diff --git a/tests/integration/cost_calculation/cases/anthropic.py b/tests/integration/cost_calculation/cases/anthropic.py
index c214352fdb0..702420e36e8 100644
--- a/tests/integration/cost_calculation/cases/anthropic.py
+++ b/tests/integration/cost_calculation/cases/anthropic.py
@@ -4002,6 +4002,46 @@ CLAUDE_SONNET_5_PASSTHROUGH_MESSAGES_CACHE_READ: Final = CostTrackingTestCase(
     ),
 )
 
+CLAUDE_SONNET_5_PASSTHROUGH_MESSAGES_STREAM_CACHE_WRITE_ON_MESSAGE_DELTA: Final = CostTrackingTestCase(
+    name="claude-sonnet-5-passthrough-messages_stream_cache_write_on_message_delta",
+    covers="quota_management.spend_tracking.scripted_wire.logs_cost",
+    model="claude-sonnet-5",
+    endpoint="/anthropic/v1/messages",
+    request={
+        "model": "$MODEL",
+        "max_tokens": 12,
+        "messages": [
+            {
+                "role": "user",
+                "content": [{"type": "text", "text": "cached text", "cache_control": {"type": "ephemeral"}}],
+            }
+        ],
+        "stream": True,
+    },
+    response=SseResponse(
+        content_type="text/event-stream",
+        frames=(
+            'event: message_start\ndata: {"type":"message_start","message":{"id":"msg_$REQUEST_ID","type":"message","role":"assistant","model":"claude-sonnet-5","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":3,"output_tokens":1}}}',
+            'event: content_block_start\ndata: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}',
+            'event: content_block_delta\ndata: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"scripted response"}}',
+            'event: content_block_stop\ndata: {"type":"content_block_stop","index":0}',
+            'event: message_delta\ndata: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"input_tokens":3,"cache_read_input_tokens":25490,"cache_creation_input_tokens":10553,"output_tokens":12}}',
+            'data: {"type":"message_stop"}',
+        ),
+    ),
+    expected=ExactExpected(
+        spend=0.04741075,
+        input_cost=0.04723075,
+        output_cost=0.00018,
+        prompt_tokens=36046,
+        completion_tokens=12,
+        cache_read_cost=0.007647,
+        cache_creation_cost=0.03957375,
+        breakdown_persisted=False,
+        cost_header=False,
+    ),
+)
+
 CLAUDE_SONNET_5_CACHE_CREATION_1H_ABOVE_200K: Final = CostTrackingTestCase(
     name="claude-sonnet-5-cache_creation_1h_above_200k",
     covers="quota_management.spend_tracking.cost_matrix.logs_cost",
@@ -6997,6 +7037,7 @@ CASES: Final[tuple[CostTrackingTestCase, ...]] = (
     CLAUDE_HAIKU_4_5_MESSAGES_INPUT_TEXT,
     CLAUDE_SONNET_5_PASSTHROUGH_MESSAGES,
     CLAUDE_SONNET_5_PASSTHROUGH_MESSAGES_CACHE_READ,
+    CLAUDE_SONNET_5_PASSTHROUGH_MESSAGES_STREAM_CACHE_WRITE_ON_MESSAGE_DELTA,
     CLAUDE_SONNET_5_CACHE_CREATION_1H_ABOVE_200K,
     CLAUDE_OPUS_5_5_INPUT_TEXT,
     CLAUDE_SONNET_5_5_INPUT_TEXT,
diff --git a/tests/integration/cost_calculation/cases/fireworks_ai.py b/tests/integration/cost_calculation/cases/fireworks_ai.py
index bd740cd8166..6e6c2c9abbf 100644
--- a/tests/integration/cost_calculation/cases/fireworks_ai.py
+++ b/tests/integration/cost_calculation/cases/fireworks_ai.py
@@ -1097,6 +1097,138 @@ FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_CACHE_READ: Final = CostTrackingT
     ),
 )
 
+FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_MESSAGES_STREAM_CACHE_READ: Final = CostTrackingTestCase(
+    name="fireworks_ai-accounts-fireworks-models-kimi-k3-messages_stream_cache_read",
+    covers="quota_management.spend_tracking.scripted_wire.logs_cost",
+    model="fireworks_ai/accounts/fireworks/models/kimi-k3",
+    endpoint="/v1/messages",
+    request={
+        "model": "$MODEL",
+        "max_tokens": 380,
+        "messages": [{"role": "user", "content": "3e7a1c5d9b02 summarize the attached material in one line"}],
+        "stream": True,
+    },
+    response=SseResponse(
+        content_type="text/event-stream",
+        frames=sse_frames(
+            {
+                "id": "chatcmpl-$REQUEST_ID",
+                "object": "chat.completion.chunk",
+                "created": 1789788231,
+                "model": "accounts/fireworks/models/kimi-k3",
+                "choices": [{"index": 0, "delta": {"role": "assistant"}, "finish_reason": None}],
+                "usage": None,
+            },
+            {
+                "id": "chatcmpl-$REQUEST_ID",
+                "object": "chat.completion.chunk",
+                "created": 1789788231,
+                "model": "accounts/fireworks/models/kimi-k3",
+                "choices": [
+                    {
+                        "index": 0,
+                        "delta": {"role": "assistant", "content": "scripted answer 3e7a1c5d9b02"},
+                        "finish_reason": None,
+                    }
+                ],
+                "usage": None,
+            },
+            {
+                "id": "chatcmpl-$REQUEST_ID",
+                "object": "chat.completion.chunk",
+                "created": 1789788231,
+                "model": "accounts/fireworks/models/kimi-k3",
+                "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
+                "usage": None,
+            },
+            {
+                "id": "chatcmpl-$REQUEST_ID",
+                "object": "chat.completion.chunk",
+                "created": 1789788231,
+                "model": "accounts/fireworks/models/kimi-k3",
+                "choices": [],
+                "usage": {
+                    "prompt_tokens": 12928,
+                    "completion_tokens": 380,
+                    "total_tokens": 13308,
+                    "prompt_tokens_details": {"cached_tokens": 12288},
+                },
+            },
+            done=True,
+        ),
+    ),
+    expected=ExactExpected(
+        spend=0.00207128, input_cost=0.00112128, output_cost=0.00095, prompt_tokens=12928, completion_tokens=380
+    ),
+)
+
+FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_MESSAGES_STREAM_CACHE_READ_CHOICE_BEARING_USAGE: Final = (
+    CostTrackingTestCase(
+        name="fireworks_ai-accounts-fireworks-models-kimi-k3-messages_stream_cache_read_choice_bearing_usage",
+        covers="quota_management.spend_tracking.scripted_wire.logs_cost",
+        model="fireworks_ai/accounts/fireworks/models/kimi-k3",
+        endpoint="/v1/messages",
+        request={
+            "model": "$MODEL",
+            "max_tokens": 380,
+            "messages": [{"role": "user", "content": "9b4d2f8e1a67 summarize the attached material in one line"}],
+            "stream": True,
+        },
+        response=SseResponse(
+            content_type="text/event-stream",
+            frames=sse_frames(
+                {
+                    "id": "chatcmpl-$REQUEST_ID",
+                    "object": "chat.completion.chunk",
+                    "created": 1789788231,
+                    "model": "accounts/fireworks/models/kimi-k3",
+                    "choices": [{"index": 0, "delta": {"role": "assistant"}, "finish_reason": None}],
+                    "usage": None,
+                },
+                {
+                    "id": "chatcmpl-$REQUEST_ID",
+                    "object": "chat.completion.chunk",
+                    "created": 1789788231,
+                    "model": "accounts/fireworks/models/kimi-k3",
+                    "choices": [
+                        {
+                            "index": 0,
+                            "delta": {"role": "assistant", "content": "scripted answer 9b4d2f8e1a67"},
+                            "finish_reason": None,
+                        }
+                    ],
+                    "usage": None,
+                },
+                {
+                    "id": "chatcmpl-$REQUEST_ID",
+                    "object": "chat.completion.chunk",
+                    "created": 1789788231,
+                    "model": "accounts/fireworks/models/kimi-k3",
+                    "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
+                    "usage": None,
+                },
+                {
+                    "id": "chatcmpl-$REQUEST_ID",
+                    "object": "chat.completion.chunk",
+                    "created": 1789788231,
+                    "model": "accounts/fireworks/models/kimi-k3",
+                    "choices": [{"index": 0, "delta": {}}],
+                    "usage": {
+                        "prompt_tokens": 12928,
+                        "completion_tokens": 380,
+                        "total_tokens": 13308,
+                        "prompt_tokens_details": {"cached_tokens": 12288},
+                    },
+                },
+                done=True,
+            ),
+        ),
+        expected=ExactExpected(
+            spend=0.00207128, input_cost=0.00112128, output_cost=0.00095, prompt_tokens=12928, completion_tokens=380
+        ),
+    )
+)
+
 FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_STREAM: Final = CostTrackingTestCase(
     name="fireworks_ai-accounts-fireworks-models-kimi-k3-stream",
     covers="quota_management.spend_tracking.scripted_wire.logs_cost",
@@ -2971,6 +3103,8 @@ CASES: Final[tuple[CostTrackingTestCase, ...]] = (
     FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_DEEPSEEK_V4P1_FLASH_STREAM_FULL_USAGE,
     FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_INPUT_TEXT,
     FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_CACHE_READ,
+    FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_MESSAGES_STREAM_CACHE_READ,
+    FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_MESSAGES_STREAM_CACHE_READ_CHOICE_BEARING_USAGE,
     FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_STREAM,
     FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_STREAM_NO_USAGE,
     FIREWORKS_AI_ACCOUNTS_FIREWORKS_MODELS_KIMI_K3_STREAM_NO_USAGE_TOOL_CALL,
diff --git a/tests/integration/cost_calculation/cases/openai.py b/tests/integration/cost_calculation/cases/openai.py
index 6ad0ff95615..fe4b736959c 100644
--- a/tests/integration/cost_calculation/cases/openai.py
+++ b/tests/integration/cost_calculation/cases/openai.py
@@ -1936,6 +1936,82 @@ GPT_5_4_MINI_CACHE_READ: Final = CostTrackingTestCase(
     ),
 )
 
+GPT_5_4_MINI_STREAM_CACHE_READ_CHOICE_BEARING_USAGE: Final = CostTrackingTestCase(
+    name="gpt-5.4-mini-stream_cache_read_choice_bearing_usage",
+    covers="quota_management.spend_tracking.scripted_wire.logs_cost",
+    model="gpt-5.4-mini",
+    request={
+        "model": "$MODEL",
+        "messages": [
+            {
+                "role": "system",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": "You are a deterministic pricing-harness assistant. Keep answers to a single short line.",
+                    }
+                ],
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": "6c1f0b2a9d4e summarize the attached material in one line and name the city weather",
+                    }
+                ],
+            },
+        ],
+        "stream": True,
+        "stream_options": {"include_usage": True},
+        "allowed_openai_params": [],
+    },
+    response=SseResponse(
+        content_type="text/event-stream",
+        frames=sse_frames(
+            {
+                "id": "chatcmpl-$REQUEST_ID",
+                "object": "chat.completion.chunk",
+                "created": 1789788260,
+                "model": "gpt-5.4-mini",
+                "choices": [
+                    {
+                        "index": 0,
+                        "delta": {"role": "assistant", "content": "scripted answer 6c1f0b2a9d4e"},
+                        "finish_reason": None,
+                    }
+                ],
+                "usage": None,
+            },
+            {
+                "id": "chatcmpl-$REQUEST_ID",
+                "object": "chat.completion.chunk",
+                "created": 1789788260,
+                "model": "gpt-5.4-mini",
+                "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
+                "usage": None,
+            },
+            {
+                "id": "chatcmpl-$REQUEST_ID",
+                "object": "chat.completion.chunk",
+                "created": 1789788260,
+                "model": "gpt-5.4-mini",
+                "choices": [{"index": 0, "delta": {}}],
+                "usage": {
+                    "prompt_tokens": 12928,
+                    "completion_tokens": 380,
+                    "total_tokens": 13308,
+                    "prompt_tokens_details": {"cached_tokens": 12288},
+                },
+            },
+            done=True,
+        ),
+    ),
+    expected=ExactExpected(
+        spend=0.00171808, input_cost=0.00065408, output_cost=0.001064, prompt_tokens=12928, completion_tokens=380
+    ),
+)
+
 GPT_5_4_MINI_AUDIO_INPUT: Final = CostTrackingTestCase(
     name="gpt-5.4-mini-audio_input",
     covers="quota_management.spend_tracking.cost_matrix.logs_cost",
@@ -11161,6 +11237,7 @@ CASES: Final[tuple[CostTrackingTestCase, ...]] = (
     GPT_5_3_CODEX_STREAM_FULL_USAGE,
     GPT_5_4_MINI_INPUT_TEXT,
     GPT_5_4_MINI_CACHE_READ,
+    GPT_5_4_MINI_STREAM_CACHE_READ_CHOICE_BEARING_USAGE,
     GPT_5_4_MINI_AUDIO_INPUT,
     GPT_5_4_MINI_AUDIO_OUTPUT,
     GPT_5_4_MINI_REASONING,
diff --git a/tests/integration/cost_calculation/test_bridged_previous_response_id_spend.py b/tests/integration/cost_calculation/test_bridged_previous_response_id_spend.py
new file mode 100644
index 00000000000..2a8c63fff3d
--- /dev/null
+++ b/tests/integration/cost_calculation/test_bridged_previous_response_id_spend.py
@@ -0,0 +1,123 @@
+"""A /v1/responses deployment bridged to chat completions (`use_chat_completions_api: true`) answers a
+`previous_response_id` follow-up with the prior turn replayed from LiteLLM_SpendLogs, and bills the follow-up
+from its own usage (LIT-9604, #46398)"""
+
+import json
+import uuid
+from collections.abc import Iterator
+from dataclasses import dataclass
+from typing import Final
+
+import pytest
+from integration._support.client import Gateway, eventually, gateway_from_environment
+from integration._support.database import read_rows
+from integration._support.process import OwnedProxy, owned_proxy_process
+from integration._support.wire import Reply, Request, Wire, wire_server
+from integration._support.workers import cost_map_environment
+from integration.cost_calculation.cost_tracking_case import COST_MAP
+from pydantic import JsonValue, TypeAdapter
+
+pytestmark: Final = pytest.mark.timeout(240)
+
+_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue])
+_MESSAGES: Final = TypeAdapter(list[dict[str, JsonValue]])
+_MODEL: Final = "gpt-5.6"
+_PROMPT_TOKENS: Final = 1840
+_COMPLETION_TOKENS: Final = 412
+_FIRST_TURN: Final = "My favorite color is yellow. Remember it"
+_SECOND_TURN: Final = "What is my favorite color?"
+_ANSWER: Final = "scripted answer yellow"
+
+
+@dataclass(frozen=True, slots=True)
+class _Rig:
+    wire: Wire
+    proxy: OwnedProxy
+
+    @property
+    def gateway(self) -> Gateway:
+        return self.proxy.gateway
+
+
+def _respond(request: Request) -> Reply:
+    assert request.target.endswith("/chat/completions"), request.target
+    body: Final = _JSON_OBJECT.validate_json(request.body)
+    assert body["model"] == _MODEL, body
+    completion: Final = {
+        "id": f"chatcmpl-{uuid.uuid4().hex}",
+        "object": "chat.completion",
+        "created": 1,
+        "model": _MODEL,
+        "choices": [{"index": 0, "message": {"role": "assistant", "content": _ANSWER}, "finish_reason": "stop"}],
+        "usage": {
+            "prompt_tokens": _PROMPT_TOKENS,
+            "completion_tokens": _COMPLETION_TOKENS,
+            "total_tokens": _PROMPT_TOKENS + _COMPLETION_TOKENS,
+        },
+    }
+    return Reply(body=json.dumps(completion).encode())
+
+
+@pytest.fixture(scope="module")
+def rig(tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Rig]:
+    directory: Final = tmp_path_factory.mktemp("bridged-previous-response-id-rig")
+    with gateway_from_environment() as gateway, wire_server(_respond) as wire:
+        overrides: Final = {**cost_map_environment(gateway.upstream_url), "STORE_PROMPTS_IN_SPEND_LOGS": "true"}
+        with owned_proxy_process(
+            gateway, directory, overrides, remove_environment=("LITELLM_LOCAL_MODEL_COST_MAP",)
+        ) as owned:
+            yield _Rig(wire, owned)
+
+
+def _spend_rows(model: str) -> list[dict[str, JsonValue]]:
+    return read_rows(
+        'SELECT request_id, spend, status FROM "LiteLLM_SpendLogs" WHERE model_group = %s ORDER BY "startTime"',
+        (model,),
+    )
+
+
+def _upstream_body(request: Request) -> dict[str, JsonValue]:
+    body: Final = _JSON_OBJECT.validate_json(request.body)
+    assert "previous_response_id" not in body, body
+    return body
+
+
+def _upstream_messages(request: Request) -> list[dict[str, JsonValue]]:
+    return _MESSAGES.validate_python(_upstream_body(request)["messages"])
+
+
+def test_bridged_previous_response_id_replays_the_prior_turn_and_bills_the_follow_up(rig: _Rig) -> None:
+    with rig.gateway.scenario() as scenario:
+        model: Final = scenario.model(
+            model=f"openai/{_MODEL}",
+            api_base=rig.wire.url,
+            api_key="sk-scripted-provider",
+            use_chat_completions_api=True,
+        )
+        first: Final = rig.gateway.request("POST", "/v1/responses", {"model": model, "input": _FIRST_TURN})
+        assert first.status_code == 200, first.text
+        first_id: Final = _JSON_OBJECT.validate_json(first.content)["id"]
+        assert isinstance(first_id, str) and first_id.startswith("resp_"), first_id
+        first_rows: Final = eventually(lambda: _spend_rows(model), lambda rows: len(rows) == 1, seconds=70)
+        assert first_rows[0]["status"] == "success", first_rows
+
+        second: Final = rig.gateway.request(
+            "POST", "/v1/responses", {"model": model, "input": _SECOND_TURN, "previous_response_id": first_id}
+        )
+        assert second.status_code == 200, second.text
+        sent: Final = tuple(request for request in rig.wire.drain() if request.method == "POST")
+        assert len(sent) == 2, [request.target for request in sent]
+        assert _upstream_messages(sent[0]) == [{"role": "user", "content": _FIRST_TURN}], sent[0].body
+        assert _upstream_messages(sent[1]) == [
+            {"role": "user", "content": _FIRST_TURN},
+            {"role": "assistant", "content": _ANSWER},
+            {"role": "user", "content": _SECOND_TURN},
+        ], sent[1].body
+
+        rows: Final = eventually(lambda: _spend_rows(model), lambda values: len(values) == 2, seconds=70)
+        assert [row["status"] for row in rows] == ["success", "success"], rows
+        rates: Final = COST_MAP[_MODEL]
+        assert rates.input_cost_per_token is not None and rates.output_cost_per_token is not None, rates
+        assert float(rows[1]["spend"]) == pytest.approx(
+            _PROMPT_TOKENS * rates.input_cost_per_token + _COMPLETION_TOKENS * rates.output_cost_per_token
+        ), rows