+    expected_response = {"id": "vs_1", "object": "vector_store"}
+    mock_create = MagicMock(return_value=expected_response)
+    # Router.__init__ binds create via a local import, so patch the module
+    # attribute before constructing the Router.
+    with patch("litellm.vector_stores.main.create", new=mock_create):  # test-quality-ok: the SDK call is the only place a leaked router kwarg would surface
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "gpt-3.5-turbo",
+                    "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+                }
+            ]
+        )
+        create_response = router.vector_store_create(custom_llm_provider="openai")
+
+    assert create_response is expected_response
+    mock_create.assert_called_once()
+    assert "router" not in mock_create.call_args.kwargs
+
+
 class TestPreRoutingStrategyRegistryLifecycle:
     """
     Regression tests: a deployment leaving the model_list must release the
@@ -11595,3 +11772,138 @@ class TestTierParamsTheTargetAccepts:
         accepted = router._tier_params_the_target_accepts("no-such-group", {"reasoning_effort": "max"}, {})
 
         assert accepted == {"reasoning_effort": "max"}
+
+
+class TestPreRoutingTierDrivesFallbacks:
+    """#38832: a complexity/auto router picks a tier behind the router name, but fallback
+    lookup stayed on the router name, so the tier's configured chain never ran and a
+    provider failure on the tier's first hop was returned to the client."""
+
+    class _TierRouter(litellm.Router):
+        async def async_pre_routing_hook(
+            self, model, request_kwargs, messages=None, input=None, specific_deployment=False
+        ):
+            from litellm.types.router import PreRoutingHookResponse
+
+            if model == "smart-router":
+                return PreRoutingHookResponse(model="tier1", messages=messages)
+            return None
+
+    @classmethod
+    def _router(cls, fallbacks) -> "litellm.Router":
+        return cls._TierRouter(
+            model_list=[
+                {
+                    "model_name": "smart-router",
+                    "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "sk-x"},
+                },
+                {
+                    "model_name": "tier1",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "litellm.RateLimitError",
+                    },
+                },
+                {
+                    "model_name": "backup-a",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "from backup-a",
+                    },
+                },
+                {
+                    "model_name": "backup-b",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "from backup-b",
+                    },
+                },
+                {
+                    "model_name": "failing-backup",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "litellm.RateLimitError",
+                    },
+                },
+                {
+                    "model_name": "plain",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "litellm.RateLimitError",
+                    },
+                },
+            ],
+            fallbacks=fallbacks,
+            num_retries=0,
+        )
+
+    @pytest.mark.asyncio
+    async def test_the_selected_tier_fallback_chain_runs(self):
+        router = self._router([{"tier1": ["backup-a"]}])
+
+        response = await router.acompletion(
+            model="smart-router", messages=[{"role": "user", "content": "hi"}]
+        )
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_a_chain_keyed_on_the_router_name_is_not_used(self):
+        """The router name has no chain of its own, so nothing should rescue this call."""
+        router = self._router([{"tier2": ["backup-a"]}])
+
+        with pytest.raises(litellm.RateLimitError):
+            await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+    @pytest.mark.asyncio
+    async def test_a_chain_keyed_on_the_router_name_rescues_when_no_tier_chain_exists(self):
+        """The documented contract: configs keyed on the requested name keep working behind auto-routers."""
+        router = self._router([{"smart-router": ["backup-a"]}])
+
+        response = await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_the_tier_chain_wins_over_the_router_name_chain(self):
+        router = self._router([{"tier1": ["backup-a"]}, {"smart-router": ["backup-b"]}])
+
+        response = await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_a_request_without_a_pre_routing_hook_still_uses_its_own_group(self):
+        router = self._router([{"tier1": ["backup-a"]}])
+
+        response = await router.acompletion(
+            model="tier1", messages=[{"role": "user", "content": "hi"}]
+        )
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_a_caller_cannot_pick_the_chain_by_sending_the_selection(self):
+        """The metadata bucket carries caller-supplied keys, so only the hook may set the tier."""
+        router = self._router([{"tier1": ["backup-a"]}])
+
+        with pytest.raises(litellm.RateLimitError):
+            await router.acompletion(
+                model="plain",
+                messages=[{"role": "user", "content": "hi"}],
+                metadata={"pre_routing_selected_model": "tier1"},
+            )
+
+    @pytest.mark.asyncio
+    async def test_each_fallback_hop_resolves_its_own_chain(self):
+        """The second hop must key off the group it is running, not the tier that failed."""
+        router = self._router([{"tier1": ["failing-backup"]}, {"failing-backup": ["backup-b"]}])
+
+        response = await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+        assert response.choices[0].message.content == "from backup-b"
diff --git a/tests/test_litellm/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py
index 7b7a962bf00..30b265905f3 100644
--- a/tests/test_litellm/test_router_model_cost_isolation.py
+++ b/tests/test_litellm/test_router_model_cost_isolation.py
@@ -2281,3 +2281,83 @@ def test_every_declaring_deployment_is_named(caplog):
     assert "azure-ptu-east" in warnings[0]
     assert "azure-ptu-west" in warnings[0]
     assert "plain-gpt-4o" not in warnings[0]
+
+
+def _simulate_price_data_reload_with_provider_sets(monkeypatch, fetched_catalog):
+    """Like `_simulate_price_data_reload`, plus the provider model-set refresh the proxy's
+    `_swap_in_model_cost_map` does before replaying, so bare names in the new catalog resolve."""
+    monkeypatch.setattr(litellm, "model_cost", fetched_catalog)
+    _invalidate_model_cost_lowercase_map()
+    litellm.add_known_models(model_cost_map=fetched_catalog)
+    reapply_runtime_model_cost_registrations()
+
+
+def test_a_config_deployment_dropped_by_a_stale_cost_map_comes_back_on_reload(monkeypatch):
+    """
+    Booting on the bundled backup, a bare model that only the remote catalog knows
+    cannot be provider-resolved, so the proxy router (ignore_invalid_deployments) drops
+    it. Once a reload brings in a catalog that knows the model, the deployment must be
+    served again with its access groups, and exactly once however many reloads follow.
+    """
+    backend = "lit-5766-only-in-remote-catalog"
+    try:
+        router = Router(
+            model_list=[
+                {
+                    "model_name": "new-model",
+                    "litellm_params": {"model": backend, "api_key": "k"},
+                    "model_info": {"id": "new-id", "access_groups": ["team-models"]},
+                },
+                {
+                    "model_name": "control-model",
+                    "litellm_params": {"model": "hosted_vllm/control-backend", "api_key": "k"},
+                    "model_info": {"id": "control-id", "access_groups": ["team-models"]},
+                },
+            ],
+            ignore_invalid_deployments=True,
+        )
+        assert router.get_model_names() == ["control-model"]
+        assert router.get_model_access_groups(model_name="new-model") == {}
+
+        fresh_catalog = {**litellm.model_cost, backend: {"litellm_provider": "openai", "mode": "chat"}}
+        _simulate_price_data_reload_with_provider_sets(monkeypatch, fresh_catalog)
+        _simulate_price_data_reload_with_provider_sets(monkeypatch, fresh_catalog)
+
+        assert sorted(router.get_model_names()) == ["control-model", "new-model"]
+        assert router.get_model_access_groups(model_name="new-model") == {"team-models": ["new-model"]}
+        assert [d["model_info"]["id"] for d in router.model_list] == ["control-id", "new-id"]
+        assert "new-id" in litellm.model_cost
+    finally:
+        litellm.open_ai_chat_completion_models.discard(backend)
+        litellm.models_by_provider["openai"].discard(backend)
+
+
+def test_a_config_deployment_dropped_for_a_permanent_reason_is_not_retried_on_reload(monkeypatch):
+    """
+    Only provider-resolution drops can be healed by a fresh catalog. A deployment that
+    fails after its provider resolved (here a pass-through vertex entry with no project)
+    has already touched router state, so replaying it on every reload would leak into
+    `deployment_names` each time.
+    """
+    router = Router(
+        model_list=[
+            {
+                "model_name": "vertex-passthrough",
+                "litellm_params": {"model": "vertex_ai/gemini-2.5-flash", "use_in_pass_through": True},
+                "model_info": {"id": "vertex-id"},
+            },
+            {
+                "model_name": "control-model",
+                "litellm_params": {"model": "hosted_vllm/control-backend", "api_key": "k"},
+                "model_info": {"id": "control-id"},
+            },
+        ],
+        ignore_invalid_deployments=True,
+    )
+    assert router.get_model_names() == ["control-model"]
+    names_after_boot = list(router.deployment_names)
+
+    _simulate_price_data_reload_with_provider_sets(monkeypatch, dict(litellm.model_cost))
+
+    assert router.get_model_names() == ["control-model"]
+    assert router.deployment_names == names_after_boot
diff --git a/tests/test_litellm/test_router_retry_policy_update.py b/tests/test_litellm/test_router_retry_policy_update.py
index 1b98b8c1ae8..be568134763 100644
--- a/tests/test_litellm/test_router_retry_policy_update.py
+++ b/tests/test_litellm/test_router_retry_policy_update.py
@@ -21,6 +21,7 @@ This file pins both halves of the fix.
 
 import json
 from dataclasses import dataclass
+from typing import Final
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -28,8 +29,19 @@ from pydantic import ValidationError
 
 
 import litellm
+from litellm.router_strategy.budget_limiter import RouterBudgetLimiting
+from litellm.router_utils.pre_call_checks.model_rate_limit_check import ModelRateLimitingCheck
+from litellm.router_utils.pre_call_checks.prompt_caching_deployment_check import PromptCachingDeploymentCheck
 from litellm.types.router import RetryPolicy, UpdateRouterConfig
 
+
+@pytest.fixture(autouse=True)
+def isolate_litellm_callbacks():
+    callbacks_before: Final = litellm.callbacks.copy()
+    yield
+    litellm.callbacks = callbacks_before  # test-quality-ok: required callback-state restoration fixture
+
+
 # ---------------------------------------------------------------------------
 # UpdateRouterConfig schema membership (LIT-3152 part 1)
 # ---------------------------------------------------------------------------
@@ -100,6 +112,114 @@ def _build_router() -> litellm.Router:
     )
 
 
+def test_update_settings_adds_optional_pre_call_check_once():
+    router = _build_router()
+
+    router.update_settings(num_retries=7, optional_pre_call_checks=["prompt_caching"])
+    router.update_settings(optional_pre_call_checks=["prompt_caching"])
+
+    prompt_caching_callbacks = [
+        callback for callback in router.optional_callbacks if isinstance(callback, PromptCachingDeploymentCheck)
+    ]
+    assert len(prompt_caching_callbacks) == 1
+    assert router.num_retries == 7
+
+
+def test_update_settings_clears_omitted_toggleable_pre_call_checks():
+    router = _build_router()
+
+    router.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router.update_settings(optional_pre_call_checks=[])
+
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in (router.optional_callbacks or []))
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in litellm.callbacks)
+
+
+def test_set_optional_pre_call_checks_reconciles_callback_types():
+    router = _build_router()
+
+    router.set_optional_pre_call_checks(["prompt_caching"])
+    router.set_optional_pre_call_checks([])
+
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in (router.optional_callbacks or []))
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in litellm.callbacks)
+
+
+def test_remove_optional_pre_call_check_removes_local_and_global_callbacks():
+    router = _build_router()
+
+    router.set_optional_pre_call_checks(["prompt_caching"])
+    router._remove_optional_callbacks_of_type(PromptCachingDeploymentCheck)
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router.optional_callbacks or []))
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+
+def test_remove_optional_pre_call_check_keeps_global_callback_for_another_router():
+    router_a = _build_router()
+    router_b = _build_router()
+
+    router_a.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router_b.update_settings(optional_pre_call_checks=["prompt_caching"])
+
+    router_a.update_settings(optional_pre_call_checks=[])
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router_a.optional_callbacks or []))
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in (router_b.optional_callbacks or []))
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+    router_b.update_settings(optional_pre_call_checks=[])
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router_b.optional_callbacks or []))
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+
+def test_remove_optional_pre_call_check_keeps_global_callback_when_second_router_clears_first():
+    router_a = _build_router()
+    router_b = _build_router()
+
+    router_a.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router_b.update_settings(optional_pre_call_checks=["prompt_caching"])
+
+    router_b.update_settings(optional_pre_call_checks=[])
+
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in (router_a.optional_callbacks or []))
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router_b.optional_callbacks or []))
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+    router_a.update_settings(optional_pre_call_checks=[])
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+
+def test_update_settings_replaces_toggleable_pre_call_checks():
+    router = _build_router()
+
+    router.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router.update_settings(optional_pre_call_checks=["enforce_model_rate_limits"])
+
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in (router.optional_callbacks or []))
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in litellm.callbacks)
+    assert any(isinstance(callback, ModelRateLimitingCheck) for callback in (router.optional_callbacks or []))
+
+
+@pytest.mark.asyncio
+async def test_update_settings_preserves_router_budget_limiting_when_omitted(monkeypatch):
+    async def _disable_periodic_sync(*args, **kwargs):
+        return None
+
+    monkeypatch.setattr(
+        "litellm.router_strategy.budget_limiter.RouterBudgetLimiting.periodic_sync_in_memory_spend_with_redis",
+        _disable_periodic_sync,
+    )
+    router = _build_router()
+
+    router.add_optional_pre_call_checks(["router_budget_limiting"])
+    router.update_settings(optional_pre_call_checks=[])
+
+    assert any(isinstance(callback, RouterBudgetLimiting) for callback in (router.optional_callbacks or []))
+
+
 def test_update_settings_persists_retry_policy_dict():
     """When the proxy's ``_add_router_settings_from_db_config`` calls
     ``llm_router.update_settings(retry_policy={...})`` after reading the
@@ -255,8 +375,12 @@ async def test_config_update_persists_and_reads_back_retry_policy(monkeypatch):
             RateLimitErrorRetries=7,
         )
     )
+    request = MagicMock()
+    request.json = AsyncMock(return_value={"router_settings": {"retry_policy": posted.model_dump()}})
+
     await proxy_server.update_config(
         config_info=ConfigYAML(router_settings=posted),
+        request=request,
         user_api_key_dict=UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234"),
     )
 
diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py
index 521e91daded..0790b41c349 100644
--- a/tests/test_litellm/test_utils.py
+++ b/tests/test_litellm/test_utils.py
@@ -4655,6 +4655,7 @@ GEMINI_4096_CACHE_MIN_MODELS: Final = tuple(
         "gemini-3.5-flash",
         "gemini-3.6-flash",
         "gemini-3.7-flash",
+        "gemini-3.8-flash",
         "gemini-3.1-pro-preview",
         "gemini-3.1-pro-preview-customtools",
     )
diff --git a/tests/test_litellm/vector_stores/__init__.py b/tests/test_litellm/vector_stores/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/vector_stores/test_main.py b/tests/test_litellm/vector_stores/test_main.py
new file mode 100644
index 00000000000..d01e696906a
--- /dev/null
+++ b/tests/test_litellm/vector_stores/test_main.py
@@ -0,0 +1,78 @@
+"""
+Tests for litellm/vector_stores/main.py.
+
+Pins the router threading contract for vector store search: the router is an
+explicit named parameter that reaches the HTTP handler, and it must never leak
+into litellm_params/kwargs where logging would model_dump() it (the #19550
+serialization trap).
+"""
+
+from unittest.mock import MagicMock, patch
+
+import litellm.vector_stores.main as vector_stores_main
+from litellm.vector_stores.main import search
+
+MOCK_SEARCH_RESPONSE = {
+    "object": "vector_store.search_results.page",
+    "search_query": "q",
+    "data": [],
+}
+
+
+def test_search_threads_router_to_handler():
+    """search() must pass its router param through to the HTTP handler"""
+    mock_router = MagicMock()
+    logger = MagicMock()
+
+    with (
+        patch(  # test-quality-ok: stubs provider config resolution; the seam under test is the router kwarg threading
+            "litellm.vector_stores.main.ProviderConfigManager.get_provider_vector_stores_config",
+            return_value=MagicMock(),
+        ),
+        patch.object(  # test-quality-ok: the handler call is the observable boundary for the router kwarg contract
+            vector_stores_main.base_llm_http_handler,
+            "vector_store_search_handler",
+            return_value=MOCK_SEARCH_RESPONSE,
+        ) as mock_handler,
+    ):
+        response = search(
+            vector_store_id="bkt:idx",
+            query="q",
+            custom_llm_provider="s3_vectors",
+            router=mock_router,
+            litellm_logging_obj=logger,
+        )
+
+    assert response == MOCK_SEARCH_RESPONSE
+    mock_handler.assert_called_once()
+    assert mock_handler.call_args.kwargs["router"] is mock_router
+
+
+def test_search_router_not_in_litellm_params():
+    """Regression (#19550 class): the router must stay out of GenericLiteLLMParams,
+    otherwise pre-call logging model_dump()s it and breaks serialization."""
+    mock_router = MagicMock()
+    logger = MagicMock()
+
+    with (
+        patch(  # test-quality-ok: stubs provider config resolution; the seam under test is litellm_params contents
+            "litellm.vector_stores.main.ProviderConfigManager.get_provider_vector_stores_config",
+            return_value=MagicMock(),
+        ),
+        patch.object(  # test-quality-ok: the handler call is where a leaked router in litellm_params would surface
+            vector_stores_main.base_llm_http_handler,
+            "vector_store_search_handler",
+            return_value=MOCK_SEARCH_RESPONSE,
+        ) as mock_handler,
+    ):
+        search(
+            vector_store_id="bkt:idx",
+            query="q",
+            custom_llm_provider="s3_vectors",
+            router=mock_router,
+            litellm_logging_obj=logger,
+        )
+
+    litellm_params = mock_handler.call_args.kwargs["litellm_params"]
+    assert "router" not in litellm_params.model_dump(exclude_none=True)
+    assert getattr(litellm_params, "router", None) is None
diff --git a/type-discipline-budget.json b/type-discipline-budget.json
index 3d2e97d55a5..52cb9628252 100644
--- a/type-discipline-budget.json
+++ b/type-discipline-budget.json
@@ -1,6 +1,6 @@
 {
   "LIT001": {
-    "limit": 22367
+    "limit": 22364
   },
   "LIT002": {
     "limit": 26777
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx
index 79bd2f6a21b..de1eb153f6f 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx
@@ -75,6 +75,40 @@ const langgraphInfo: AgentCreateInfo = {
   ],
 };
 
+const FULL_RUNTIME_ARN = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime/hosted_agent_4vm3i-BaTdfOELAs";
+
+const BEDROCK_AGENTCORE_AGENT = {
+  agent_id: "agent-3",
+  agent_name: "bedrock-agent",
+  agent_card_params: { name: "bedrock-agent", description: "agentcore agent", url: "", version: "1.0.0", skills: [] },
+  litellm_params: {
+    custom_llm_provider: "bedrock",
+    model: `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+  },
+};
+
+const bedrockAgentcoreInfo: AgentCreateInfo = {
+  agent_type: "bedrock_agentcore",
+  agent_type_display_name: "Bedrock AgentCore",
+  description: "Bedrock AgentCore runtimes",
+  logo_url: "/b.png",
+  use_a2a_form_fields: false,
+  litellm_params_template: { custom_llm_provider: "bedrock" },
+  model_template: "bedrock/agentcore/{agent_runtime_arn}",
+  credential_fields: [
+    {
+      key: "agent_runtime_arn",
+      label: "Agent Runtime ARN",
+      field_type: "text",
+      required: true,
+      include_in_litellm_params: false,
+      validation_pattern: "^arn:aws[a-zA-Z0-9-]*:bedrock-agentcore:[a-z0-9-]+:[0-9]{12}:runtime/.+$",
+      validation_message:
+        'Enter the complete Bedrock AgentCore runtime ARN, including the runtime ID after "runtime/".',
+    },
+  ],
+};
+
 const setup = () => userEvent.setup({ pointerEventsCheck: PointerEventsCheckLevel.Never });
 
 const renderView = () => render(<AgentInfoView agentId="agent-1" onClose={vi.fn()} accessToken="tok" isAdmin={true} />);
@@ -247,6 +281,69 @@ describe("AgentInfoView update payload", () => {
     });
   });
 
+  it("preserves the full AgentCore runtime ARN (including the resource id after runtime/) across an unedited save", async () => {
+    vi.mocked(networking.getAgentCreateMetadata).mockResolvedValue([bedrockAgentcoreInfo]);
+    vi.mocked(networking.getAgentInfo).mockResolvedValue(BEDROCK_AGENTCORE_AGENT as never);
+    const user = setup();
+    renderView();
+    await openEditor(user);
+
+    expect(await screen.findByLabelText("Agent Runtime ARN")).toHaveValue(FULL_RUNTIME_ARN);
+
+    await save(user);
+
+    expect((patchedPayload().litellm_params as Record<string, unknown>).model).toBe(
+      `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+    );
+  });
+
+  it("blocks the save and shows a validation error when the Agent Runtime ARN is truncated", async () => {
+    vi.mocked(networking.getAgentCreateMetadata).mockResolvedValue([bedrockAgentcoreInfo]);
+    vi.mocked(networking.getAgentInfo).mockResolvedValue(BEDROCK_AGENTCORE_AGENT as never);
+    const user = setup();
+    renderView();
+    await openEditor(user);
+
+    const arnField = await screen.findByLabelText("Agent Runtime ARN");
+    await user.clear(arnField);
+    fireEvent.change(arnField, {
+      target: { value: "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime" },
+    });
+    await user.click(screen.getByRole("button", { name: "Save Changes" }));
+
+    expect(
+      await screen.findByText(
+        'Enter the complete Bedrock AgentCore runtime ARN, including the runtime ID after "runtime/".',
+      ),
+    ).toBeInTheDocument();
+    expect(networking.patchAgentCall).not.toHaveBeenCalled();
+  });
+
+  it("renders and saves normally when a field's validation_pattern is not a valid regex", async () => {
+    const infoWithBadPattern: AgentCreateInfo = {
+      ...bedrockAgentcoreInfo,
+      credential_fields: [
+        {
+          ...bedrockAgentcoreInfo.credential_fields[0],
+          validation_pattern: "(unterminated",
+        },
+      ],
+    };
+    vi.mocked(networking.getAgentCreateMetadata).mockResolvedValue([infoWithBadPattern]);
+    vi.mocked(networking.getAgentInfo).mockResolvedValue(BEDROCK_AGENTCORE_AGENT as never);
+    const user = setup();
+    renderView();
+    await openEditor(user);
+
+    expect(await screen.findByLabelText("Agent Runtime ARN")).toHaveValue(FULL_RUNTIME_ARN);
+
+    await save(user);
+
+    expect((patchedPayload().litellm_params as Record<string, unknown>).model).toBe(
+      `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+    );
+  });
+
   it("reloads the agent and leaves edit mode when the edit is cancelled", async () => {
     const user = setup();
     renderView();
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.test.ts
new file mode 100644
index 00000000000..0c2d2500776
--- /dev/null
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.test.ts
@@ -0,0 +1,73 @@
+import { describe, it, expect } from "vitest";
+import { detectAgentType, extractModelTemplateValues, parseDynamicAgentForForm } from "./agent_type_utils";
+import type { AgentCreateInfo } from "@/components/networking";
+import type { Agent } from "@/components/agents/types";
+
+const FULL_RUNTIME_ARN = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime/hosted_agent_4vm3i-BaTdfOELAs";
+
+const bedrockAgentcoreInfo: AgentCreateInfo = {
+  agent_type: "bedrock_agentcore",
+  agent_type_display_name: "Bedrock AgentCore",
+  model_template: "bedrock/agentcore/{agent_runtime_arn}",
+  credential_fields: [
+    {
+      key: "agent_runtime_arn",
+      label: "Agent Runtime ARN",
+      required: true,
+      include_in_litellm_params: false,
+    },
+  ],
+};
+
+describe("extractModelTemplateValues", () => {
+  it("recovers a placeholder value that itself contains '/' (an AWS ARN resource path)", () => {
+    const values = extractModelTemplateValues(
+      "bedrock/agentcore/{agent_runtime_arn}",
+      `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+    );
+
+    expect(values.agent_runtime_arn).toBe(FULL_RUNTIME_ARN);
+  });
+
+  it("recovers a placeholder value with no '/' (single path segment)", () => {
+    const values = extractModelTemplateValues("langgraph/{assistant_id}", "langgraph/asst_1");
+
+    expect(values.assistant_id).toBe("asst_1");
+  });
+
+  it("returns no match when the model does not fit the template", () => {
+    const values = extractModelTemplateValues("langgraph/{assistant_id}", "azure_ai/agents/asst_1");
+
+    expect(values).toEqual({});
+  });
+});
+
+describe("parseDynamicAgentForForm", () => {
+  it("preserves the full runtime ARN, including the resource id after 'runtime/', when populating the edit form", () => {
+    const agent = {
+      agent_id: "agent-1",
+      agent_name: "bedrock-agent",
+      agent_card_params: { description: "" },
+      litellm_params: {
+        custom_llm_provider: "bedrock",
+        model: `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+      },
+    } as unknown as Agent;
+
+    const values = parseDynamicAgentForForm(agent, bedrockAgentcoreInfo);
+
+    expect(values.agent_runtime_arn).toBe(FULL_RUNTIME_ARN);
+  });
+});
+
+describe("detectAgentType", () => {
+  it("detects bedrock_agentcore agents from the model prefix", () => {
+    const agent = {
+      agent_id: "agent-1",
+      agent_name: "bedrock-agent",
+      litellm_params: { model: `bedrock/agentcore/${FULL_RUNTIME_ARN}` },
+    } as unknown as Agent;
+
+    expect(detectAgentType(agent)).toBe("bedrock_agentcore");
+  });
+});
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts
index f91590c5732..506f355c519 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts
@@ -25,6 +25,29 @@ export const detectAgentType = (agent: Agent): string => {
   return "a2a";
 };
 
+const escapeRegExp = (segment: string): string => segment.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
+
+/**
+ * Reverses a `model_template` (e.g. "bedrock/agentcore/{agent_runtime_arn}") against a stored
+ * `model` string to recover the placeholder values that produced it. Builds a regex from the
+ * template's literal segments rather than matching by split("/") position, because a
+ * placeholder's value can itself contain "/" (an AWS ARN's "runtime/<runtime-id>" resource path,
+ * a Vertex AI reasoning engine's "projects/.../reasoningEngines/..." resource id) and would
+ * otherwise be cut off at the first one.
+ */
+export const extractModelTemplateValues = (template: string, model: string): Record<string, string> => {
+  // Splitting on a regex with a capturing group interleaves the captured placeholder
+  // names between the surrounding literal segments, e.g. "a/{x}/b" -> ["a/", "x", "/b"].
+  const parts = template.split(/\{([a-zA-Z0-9_]+)\}/g);
+  const fieldNames = parts.filter((_part, index) => index % 2 === 1);
+  const pattern = parts.map((part, index) => (index % 2 === 1 ? "(.+)" : escapeRegExp(part))).join("");
+
+  const match = model.match(new RegExp(`^${pattern}$`));
+  if (!match) return {};
+
+  return Object.fromEntries(fieldNames.map((name, index) => [name, match[index + 1]]));
+};
+
 /**
  * Parses agent data for dynamic form fields (non-A2A agents).
  * Extracts values from litellm_params based on the agent type metadata.
@@ -35,24 +58,18 @@ export const parseDynamicAgentForForm = (agent: Agent, agentTypeInfo: AgentCreat
     description: agent.agent_card_params?.description || "",
   };
 
+  const templateValues =
+    agentTypeInfo.model_template && agent.litellm_params?.model
+      ? extractModelTemplateValues(agentTypeInfo.model_template, agent.litellm_params.model)
+      : {};
+
   // Extract credential field values from litellm_params
   for (const field of agentTypeInfo.credential_fields) {
     if (field.include_in_litellm_params !== false) {
       values[field.key] = agent.litellm_params?.[field.key] || field.default_value || "";
-    } else {
-      // For fields not in litellm_params (like agent_id), try to extract from model string
-      if (agentTypeInfo.model_template && agent.litellm_params?.model) {
-        const model = agent.litellm_params.model;
-        const templateParts = agentTypeInfo.model_template.split("/");
-        const modelParts = model.split("/");
-
-        // Find the placeholder position and extract the value
-        templateParts.forEach((part, index) => {
-          if (part === `{${field.key}}` && modelParts[index]) {
-            values[field.key] = modelParts[index];
-          }
-        });
-      }
+    } else if (templateValues[field.key] !== undefined) {
+      // For fields not in litellm_params (like agent_runtime_arn), recover from the model string
+      values[field.key] = templateValues[field.key];
     }
   }
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx
index 04a8b0df9d9..0f3355fe073 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx
@@ -24,58 +24,80 @@ interface DynamicAgentFormFieldsProps {
 export const unmountedDynamicFieldNames = (mountedPanels: readonly string[]): readonly string[] =>
   mountedPanels.includes(AGENT_FORM_CONFIG.cost.key) ? [] : COST_FIELD_NAMES;
 
-const CredentialField = ({ field }: { field: AgentCredentialFieldMetadata }) => (
-  <AgentFormField
-    name={field.key}
-    label={field.tooltip ? labelWithHint(field.label, field.tooltip) : field.label}
-    defaultValue={field.default_value ?? undefined}
-    rules={field.required ? { required: `Please enter ${field.label}` } : undefined}
-  >
-    {({ value, onChange, ref, ...control }) => {
-      const text = typeof value === "string" ? value : "";
-      if (field.field_type === "password") {
-        return (
-          <PasswordInput
-            {...control}
-            value={typeof value === "string" ? value : ""}
-            onChange={onChange}
-            ref={ref}
-            placeholder={field.placeholder || ""}
-          />
-        );
-      }
-      if (field.field_type === "textarea") {
-        return (
-          <Textarea
-            {...control}
-            ref={ref}
-            rows={3}
-            placeholder={field.placeholder || ""}
-            value={text}
-            onChange={onChange}
-          />
-        );
-      }
-      if (field.field_type === "select" && field.options) {
-        return (
-          <Select value={text || null} onValueChange={onChange}>
-            <SelectTrigger {...control} className="w-full">
-              <SelectValue placeholder={field.placeholder || ""} />
-            </SelectTrigger>
-            <SelectContent>
-              {field.options.map((option) => (
-                <SelectItem key={option} value={option} title={option}>
-                  {option}
-                </SelectItem>
-              ))}
-            </SelectContent>
-          </Select>
-        );
-      }
-      return <Input {...control} ref={ref} placeholder={field.placeholder || ""} value={text} onChange={onChange} />;
-    }}
-  </AgentFormField>
-);
+// A field's validation_pattern is server-supplied metadata; if it's ever not a valid regex, skip
+// validation rather than throwing during render and taking the whole form down with it.
+const buildValidationPatternRule = (
+  field: AgentCredentialFieldMetadata,
+): { value: RegExp; message: string } | undefined => {
+  if (!field.validation_pattern) return undefined;
+  try {
+    return {
+      value: new RegExp(field.validation_pattern),
+      message: field.validation_message || `${field.label} looks incomplete or malformed`,
+    };
+  } catch {
+    return undefined;
+  }
+};
+
+const CredentialField = ({ field }: { field: AgentCredentialFieldMetadata }) => {
+  const patternRule = buildValidationPatternRule(field);
+  return (
+    <AgentFormField
+      name={field.key}
+      label={field.tooltip ? labelWithHint(field.label, field.tooltip) : field.label}
+      defaultValue={field.default_value ?? undefined}
+      rules={{
+        ...(field.required ? { required: `Please enter ${field.label}` } : {}),
+        ...(patternRule ? { pattern: patternRule } : {}),
+      }}
+    >
+      {({ value, onChange, ref, ...control }) => {
+        const text = typeof value === "string" ? value : "";
+        if (field.field_type === "password") {
+          return (
+            <PasswordInput
+              {...control}
+              value={typeof value === "string" ? value : ""}
+              onChange={onChange}
+              ref={ref}
+              placeholder={field.placeholder || ""}
+            />
+          );
+        }
+        if (field.field_type === "textarea") {
+          return (
+            <Textarea
+              {...control}
+              ref={ref}
+              rows={3}
+              placeholder={field.placeholder || ""}
+              value={text}
+              onChange={onChange}
+            />
+          );
+        }
+        if (field.field_type === "select" && field.options) {
+          return (
+            <Select value={text || null} onValueChange={onChange}>
+              <SelectTrigger {...control} className="w-full">
+                <SelectValue placeholder={field.placeholder || ""} />
+              </SelectTrigger>
+              <SelectContent>
+                {field.options.map((option) => (
+                  <SelectItem key={option} value={option} title={option}>
+                    {option}
+                  </SelectItem>
+                ))}
+              </SelectContent>
+            </Select>
+          );
+        }
+        return <Input {...control} ref={ref} placeholder={field.placeholder || ""} value={text} onChange={onChange} />;
+      }}
+    </AgentFormField>
+  );
+};
 
 const DynamicAgentFormFields: React.FC<DynamicAgentFormFieldsProps> = ({ agentTypeInfo, panels }) => (
   <>
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx
index 1199b66621f..84a05113177 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx
@@ -111,17 +111,17 @@ describe("ModelsAndEndpointsPage", () => {
   // POST /model/new 403s a proxy_admin_viewer, so the form's tab must not render for one.
   it("hides the Add Model tab for a view-only admin session", () => {
     mockUseAuthorized.mockReturnValue(VIEW_ONLY_ADMIN);
-    const { getByRole, queryByRole } = renderPage();
-    expect(queryByRole("tab", { name: "Add Model" })).not.toBeInTheDocument();
-    expect(getByRole("tab", { name: "All Models" })).toBeInTheDocument();
+    renderPage();
+    expect(screen.queryByRole("tab", { name: "Add Model" })).not.toBeInTheDocument();
+    expect(screen.getByRole("tab", { name: "All Models" })).toBeInTheDocument();
   });
 
   // Read parity: the Auto-Routers list stays reachable for a view-only admin; only the
   // create affordance inside it is withheld, which AutoRoutersTabPanel decides.
   it("keeps the Auto-Routers tab for a view-only admin session", () => {
     mockUseAuthorized.mockReturnValue(VIEW_ONLY_ADMIN);
-    const { getByRole } = renderPage();
-    expect(getByRole("tab", { name: /Auto-Routers/ })).toBeInTheDocument();
+    renderPage();
+    expect(screen.getByRole("tab", { name: /Auto-Routers/ })).toBeInTheDocument();
   });
 
   // Auto-routers are excluded from the All Models table, so this tab is their home: the only
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx
index 34643811e29..4203a3dbf70 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx
@@ -116,16 +116,33 @@ describe("VectorStoreTester", () => {
     await waitFor(() => expect(mockSearch).toHaveBeenCalledTimes(1));
   });
 
-  it("reports a failed search and keeps the history empty", async () => {
+  it("shows the backend error in the history when a search fails", async () => {
     const user = userEvent.setup();
-    mockSearch.mockRejectedValue(new Error("boom"));
+    const errorBody = '{"error":{"message":"OpenAIException - api_key is required"}}';
+    mockSearch.mockRejectedValue(new Error(errorBody));
     renderTester();
 
     await user.type(queryInput(), "hello");
     await user.click(searchButton());
 
-    await waitFor(() => expect(mockFromBackend).toHaveBeenCalledWith("Failed to search vector store"));
-    expect(screen.getByText(EMPTY_STATE)).toBeInTheDocument();
+    await waitFor(() => expect(mockFromBackend).toHaveBeenCalledWith(errorBody));
+    expect(screen.getByText(`Search failed: ${errorBody}`)).toBeInTheDocument();
+    expect(screen.queryByText("No results found")).not.toBeInTheDocument();
+    expect(screen.queryByText(EMPTY_STATE)).not.toBeInTheDocument();
+    // the failed query stays in the input for retry
+    expect(queryInput()).toHaveValue("hello");
+  });
+
+  it('renders "No results found" for an empty result set, not an error', async () => {
+    const user = userEvent.setup();
+    mockSearch.mockResolvedValue({ object: "vector_store.search_results.page", search_query: "hello", data: [] });
+    renderTester();
+
+    await user.type(queryInput(), "hello");
+    await user.click(searchButton());
+
+    expect(await screen.findByText("No results found")).toBeInTheDocument();
+    expect(screen.queryByText(/search failed/i)).not.toBeInTheDocument();
   });
 
   it("clears the search history", async () => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx
index 6d12880319b..a9c4e0d1061 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx
@@ -40,6 +40,7 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
     {
       query: string;
       response: VectorStoreSearchResponse | null;
+      error: string | null;
       timestamp: number;
     }[]
   >([]);
@@ -59,6 +60,7 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
       const historyEntry = {
         query,
         response,
+        error: null,
         timestamp: Date.now(),
       };
 
@@ -66,7 +68,9 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
       setQuery("");
     } catch (error) {
       console.error("Error searching vector store:", error);
-      toast.fromError("Failed to search vector store");
+      const errorMessage = error instanceof Error ? error.message : String(error);
+      toast.fromError(errorMessage);
+      setSearchHistory((prev) => [{ query, response: null, error: errorMessage, timestamp: Date.now() }, ...prev]);
     } finally {
       setIsLoading(false);
     }
@@ -228,7 +232,13 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
                           })}
                         </div>
                       ) : (
-                        <div className="text-sm text-muted-foreground">No results found</div>
+                        <div
+                          className={
+                            entry.error ? "text-sm break-words text-destructive" : "text-sm text-muted-foreground"
+                          }
+                        >
+                          {entry.error ? `Search failed: ${entry.error}` : "No results found"}
+                        </div>
                       )}
                     </div>
                   </div>
diff --git a/ui/litellm-dashboard/src/autorouter_presets.json b/ui/litellm-dashboard/src/autorouter_presets.json
index b977bd484ac..1e0d40567d7 100644
--- a/ui/litellm-dashboard/src/autorouter_presets.json
+++ b/ui/litellm-dashboard/src/autorouter_presets.json
@@ -68,13 +68,16 @@
   },
   "openai_family": {
     "label": "OpenAI Family",
-    "description": "Routes across the GPT model family: gpt-5.4-nano for simple queries, gpt-5.4-mini for medium, gpt-5.4 for complex, o3 for reasoning-heavy requests.",
+    "description": "Routes across the GPT model family: Luna for simple queries, Terra for medium, Sol for complex, Sol at xhigh thinking for reasoning.",
     "complexity_router_config": {
       "tiers": {
-        "SIMPLE": ["gpt-5.4-nano"],
-        "MEDIUM": ["gpt-5.4-mini"],
-        "COMPLEX": ["gpt-5.4"],
-        "REASONING": ["o3"]
+        "SIMPLE": ["gpt-5.6-luna"],
+        "MEDIUM": ["gpt-5.6-terra"],
+        "COMPLEX": ["gpt-5.6-sol"],
+        "REASONING": ["gpt-5.6-sol"]
+      },
+      "tier_model_configs": {
+        "REASONING": [{ "model_name": "gpt-5.6-sol", "litellm_params": { "reasoning_effort": "xhigh" } }]
       },
       "classifier_type": "heuristic",
       "escalation_keywords": ["LITELLM ESCALATE"],
diff --git a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx
index d8a955b719c..ba380662403 100644
--- a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx
@@ -101,18 +101,24 @@ vi.mock("./build_complexity_router_config", async (importOriginal) => {
 });
 
 // A real TeamDropdown fetches teams and renders an antd Select; the wiring under test is
-// whether team_id is registered, validated and forwarded, so a plain control stands in.
+// whether team_id is registered, validated and forwarded, so a plain control stands in. The
+// clear button mirrors the real dropdown's x, which emits null rather than a string.
 vi.mock("../common_components/team_dropdown", () => ({
-  default: ({ value, onChange }: { value?: string; onChange?: (next: string) => void }) => (
-    <select
-      data-testid="team-dropdown"
-      value={value ?? ""}
-      onChange={(event) => onChange?.(event.target.value)}
-      aria-label="Select Team"
-    >
-      <option value="">none</option>
-      <option value="team-1">team-1</option>
-    </select>
+  default: ({ value, onChange }: { value?: string; onChange?: (next: string | null) => void }) => (
+    <>
+      <select
+        data-testid="team-dropdown"
+        value={value ?? ""}
+        onChange={(event) => onChange?.(event.target.value)}
+        aria-label="Select Team"
+      >
+        <option value="">none</option>
+        <option value="team-1">team-1</option>
+      </select>
+      <button type="button" data-testid="team-dropdown-clear" onClick={() => onChange?.(null)}>
+        clear team
+      </button>
+    </>
   ),
 }));
 
@@ -354,6 +360,25 @@ describe("AddAutoRouterTab", () => {
     expect(handleAddAutoRouterSubmit).not.toHaveBeenCalled();
   });
 
+  // The shared dropdown emits null on clear while this form's schema wants a string, so the
+  // form maps null back to "": the user sees the pick-a-team message, not a zod type error.
+  it("treats a team picked and then cleared like no team at all", async () => {
+    const user = userEvent.setup();
+    vi.mocked(getMissingTiersError).mockReturnValue(null);
+
+    renderWithProviders(
+      <AddAutoRouterTab handleOk={vi.fn()} accessToken="token" userRole="Internal User" createScope="team-required" />,
+    );
+
+    await user.type(screen.getByPlaceholderText(/smart_router/i), "team-scoped-router");
+    await user.selectOptions(screen.getByTestId("team-dropdown"), "team-1");
+    await user.click(screen.getByTestId("team-dropdown-clear"));
+    await user.click(screen.getByRole("button", { name: /add auto router/i }));
+
+    expect(await screen.findByText("Please select a team to continue")).toBeInTheDocument();
+    expect(handleAddAutoRouterSubmit).not.toHaveBeenCalled();
+  });
+
   it("defaults a new router to session affinity off, matching the backend field default", async () => {
     const user = userEvent.setup();
     vi.mocked(getMissingTiersError).mockReturnValue(null);
diff --git a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx
index 318adcce369..03b7432e4ec 100644
--- a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx
@@ -548,7 +548,9 @@ const AddAutoRouterTab: React.FC<AddAutoRouterTabProps> = ({
                     "Select the team this auto router belongs to. Only keys for this team will be able to call it.",
                   )}
                 >
-                  {({ id, value, onChange }) => <TeamDropdown id={id} value={value} onChange={onChange} />}
+                  {({ id, value, onChange }) => (
+                    <TeamDropdown id={id} value={value} onChange={(next) => onChange(next ?? "")} />
+                  )}
                 </FormField>
               )}
 
diff --git a/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx b/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx
new file mode 100644
index 00000000000..01b8a12d99c
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx
@@ -0,0 +1,48 @@
+import { render, screen } from "@testing-library/react";
+import userEvent from "@testing-library/user-event";
+import { describe, expect, it, vi } from "vitest";
+
+import { chooseSelectOption } from "../../../tests/test-utils";
+import type { Team } from "../key_team_helpers/key_list";
+import TeamDropdown from "./team_dropdown";
+
+const TEAMS = [
+  { team_id: "team-1", team_alias: "Alpha Team" },
+  { team_id: "team-2", team_alias: "Beta Team" },
+] as unknown as Team[];
+
+vi.mock("@/app/(dashboard)/hooks/teams/useTeams", () => ({
+  useInfiniteTeams: () => ({
+    data: { pages: [{ teams: TEAMS }] },
+    fetchNextPage: vi.fn(),
+    hasNextPage: false,
+    isFetchingNextPage: false,
+    isLoading: false,
+  }),
+}));
+
+describe("TeamDropdown", () => {
+  it("emits the picked team's id and full object", async () => {
+    const user = userEvent.setup();
+    const onChange = vi.fn();
+    const onTeamSelect = vi.fn();
+    render(<TeamDropdown onChange={onChange} onTeamSelect={onTeamSelect} />);
+
+    await chooseSelectOption(user, screen.getByRole("combobox"), /^Beta Team/);
+
+    expect(onChange).toHaveBeenCalledWith("team-2");
+    expect(onTeamSelect).toHaveBeenCalledWith(TEAMS[1]);
+  });
+
+  it("emits null, never the empty string, when the selection is cleared", async () => {
+    const user = userEvent.setup();
+    const onChange = vi.fn();
+    const onTeamSelect = vi.fn();
+    render(<TeamDropdown value="team-1" onChange={onChange} onTeamSelect={onTeamSelect} />);
+
+    await user.click(screen.getByRole("button", { name: "Clear" }));
+
+    expect(onChange).toHaveBeenCalledWith(null);
+    expect(onTeamSelect).toHaveBeenCalledWith(null);
+  });
+});
diff --git a/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx b/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx
index 35121f41598..7d385c2a3f7 100644
--- a/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx
+++ b/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx
@@ -5,7 +5,7 @@ import { Team } from "../key_team_helpers/key_list";
 
 interface TeamDropdownProps {
   value?: string;
-  onChange?: (value: string) => void;
+  onChange?: (value: string | null) => void;
   /** Callback with the full Team object (or null on clear). */
   onTeamSelect?: (team: Team | null) => void;
   disabled?: boolean;
@@ -47,7 +47,7 @@ const TeamDropdown: React.FC<TeamDropdownProps> = ({
   }, [data]);
 
   const handleChange = (teamId: string) => {
-    onChange?.(teamId);
+    onChange?.(teamId || null);
     if (onTeamSelect) {
       onTeamSelect(teamId ? teams.find((t) => t.team_id === teamId) ?? null : null);
     }
diff --git a/ui/litellm-dashboard/src/components/networking.tsx b/ui/litellm-dashboard/src/components/networking.tsx
index b53a67f9bcc..db7baf5e171 100644
--- a/ui/litellm-dashboard/src/components/networking.tsx
+++ b/ui/litellm-dashboard/src/components/networking.tsx
@@ -310,6 +310,8 @@ export interface AgentCredentialFieldMetadata {
   options?: string[] | null;
   default_value?: string | null;
   include_in_litellm_params?: boolean;
+  validation_pattern?: string | null;
+  validation_message?: string | null;
 }
 
 export interface AgentCreateInfo {
@@ -6970,7 +6972,7 @@ export const vectorStoreSearchCall = async (
     if (!response.ok) {
       const errorData = await response.text();
       await handleError(errorData);
-      return null;
+      throw new Error(errorData);
     }
 
     const data = await response.json();
diff --git a/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts b/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts
index 2a8306473b8..b5802ffa2dc 100644
--- a/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts
+++ b/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts
@@ -158,6 +158,24 @@ describe("autorouter_presets", () => {
     });
   });
 
+  it("pins the OpenAI preset to the Luna, Terra, and Sol progression", () => {
+    const preset = getPresetByKey("openai_family")!;
+    const expectedTiers = {
+      SIMPLE: ["gpt-5.6-luna"],
+      MEDIUM: ["gpt-5.6-terra"],
+      COMPLEX: ["gpt-5.6-sol"],
+      REASONING: ["gpt-5.6-sol"],
+    };
+    expect(preset.complexity_router_config.tiers).toEqual(expectedTiers);
+    expect(preset.complexity_router_config.tier_model_configs).toEqual({
+      REASONING: [{ model_name: "gpt-5.6-sol", litellm_params: { reasoning_effort: "xhigh" } }],
+    });
+    const prefill = buildPresetPrefill(preset.complexity_router_config, groupsOnly(getRequiredModelsInPreset(preset)));
+    expect(prefill.complexityRouterConfig.tier_model_params).toEqual({
+      REASONING: { "gpt-5.6-sol": { reasoning_effort: "xhigh" } },
+    });
+  });
+
   it("pins the gemini preset to concrete model ids, never Google's hot-swapping -latest aliases", () => {
     const gemini = getPresetByKey("gemini_family")!;
     const config = gemini.complexity_router_config;
diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts
index 6e38f3fa15e..a1b27070003 100644
--- a/ui/litellm-dashboard/src/lib/http/schema.d.ts
+++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts
@@ -13289,6 +13289,58 @@ export interface paths {
         patch: operations["patch_user_scim_v2_Users__user_id__patch"];
         trace?: never;
     };
+    "/scim/v2/placeholders": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        /**
+         * List Placeholders
+         * @description List user rows whose id is another account's SSO identity or email.
+         *
+         *     An earlier release provisioned a group member it could not match as a user keyed
+         *     by the raw member value, and that row now shadows the account the value really
+         *     names, so every push of that member is refused. This lists those rows so an
+         *     operator can fold each one into the account it shadows with
+         *     ``POST /scim/v2/placeholders/{user_id}/merge``. A row that has an SSO identity of
+         *     its own or owns virtual keys is left out: someone uses that account.
+         */
+        get: operations["list_placeholders_scim_v2_placeholders_get"];
+        put?: never;
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
+    "/scim/v2/placeholders/{user_id}/merge": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Merge Placeholder
+         * @description Fold a placeholder user into the one account its id names by SSO identity or email.
+         *
+         *     The account is added to every team the placeholder is on, then the placeholder is
+         *     deleted the way ``DELETE /scim/v2/Users/{id}`` deletes a user, so the next group
+         *     push resolves the member value to the real account. Refused with 409 when the row
+         *     has an SSO identity of its own, owns virtual keys, or names no account or several.
+         */
+        post: operations["merge_placeholder_scim_v2_placeholders__user_id__merge_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/search": {
         parameters: {
             query?: never;
@@ -22816,6 +22868,10 @@ export interface components {
             required: boolean;
             /** Tooltip */
             tooltip?: string | null;
+            /** Validation Message */
+            validation_message?: string | null;
+            /** Validation Pattern */
+            validation_pattern?: string | null;
         };
         /**
          * AgentExtension
@@ -34927,6 +34983,27 @@ export interface components {
             /** Value */
             value?: unknown | null;
         };
+        /**
+         * SCIMPlaceholder
+         * @description A user row keyed by a value that names another account by SSO identity or email.
+         */
+        SCIMPlaceholder: {
+            /** Placeholder User Id */
+            placeholder_user_id: string;
+            /** Resolved User Ids */
+            resolved_user_ids: string[];
+            /** Team Ids */
+            team_ids: string[];
+        };
+        /** SCIMPlaceholderMergeResult */
+        SCIMPlaceholderMergeResult: {
+            /** Merged Into User Id */
+            merged_into_user_id: string;
+            /** Placeholder User Id */
+            placeholder_user_id: string;
+            /** Team Ids */
+            team_ids: string[];
+        };
         /** SCIMServiceProviderConfig */
         SCIMServiceProviderConfig: {
             /** Authenticationschemes */
@@ -37400,6 +37477,8 @@ export interface components {
             } | null;
             /** Num Retries */
             num_retries?: number | null;
+            /** Optional Pre Call Checks */
+            optional_pre_call_checks?: ("prompt_caching" | "router_budget_limiting" | "responses_api_deployment_check" | "deployment_affinity" | "session_affinity" | "forward_client_headers_by_model_group" | "enforce_model_rate_limits" | "encrypted_content_affinity")[] | null;
             /** Retry After */
             retry_after?: number | null;
             retry_policy?: components["schemas"]["RetryPolicy"] | null;
@@ -55858,6 +55937,70 @@ export interface operations {
             };
         };
     };
+    list_placeholders_scim_v2_placeholders_get: {
+        parameters: {
+            query?: {
+                feature?: string | null;
+            };
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["SCIMPlaceholder"][];
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
+    merge_placeholder_scim_v2_placeholders__user_id__merge_post: {
+        parameters: {
+            query?: {
+                feature?: string | null;
+            };
+            header?: never;
+            path: {
+                user_id: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["SCIMPlaceholderMergeResult"];
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
     search_search_post: {
         parameters: {
             query?: {
diff --git a/uv.lock b/uv.lock
index 27be919eea1..aa59ff7b229 100644
--- a/uv.lock
+++ b/uv.lock
@@ -10,7 +10,7 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-08-29T17:58:57.633306Z"
+exclude-newer = "2026-08-30T17:51:25.171404Z"
 exclude-newer-span = "P3D"
 
 [manifest]
@@ -25,7 +25,7 @@ constraints = [
     { name = "packaging", specifier = ">=24.0" },
     { name = "setuptools", specifier = ">=83.0.0" },
     { name = "soupsieve", specifier = ">=2.8.4" },
-    { name = "tornado", specifier = ">=6.5.6" },
+    { name = "tornado", specifier = ">=6.5.8" },
 ]
 overrides = [
     { name = "cryptography", specifier = ">=50.0.0,<51.0" },
@@ -4552,7 +4552,7 @@ requires-dist = [
     { name = "pydantic-settings", specifier = ">=2.14.1,<3.0" },
     { name = "pyjwt", marker = "extra == 'proxy'", specifier = ">=2.13.0,<3.0" },
     { name = "pynacl", marker = "extra == 'proxy'", specifier = ">=1.6.2,<2.0" },
-    { name = "pypdf", marker = "extra == 'proxy-runtime'", specifier = ">=6.12.0,<7.0" },
+    { name = "pypdf", marker = "extra == 'proxy-runtime'", specifier = ">=6.16.1,<7.0" },
     { name = "pyroscope-io", marker = "sys_platform != 'win32' and extra == 'proxy'", specifier = ">=0.8.16,<1.0" },
     { name = "python-dotenv", specifier = ">=1.0.0,<2.0" },
     { name = "python-multipart", marker = "extra == 'proxy'", specifier = ">=0.0.27,<1.0" },
@@ -7564,14 +7564,14 @@ wheels = [
 
 [[package]]
 name = "pypdf"
-version = "6.15.0"
+version = "6.16.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/17/17/ee75a92718ec7212de831e71454d702225aa5e474a805cce169806044453/pypdf-6.15.0.tar.gz", hash = "sha256:d39c4d955a76409284a905e2d65b40076d77ab76129e0faaeeb6612403ecfc79", size = 6993794, upload-time = "2026-08-06T13:06:49.929Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/44/66/54212e75406afd9f3e933d0dda23072f6aecc55c5a273077dc2e0b028b23/pypdf-6.16.2.tar.gz", hash = "sha256:595647f6191de6f402cfde1d0c455d6cbccbd509aac32b34783009c032de5d6e", size = 7008996, upload-time = "2026-08-23T13:50:07.135Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/af/72/ce3067ac31e214a66388159f8462ddb8c13dd00170f24d555a1f1ae8ee91/pypdf-6.15.0-py3-none-any.whl", hash = "sha256:14e001d6504822cb1ca9c7ed9a69bccb320f59b320730f55af804361abe4d5ee", size = 378123, upload-time = "2026-08-06T13:06:47.709Z" },
+    { url = "https://files.pythonhosted.org/packages/13/f1/a2da3b55acd4ab737bf728c97edaaed5ec1d3c1236acb639dcdfa97e42c7/pypdf-6.16.2-py3-none-any.whl", hash = "sha256:c8b09a59399062fb45a1b8156c18a787a10a3dae03ac9674397a226712c94604", size = 385060, upload-time = "2026-08-23T13:50:05.349Z" },
 ]
 
 [[package]]
@@ -9441,19 +9441,19 @@ wheels = [
 
 [[package]]
 name = "tornado"
-version = "6.5.7"
+version = "6.5.8"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/64/24/95ec527ad67b76d59299e5465b3935d05e4294b7e0290a3924b7487df30b/tornado-6.5.7.tar.gz", hash = "sha256:66c513a76cda70d53907bc27cf1447557699c2e95aa48ba27a442ff61c3ddfc2", size = 519252, upload-time = "2026-06-08T17:34:51.232Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/10/d3/343e5bb989d6515b1646cf3d40135d73f3d5e45339bded401b56cdac24dd/tornado-6.5.8.tar.gz", hash = "sha256:9452e1b208a8bd771e2cb1f2ff564985b9b214bdebbe622793e1799e0a6bd23f", size = 520493, upload-time = "2026-08-07T02:12:42.971Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/02/dc/c7043cab6fed8ae159fc1923ce829ada35c4dbd797d408a43858ffaf9639/tornado-6.5.7-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:148b2eb15c2c765a50796172c1e499649b35f30d2e3c3d3e15913cfa56bfb163", size = 448543, upload-time = "2026-06-08T17:34:38.052Z" },
-    { url = "https://files.pythonhosted.org/packages/92/4f/090b1431e5a43df696feceffc268c5383cc079ecb5f08ce58f917109aafe/tornado-6.5.7-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:9da38de27f1da3b78a966f0dae12b5a1ea9afe72ca805d84ff06508272ddf100", size = 446707, upload-time = "2026-06-08T17:34:39.594Z" },
-    { url = "https://files.pythonhosted.org/packages/37/d8/ef374952fd5da67d4463122c2b8e5a96536ec10b4b339254c6dcde81d01c/tornado-6.5.7-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:8d759e71906ee783f8867b93bf26a265743da4c1e2f4a018464c1ba019862972", size = 449774, upload-time = "2026-06-08T17:34:41.204Z" },
-    { url = "https://files.pythonhosted.org/packages/35/37/d434c73f4c6e014b745b9b37085f34f40c022f007efff3d7fe65991899f3/tornado-6.5.7-cp39-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8a46347a18f23fb92b396beebe0fb78f61dda0cc302445202c16203d8a18848b", size = 450745, upload-time = "2026-06-08T17:34:42.531Z" },
-    { url = "https://files.pythonhosted.org/packages/b6/2b/56b9aff361d7f1ab728a805ec7d7ea835f8807afa9f5cc690ea0e630efb9/tornado-6.5.7-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:7778b30bef919231265e91c69963ce0f49a1e9c07ac900bbe75b19ce2575ba92", size = 450578, upload-time = "2026-06-08T17:34:43.787Z" },
-    { url = "https://files.pythonhosted.org/packages/02/30/a7444fb23aa76860a14198fab96ac79f1866b0a6e19e26c4381b0938e50f/tornado-6.5.7-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:e726f0c75da7726eec023aa62751ff8878bd2737e34fbdd33b1ae5897d2200f5", size = 449985, upload-time = "2026-06-08T17:34:45.326Z" },
-    { url = "https://files.pythonhosted.org/packages/5c/42/5f0e56c01e8d9d36f4e23f367b85ae6cae0c1ecddd5e6977d8388ad27488/tornado-6.5.7-cp39-abi3-win32.whl", hash = "sha256:f8de3bf12d3efdd0cbe7c8887868198f8a91415e3f29fcf258d9b8eb7b1d9ae4", size = 451047, upload-time = "2026-06-08T17:34:46.784Z" },
-    { url = "https://files.pythonhosted.org/packages/c9/a4/b393076ffb21b469eec5b328a0534cf03a3b90bfc6b1f09507cdd075d938/tornado-6.5.7-cp39-abi3-win_amd64.whl", hash = "sha256:de942f843533a039ef9fa3d9c88c7cd8a7c94553fb5ad0154270989b3d99a2c4", size = 451485, upload-time = "2026-06-08T17:34:48.248Z" },
-    { url = "https://files.pythonhosted.org/packages/71/2e/7b1c769803121b809112cf9a00681c472eae1d80e32d7ec0e0bd61d0d0e1/tornado-6.5.7-cp39-abi3-win_arm64.whl", hash = "sha256:ff934fce95643af5f11efdae618eaa73d469dc588641e5c8d19295a0c65c4796", size = 450506, upload-time = "2026-06-08T17:34:49.702Z" },
+    { url = "https://files.pythonhosted.org/packages/f2/d5/007086fd8df5489338e204f65adce33fd4f21a4999dbb2b9cff2f897b5f4/tornado-6.5.8-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:cc6aa787d7cfab7c3d35189dc7a56fbd2399a569624c730c6b55b3d6531d0403", size = 449487, upload-time = "2026-08-07T02:12:28.682Z" },
+    { url = "https://files.pythonhosted.org/packages/70/c8/5a24a99495903f594f6a199dd7beead1cbc0a13e2cb9102727bcaaf2a997/tornado-6.5.8-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:9715b5eb79735b2bcd454ce216a9275b7c0470e64ea1bf5742f78b2f72b26eeb", size = 447649, upload-time = "2026-08-07T02:12:30.306Z" },
+    { url = "https://files.pythonhosted.org/packages/6e/de/f2e733f386b85962d1b1dc82cd63d169b5b4580062b35397eac9244a41fe/tornado-6.5.8-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:547d63f450d570c14fe0e8db2cfb14c9bbd1c2503b4a6612586267955aa47b58", size = 450707, upload-time = "2026-08-07T02:12:31.95Z" },
+    { url = "https://files.pythonhosted.org/packages/0b/94/20efeee9a01c141e9ac47c397f81679dfda24b32768fc4fff24e76d36c2c/tornado-6.5.8-cp39-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7e2360a0ffbe145eca8af0b19cb7203d79b1a98dd4cccdd6b368f6f49c2e3808", size = 451677, upload-time = "2026-08-07T02:12:33.512Z" },
+    { url = "https://files.pythonhosted.org/packages/42/ec/a96ccb8ccf0de2b7bc2c5fa1608a4803735018242e90c4882365a9fd418f/tornado-6.5.8-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:5d242290bdf7ab3151bc1065fdd75c0dcc21cbc7b49f22a4c56329c2d6566d22", size = 451510, upload-time = "2026-08-07T02:12:35.346Z" },
+    { url = "https://files.pythonhosted.org/packages/29/b5/93185859245ad3f00e62175f29607346788b696369347f0146e0421286bb/tornado-6.5.8-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:7b94ff0e128fe0542f3bd331fb44d06260fc4ac16881545159f34ef08aad4195", size = 450917, upload-time = "2026-08-07T02:12:36.963Z" },
+    { url = "https://files.pythonhosted.org/packages/97/cf/fe33cf062834487d34d1559746a4a12521033c22645b6d74d4bca702e018/tornado-6.5.8-cp39-abi3-win32.whl", hash = "sha256:67832909c4779c64942380cb5f044a5c6163d00831472d80e25e115de9917836", size = 451952, upload-time = "2026-08-07T02:12:38.512Z" },
+    { url = "https://files.pythonhosted.org/packages/cb/e1/468ad54333e92ccb62627e62cb88e5fc14a2171daa67ed47b1b8542d5b86/tornado-6.5.8-cp39-abi3-win_amd64.whl", hash = "sha256:11881db6b7c168494be2c2d12e65931451bdf7ee718535418ae1d8855dd5a0ee", size = 452391, upload-time = "2026-08-07T02:12:39.971Z" },
+    { url = "https://files.pythonhosted.org/packages/ad/3e/cd5e4f06e34cde33b8ef66cf36aa2b5ad46354cc1af7d2136bbe365fee1d/tornado-6.5.8-cp39-abi3-win_arm64.whl", hash = "sha256:68a7468c7e289f8514d7d664101753903217eff1bb6822c6b5994a0b5f5bcb26", size = 451411, upload-time = "2026-08-07T02:12:41.469Z" },
 ]
 
 [[package]]
diff --git a/whitelisted_bedrock_models.txt b/whitelisted_bedrock_models.txt
index 7e20081988d..8753d7c3c77 100644
--- a/whitelisted_bedrock_models.txt
+++ b/whitelisted_bedrock_models.txt
@@ -217,3 +217,17 @@ bedrock/us-east-1/zai.glm-5
 bedrock/us-west-2/zai.glm-5
 bedrock/us-gov-east-1/anthropic.claude-haiku-4-5-20251001-v1:0
 bedrock/us-gov-west-1/anthropic.claude-haiku-4-5-20251001-v1:0
+bedrock/us-gov-west-1/nvidia.nemotron-nano-3-30b
+bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2
+bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b
+bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0
+bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0
+bedrock/us-gov-west-1/anthropic.claude-sonnet-5
+bedrock/us-gov-west-1/anthropic.claude-opus-4-8
+bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b
+bedrock/us-gov-east-1/nvidia.nemotron-nano-12b-v2
+bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b
+bedrock/us-gov-east-1/openai.gpt-oss-20b-1:0
+bedrock/us-gov-east-1/openai.gpt-oss-120b-1:0
+bedrock/us-gov-east-1/anthropic.claude-sonnet-5
+bedrock/us-gov-east-1/anthropic.claude-opus-4-8