diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml
index 57ffe28a4b5..a32b5ebb2a8 100644
--- a/.github/workflows/test-unit.yml
+++ b/.github/workflows/test-unit.yml
@@ -213,7 +213,6 @@ jobs:
             test-path: >-
               tests/local_testing/test_cache_preset_key.py
               tests/local_testing/test_caching_handler.py
-              tests/local_testing/test_prompt_caching.py
               tests/local_testing/test_responses_stream_cache_keys.py
               tests/local_testing/test_unit_test_caching.py
             workers: 2
diff --git a/tests/litellm_utils_tests/test_utils.py b/tests/litellm_utils_tests/test_utils.py
index b68c2cb3d65..e8b3862756f 100644
--- a/tests/litellm_utils_tests/test_utils.py
+++ b/tests/litellm_utils_tests/test_utils.py
@@ -22,11 +22,7 @@ from litellm.litellm_core_utils.duration_parser import (
 )
 from litellm.utils import (
     check_valid_key,
-    create_pretrained_tokenizer,
-    create_tokenizer,
-    function_to_dict,
     get_llm_provider,
-    get_max_tokens,
     get_supported_openai_params,
     get_token_count,
     get_valid_models,
@@ -500,74 +496,6 @@ def test_function_to_dict():
 # test_function_to_dict()
 
 
-@pytest.mark.parametrize(
-    "model, expected_bool",
-    [
-        ("gpt-3.5-turbo", True),
-        ("azure/gpt-4-1106-preview", True),
-        ("groq/gemma-7b-it", True),
-        ("gemini/gemini-2.5-flash", True),
-    ],
-)
-def test_supports_function_calling(model, expected_bool):
-    try:
-        assert litellm.supports_function_calling(model=model) == expected_bool
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
-
-
-@pytest.mark.parametrize(
-    "model, expected_bool",
-    [
-        ("gpt-4o-mini-search-preview", True),
-        ("openai/gpt-4o-mini-search-preview", True),
-        ("gpt-4o-search-preview", True),
-        ("openai/gpt-4o-search-preview", True),
-        ("groq/deepseek-r1-distill-llama-70b", False),
-        ("groq/llama-3.3-70b-versatile", False),
-        ("codestral/codestral-latest", False),
-    ],
-)
-def test_supports_web_search(model, expected_bool):
-    try:
-        assert litellm.supports_web_search(model=model) == expected_bool
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
-
-
-@pytest.mark.parametrize(
-    "model, expected_bool",
-    [
-        ("openai/o3-mini", True),
-        ("o3-mini", True),
-        ("xai/grok-3-mini-beta", True),
-        ("xai/grok-3-mini-fast-beta", True),
-        ("xai/grok-2", False),
-        ("gpt-3.5-turbo", False),
-    ],
-)
-def test_supports_reasoning(model, expected_bool):
-    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-    try:
-        assert litellm.supports_reasoning(model=model) == expected_bool
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
-
-
-def test_get_max_token_unit_test():
-    """
-    More complete testing in `test_completion_cost.py`
-    """
-    model = "bedrock/anthropic.claude-3-haiku-20240307-v1:0"
-
-    max_tokens = get_max_tokens(
-        model
-    )  # Returns a number instead of throwing an Exception
-
-    assert isinstance(max_tokens, int)
-
-
 def test_get_supported_openai_params() -> None:
     # Mapped provider
     assert isinstance(get_supported_openai_params("gpt-4"), list)
@@ -1041,73 +969,6 @@ def test_parse_content_for_reasoning(content, expected_reasoning, expected_conte
     )
 
 
-@pytest.mark.parametrize(
-    "model, expected_bool",
-    [
-        ("vertex_ai/gemini-2.5-pro", True),
-        ("gemini/gemini-2.5-pro", True),
-        ("predibase/llama3-8b-instruct", True),
-        ("databricks/databricks-meta-llama-3-1-70b-instruct", True),
-        ("gpt-3.5-turbo", False),
-        ("groq/llama-3.3-70b-versatile", False),
-    ],
-)
-def test_supports_response_schema(model, expected_bool):
-    """
-    Unit tests for 'supports_response_schema' helper function.
-
-    Should be true for gemini-2.5-pro on google ai studio / vertex ai AND predibase models
-    Should be false otherwise
-    """
-    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-
-    from litellm.utils import supports_response_schema
-
-    response = supports_response_schema(model=model, custom_llm_provider=None)
-
-    assert expected_bool == response
-
-
-@pytest.mark.parametrize(
-    "model, expected_bool",
-    [
-        ("gpt-3.5-turbo", True),
-        ("gpt-4", True),
-        ("command-nightly", False),
-        ("gemini-2.5-pro", True),
-    ],
-)
-def test_supports_function_calling_v2(model, expected_bool):
-    """
-    Unit test for 'supports_function_calling' helper function.
-    """
-    from litellm.utils import supports_function_calling
-
-    response = supports_function_calling(model=model, custom_llm_provider=None)
-    assert expected_bool == response
-
-
-@pytest.mark.parametrize(
-    "model, expected_bool",
-    [
-        ("gpt-4o", True),
-        ("gpt-3.5-turbo", False),
-        ("claude-sonnet-4-6", True),
-        ("gemini-2.5-flash", True),
-        ("command-nightly", False),
-    ],
-)
-def test_supports_vision(model, expected_bool):
-    """
-    Unit test for 'supports_vision' helper function.
-    """
-    from litellm.utils import supports_vision
-
-    response = supports_vision(model=model, custom_llm_provider=None)
-    assert expected_bool == response
-
-
 def test_usage_object_null_tokens():
     """
     Unit test.
@@ -1146,7 +1007,6 @@ def test_is_base64_encoded():
     clear=True,
 )
 def test_async_http_handler(mock_async_client):
-    import httpx
     import ssl
 
     timeout = 120
@@ -1221,20 +1081,6 @@ def test_async_http_handler_force_ipv4(mock_async_client):
         litellm.force_ipv4 = False
 
 
-@pytest.mark.parametrize(
-    "model, expected_bool", [("gpt-3.5-turbo", False), ("gpt-4o-audio-preview", True)]
-)
-def test_supports_audio_input(model, expected_bool):
-    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-
-    from litellm.utils import supports_audio_input, supports_audio_output
-
-    supports_pc = supports_audio_input(model=model)
-
-    assert supports_pc == expected_bool
-
-
 def test_is_base64_encoded_2():
     from litellm.utils import is_base64_encoded
 
@@ -1569,23 +1415,6 @@ def test_token_counter_with_image_url_with_detail_high():
     assert _tokens == DEFAULT_IMAGE_TOKEN_COUNT + 7
 
 
-def test_fireworks_ai_vision_capability_from_cost_map(monkeypatch):
-    """
-    Fireworks deprecated document inlining on 2025-06-30, so vision/PDF support is
-    no longer hardcoded to True for every Fireworks model. Capabilities are read
-    from the model cost map: unmapped models no longer advertise vision or PDF
-    support, while mapped VLMs still do.
-    """
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
-    from litellm.utils import supports_pdf_input, supports_vision
-
-    assert supports_vision("fireworks_ai/llama-3.1-8b-instruct") is False
-    assert supports_pdf_input("fireworks_ai/llama-3.1-8b-instruct") is False
-
-    assert supports_vision("fireworks_ai/minimax-m3") is True
-
-
 def test_logprobs_type():
     from litellm.types.utils import Logprobs
 
@@ -1728,21 +1557,12 @@ def test_get_valid_models_default(monkeypatch):
     Prevent regression for existing usage.
     """
     from litellm.utils import get_valid_models
-    import litellm
 
     monkeypatch.setenv("FIREWORKS_API_KEY", "sk-1234")
     valid_models = get_valid_models()
     assert len(valid_models) > 0
 
 
-def test_supports_vision_gemini():
-    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-    from litellm.utils import supports_vision
-
-    assert supports_vision("gemini-2.5-pro") is True
-
-
 def test_pick_cheapest_chat_model_from_llm_provider():
     from litellm.litellm_core_utils.llm_request_utils import (
         pick_cheapest_chat_models_from_llm_provider,
diff --git a/tests/llm_translation/test_azure_o_series.py b/tests/llm_translation/test_azure_o_series.py
index ce7e614cbe2..7a223739844 100644
--- a/tests/llm_translation/test_azure_o_series.py
+++ b/tests/llm_translation/test_azure_o_series.py
@@ -1,15 +1,12 @@
 import json
 import os
-from datetime import datetime
-from unittest.mock import AsyncMock, patch, MagicMock
+from unittest.mock import patch
 
 
-
-import httpx
 import pytest
 
 import litellm
-from litellm import Choices, Message, ModelResponse
+from litellm import ModelResponse
 from base_llm_unit_tests import BaseLLMChatTest, BaseOSeriesModelsTest
 
 
diff --git a/tests/llm_translation/test_lambda_ai.py b/tests/llm_translation/test_lambda_ai.py
index edba459b352..e6f8b13d4ba 100644
--- a/tests/llm_translation/test_lambda_ai.py
+++ b/tests/llm_translation/test_lambda_ai.py
@@ -102,35 +102,3 @@ async def test_lambda_ai_completion_call():
             raise
 
 
-def test_lambda_ai_model_list_populated():
-    """Test that lambda_ai_models list is populated correctly"""
-    # Ensure we're using local model cost map and repopulate models
-    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-
-    # Clear and repopulate all model lists after reloading model_cost
-    litellm.lambda_ai_models = set()
-    litellm.add_known_models()
-
-    # This should be populated by the add_known_models function
-    assert (
-        len(litellm.lambda_ai_models) > 0
-    ), "lambda_ai_models list should not be empty"
-
-    # Check that all models in the list are Lambda AI models
-    for model in litellm.lambda_ai_models:
-        assert model.startswith(
-            "lambda_ai/"
-        ), f"Model {model} should start with 'lambda_ai/'"
-
-    # Check some expected models are in the list
-    expected_models = [
-        "lambda_ai/llama3.1-8b-instruct",
-        "lambda_ai/hermes3-405b",
-        "lambda_ai/deepseek-v3-0324",
-    ]
-
-    for model in expected_models:
-        assert (
-            model in litellm.lambda_ai_models
-        ), f"{model} should be in lambda_ai_models list"
diff --git a/tests/llm_translation/test_perplexity_reasoning.py b/tests/llm_translation/test_perplexity_reasoning.py
index 61fbc9d7824..0fdfdd79321 100644
--- a/tests/llm_translation/test_perplexity_reasoning.py
+++ b/tests/llm_translation/test_perplexity_reasoning.py
@@ -1,4 +1,3 @@
-import json
 import os
 from unittest.mock import patch, MagicMock
 
@@ -136,50 +135,6 @@ class TestPerplexityReasoning:
                 == "This is a test response from the reasoning model."
             )
 
-    def test_perplexity_reasoning_models_support_reasoning(self):
-        """
-        Test that Perplexity Sonar reasoning models are correctly identified as supporting reasoning
-        """
-        from litellm.utils import supports_reasoning
-
-        # Set up local model cost map
-        os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-        litellm.model_cost = litellm.get_model_cost_map(url="")
-
-        reasoning_models = [
-            "perplexity/sonar-reasoning",
-            "perplexity/sonar-reasoning-pro",
-        ]
-
-        for model in reasoning_models:
-            assert supports_reasoning(model, None), f"{model} should support reasoning"
-
-    def test_perplexity_non_reasoning_models_dont_support_reasoning(self):
-        """
-        Test that non-reasoning Perplexity models don't support reasoning
-        """
-        from litellm.utils import supports_reasoning
-
-        # Set up local model cost map
-        os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-        litellm.model_cost = litellm.get_model_cost_map(url="")
-
-        non_reasoning_models = [
-            "perplexity/sonar",
-            "perplexity/sonar-pro",
-            "perplexity/llama-3.1-sonar-large-128k-chat",
-            "perplexity/mistral-7b-instruct",
-        ]
-
-        for model in non_reasoning_models:
-            # These models should not support reasoning (should return False or raise exception)
-            try:
-                result = supports_reasoning(model, None)
-                # If it doesn't raise an exception, it should return False
-                assert result is False, f"{model} should not support reasoning"
-            except Exception:
-                # If it raises an exception, that's also acceptable behavior
-                pass
 
     @pytest.mark.parametrize(
         "model,expected_api_base",
diff --git a/tests/local_testing/test_completion_cost.py b/tests/local_testing/test_completion_cost.py
index d900dcb6f27..f40818b9bf1 100644
--- a/tests/local_testing/test_completion_cost.py
+++ b/tests/local_testing/test_completion_cost.py
@@ -6,8 +6,7 @@ import litellm.cost_calculator
 import asyncio
 import time
 from typing import Optional
-from unittest.mock import AsyncMock, MagicMock, patch
-import base64
+from unittest.mock import MagicMock, patch
 import pytest
 
 import litellm
@@ -15,9 +14,7 @@ from litellm import (
     TranscriptionResponse,
     completion_cost,
     cost_per_token,
-    get_max_tokens,
     model_cost,
-    open_ai_chat_completion_models,
 )
 from litellm.llms.custom_httpx.http_handler import HTTPHandler
 import json
@@ -162,12 +159,6 @@ def test_custom_pricing_as_completion_cost_param():
 # test_get_palm_tokens()
 
 
-def test_zephyr_hf_tokens():
-    max_tokens = get_max_tokens("huggingface/HuggingFaceH4/zephyr-7b-beta")
-    print(max_tokens)
-    assert max_tokens == 32768
-
-
 # test_zephyr_hf_tokens()
 
 
@@ -426,10 +417,8 @@ def test_groq_response_cost_tracking(is_streaming):
     from litellm.utils import (
         CallTypes,
         Choices,
-        Delta,
         Message,
         ModelResponse,
-        StreamingChoices,
         Usage,
     )
 
@@ -548,12 +537,6 @@ def test_gemini_completion_cost(provider):
     assert calculated_output_cost == output_cost
 
 
-def _count_characters(text):
-    # Remove white spaces and count characters
-    filtered_text = "".join(char for char in text if not char.isspace())
-    return len(filtered_text)
-
-
 def test_vertex_ai_completion_cost():
     os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
     litellm.model_cost = litellm.get_model_cost_map(url="")
@@ -817,10 +800,8 @@ def test_completion_cost_azure_common_deployment_name():
     from litellm.utils import (
         CallTypes,
         Choices,
-        Delta,
         Message,
         ModelResponse,
-        StreamingChoices,
         Usage,
     )
 
@@ -1252,7 +1233,7 @@ def test_cost_openai_prompt_caching():
     ],
 )
 def test_completion_cost_azure_ai_rerank(model):
-    from litellm import RerankResponse, rerank
+    from litellm import RerankResponse
 
     os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
     litellm.model_cost = litellm.get_model_cost_map(url="")
@@ -1283,7 +1264,7 @@ def test_completion_cost_azure_ai_rerank(model):
 
 
 def test_together_ai_embedding_completion_cost():
-    from litellm.utils import Choices, EmbeddingResponse, Message, ModelResponse, Usage
+    from litellm.utils import EmbeddingResponse, Usage
 
     os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
     litellm.model_cost = litellm.get_model_cost_map(url="")
@@ -2222,7 +2203,6 @@ async def test_test_completion_cost_gpt4o_audio_output_from_model(stream):
         ModelResponse,
         Usage,
         ChatCompletionAudioResponse,
-        PromptTokensDetails,
         CompletionTokensDetailsWrapper,
         PromptTokensDetailsWrapper,
     )
@@ -2464,7 +2444,6 @@ def test_add_known_models():
 
 @pytest.mark.skip(reason="flaky test")
 def test_bedrock_cost_calc_with_region():
-    from litellm import completion
 
     from litellm import ModelResponse
 
diff --git a/tests/local_testing/test_get_model_info.py b/tests/local_testing/test_get_model_info.py
index 38ccfd91f95..37f4ece611d 100644
--- a/tests/local_testing/test_get_model_info.py
+++ b/tests/local_testing/test_get_model_info.py
@@ -47,12 +47,6 @@ def test_get_model_info_custom_llm_with_same_name_vllm(monkeypatch):
     assert model_info["input_cost_per_token"] == 0.0
 
 
-def test_get_model_info_gemini_pro():
-    info = litellm.get_model_info("gemini-2.0-flash")
-    print("info", info)
-    assert info["key"] == "gemini-2.0-flash"
-
-
 def test_get_model_info_ollama_chat():
     from litellm.llms.ollama.completion.transformation import OllamaConfig
 
@@ -354,27 +348,6 @@ def test_get_model_info_huggingface_models(monkeypatch):
     )
 
 
-@pytest.mark.parametrize(
-    "model, provider",
-    [
-        ("bedrock/us-east-2/us.anthropic.claude-3-haiku-20240307-v1:0", None),
-        (
-            "bedrock/us-east-2/us.anthropic.claude-3-haiku-20240307-v1:0",
-            "bedrock",
-        ),
-    ],
-)
-def test_get_model_info_cost_calculator_bedrock_region_cris_stripped(model, provider):
-    """
-    ensure cross region inferencing model is used correctly
-    Relevant Issue: https://github.com/BerriAI/litellm/issues/8115
-    """
-    info = get_model_info(model=model, custom_llm_provider=provider)
-    print("info", info)
-    assert info["key"] == "us.anthropic.claude-3-haiku-20240307-v1:0"
-    assert info["litellm_provider"] == "bedrock"
-
-
 def test_get_model_info_case_insensitive_lookup(monkeypatch):
     """
     Test that model info lookup is case-insensitive.
diff --git a/tests/local_testing/test_prompt_caching.py b/tests/local_testing/test_prompt_caching.py
deleted file mode 100644
index f6b3fb89e9e..00000000000
--- a/tests/local_testing/test_prompt_caching.py
+++ /dev/null
@@ -1,43 +0,0 @@
-"""Asserts that prompt caching information is correctly returned for Anthropic, OpenAI, and Deepseek"""
-
-import io
-
-
-import litellm
-import pytest
-
-
-def _usage_format_tests(usage: litellm.Usage):
-    """
-    OpenAI prompt caching
-    - prompt_tokens = sum of non-cache hit tokens + cache-hit tokens
-    - total_tokens = prompt_tokens + completion_tokens
-
-    Example
-    ```
-    "usage": {
-        "prompt_tokens": 2006,
-        "completion_tokens": 300,
-        "total_tokens": 2306,
-        "prompt_tokens_details": {
-            "cached_tokens": 1920
-        },
-        "completion_tokens_details": {
-            "reasoning_tokens": 0
-        }
-        # ANTHROPIC_ONLY #
-        "cache_creation_input_tokens": 0
-    }
-    ```
-    """
-    assert usage.total_tokens == usage.prompt_tokens + usage.completion_tokens
-
-    assert usage.prompt_tokens > usage.prompt_tokens_details.cached_tokens
-
-
-def test_supports_prompt_caching():
-    from litellm.utils import supports_prompt_caching
-
-    supports_pc = supports_prompt_caching(model="anthropic/claude-sonnet-4-5-20250929")
-
-    assert supports_pc
diff --git a/tests/local_testing/test_register_model.py b/tests/local_testing/test_register_model.py
index eddd697974c..5f334a27e35 100644
--- a/tests/local_testing/test_register_model.py
+++ b/tests/local_testing/test_register_model.py
@@ -2,8 +2,6 @@
 #    This tests calling batch_completions by running 100 messages together
 
 import ast
-import sys, os
-import traceback
 from pathlib import Path
 
 import pytest
@@ -32,16 +30,6 @@ def test_update_model_cost():
 # test_update_model_cost()
 
 
-def test_update_model_cost_map_url():
-    try:
-        litellm.register_model(
-            model_cost="https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
-        )
-        assert litellm.model_cost["gpt-4"]["input_cost_per_token"] == 0.00003
-    except Exception as e:
-        pytest.fail(f"An error occurred: {e}")
-
-
 # test_update_model_cost_map_url()
 
 
diff --git a/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_fixture_models.py b/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_fixture_models.py
index 80b830369e6..96751cebe01 100644
--- a/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_fixture_models.py
+++ b/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_fixture_models.py
@@ -3,7 +3,6 @@ from __future__ import annotations
 import base64
 from collections.abc import Callable
 from datetime import date
-from pathlib import Path
 from typing import Final, cast
 from unittest.mock import patch
 from urllib.parse import parse_qs, urlparse
@@ -262,20 +261,6 @@ def _reducto_document() -> ReductoDocumentUrlDocument:
     )
 
 
-def test_fixture_catalogs_match_active_registered_ocr_models() -> None:
-    registry_path: Final = Path(__file__).resolve().parents[6] / "model_prices_and_context_window.json"
-    registry: Final = MODEL_REGISTRY.validate_json(registry_path.read_text(encoding="utf-8"))
-    active_registered: Final = frozenset(
-        model
-        for model, raw_metadata in registry.items()
-        if raw_metadata.get("mode") == "ocr" and raw_metadata.get("litellm_provider") in SUPPORTED_OCR_PROVIDERS
-        for metadata in (_ModelRegistryEntry.model_validate(raw_metadata),)
-        if metadata.deprecation_date is None or metadata.deprecation_date > date.today()
-    )
-
-    assert ACTIVE_OCR_MODELS == active_registered
-
-
 @pytest.mark.parametrize(
     ("fixture_model", "provider_config", "model"),
     (
diff --git a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
index 6b7780acd20..92b1185e542 100644
--- a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
+++ b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
@@ -1,15 +1,12 @@
 import copy
-import datetime
 import json
 import os
 import subprocess
 import sys
 import textwrap
-import unittest
 from typing import List, Optional, Tuple
-from unittest.mock import ANY, MagicMock, Mock, patch
+from unittest.mock import MagicMock, patch
 
-import httpx
 import pytest
 
 import litellm
@@ -19,7 +16,6 @@ from litellm.integrations.anthropic_cache_control_hook import (
 )
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
 from litellm.types.llms.openai import AllMessageValues
-from litellm.types.utils import StandardCallbackDynamicParams
 
 
 @pytest.fixture(autouse=True)
@@ -2984,18 +2980,6 @@ class TestPromptCacheBreakpointCapability:
         yield
         litellm.utils._cached_get_model_info_helper.cache_clear()
 
-    def test_public_helper_reads_the_model_map(self):
-        from litellm.utils import supports_prompt_cache_breakpoint
-
-        assert supports_prompt_cache_breakpoint("gpt-5.6") is True
-        assert supports_prompt_cache_breakpoint("openai/gpt-5.6-sol") is True
-        assert supports_prompt_cache_breakpoint("gpt-5.6", custom_llm_provider="openai") is True
-        assert supports_prompt_cache_breakpoint("gpt-4.1") is False
-
-    @pytest.mark.parametrize("model", ["gpt-5.6", "gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna"])
-    def test_model_map_flags_every_openai_gpt_5_6_entry(self, model):
-        assert litellm.model_cost[model]["litellm_provider"] == "openai"
-        assert litellm.model_cost[model]["supports_prompt_cache_breakpoint"] is True
 
     def test_listed_model_uses_the_model_map_flag(self, monkeypatch):
         flagged = {**litellm.model_cost["gpt-4.1"], "supports_prompt_cache_breakpoint": True}
@@ -3014,9 +2998,6 @@ class TestPromptCacheBreakpointCapability:
         )
         assert supports_openai_prompt_cache_breakpoint("gpt-5.6") is False
 
-    def test_listed_gpt_model_without_the_flag_follows_the_version_rule(self):
-        assert "supports_prompt_cache_breakpoint" not in litellm.model_cost["gpt-4.1"]
-        assert supports_openai_prompt_cache_breakpoint("gpt-4.1") is False
 
     def test_published_map_without_the_flag_still_injects_on_gpt_5_6(self, monkeypatch):
         unflagged = {k: v for k, v in litellm.model_cost["gpt-5.6"].items() if k != "supports_prompt_cache_breakpoint"}
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_guardrail_cost.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_guardrail_cost.py
index af2f169157e..aa2fc0b9a45 100644
--- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_guardrail_cost.py
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_guardrail_cost.py
@@ -1,4 +1,3 @@
-import os
 
 import pytest
 
@@ -121,22 +120,6 @@ def test_billed_guardrail_cost_by_unit_treats_none_in_spend_as_billed():
     assert billed_guardrail_cost_by_unit(entry) == {"contentPolicyUnits": 0.15}
 
 
-def test_shipped_bedrock_guardrail_prices_match_aws_pricing_page(monkeypatch):
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-    assert litellm.model_cost["bedrock/guardrails"]["guardrail_cost_per_unit"] == {
-        "automatedReasoningPolicyUnits": 0.00017,
-        "contentPolicyImageUnits": 0.00075,
-        "contentPolicyUnits": 0.00015,
-        "contextualGroundingPolicyUnits": 0.0001,
-        "sensitiveInformationPolicyFreeUnits": 0.0,
-        "sensitiveInformationPolicyUnits": 0.0001,
-        "topicPolicyUnits": 0.00015,
-        "wordPolicyUnits": 0.0,
-    }
-    assert "bedrock/guardrails" not in litellm.bedrock_models
-
-
 def test_guardrail_information_cost_sums_entries():
     entries = [
         {"guardrail_name": "a", "guardrail_cost": 0.0003},
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 5775656301d..776d78a04e0 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
@@ -1575,59 +1575,6 @@ def test_generic_cost_per_token_tiered_pricing_bills_reasoning_at_tier_rate():
         litellm.model_cost.pop(model, None)
 
 
-def test_gpt_5_6_alias_prices_match_sol(local_model_cost_map):
-    """Regression: the bare gpt-5.6 alias routes to GPT-5.6 Sol, so every cost field on
-    the two entries has to hold the same value. They drifted once before, when Sol took
-    its promotional cut and gpt-5.6 was left on the pre-cut rates, overbilling callers
-    who used the alias."""
-    alias = litellm.model_cost["gpt-5.6"]
-    sol = litellm.model_cost["gpt-5.6-sol"]
-
-    cost_fields = sorted(field for field in sol if "cost" in field)
-    assert len(cost_fields) == 27
-
-    for field in cost_fields:
-        assert alias.get(field) == sol.get(field), field
-
-
-@pytest.mark.parametrize(
-    "model,expected_none,expected_xhigh,expected_minimal",
-    [
-        # Verified against OpenAI's live API on 2026-04-24:
-        #   gpt-5.5   -> supports: none, low, medium, high, xhigh
-        #   gpt-5.5-pro -> supports: medium, high, xhigh
-        # Neither supports "minimal"; gpt-5.5-pro additionally does not support "none".
-        # The JSON must reflect this so LiteLLM rejects unsupported values locally
-        # (or drops them with drop_params=True) instead of round-tripping to OpenAI
-        # for a 400.
-        ("gpt-5.5", True, True, False),
-        ("gpt-5.5-2026-04-23", True, True, False),
-        ("gpt-5.5-pro", False, True, False),
-        ("gpt-5.5-pro-2026-04-23", False, True, False),
-    ],
-)
-def test_gpt55_reasoning_effort_flags_match_live_openai_api(
-    _local_model_cost_map, model, expected_none, expected_xhigh, expected_minimal
-):
-    """Pin reasoning_effort capability flags to OpenAI's actual API contract.
-
-    Observed via `POST /v1/chat/completions` with reasoning_effort=minimal:
-    ``Unsupported value: 'reasoning_effort' does not support 'minimal' with
-    this model``. gpt-5.5-pro additionally rejects 'none' and 'low'.
-    """
-
-    m = litellm.model_cost[model]
-    assert m.get("supports_none_reasoning_effort") is expected_none, (
-        f"{model}: supports_none_reasoning_effort expected {expected_none}"
-    )
-    assert m.get("supports_xhigh_reasoning_effort") is expected_xhigh, (
-        f"{model}: supports_xhigh_reasoning_effort expected {expected_xhigh}"
-    )
-    assert m.get("supports_minimal_reasoning_effort") is expected_minimal, (
-        f"{model}: supports_minimal_reasoning_effort expected {expected_minimal}"
-    )
-
-
 @pytest.mark.parametrize(
     "base_model,dated_model",
     [
@@ -1662,29 +1609,6 @@ def test_gpt55_dated_variants_match_base_reasoning_effort_capabilities(_local_mo
         )
 
 
-@pytest.mark.parametrize(
-    "model,expected_none,expected_minimal,expected_xhigh",
-    [
-        # Mirror live OpenAI API contract (verified via openai/gpt-5.5* on
-        # 2026-04-24): chat accepts {none, low, medium, high, xhigh} but NOT
-        # minimal; pro accepts {medium, high, xhigh} only.
-        # NOTE: openai/gpt-5.5* entries currently set supports_minimal=true on
-        # main (pre #26456). Once that PR lands, OpenAI + Azure flags align.
-        ("azure/gpt-5.5", True, False, True),
-        ("azure/gpt-5.5-pro", False, False, True),
-    ],
-)
-def test_azure_gpt55_reasoning_effort_flags_match_live_openai_api(
-    _local_model_cost_map, model, expected_none, expected_minimal, expected_xhigh
-):
-    """Azure entries pin reasoning_effort flags to OpenAI's actual API contract."""
-
-    m = litellm.model_cost[model]
-    assert m.get("supports_none_reasoning_effort") is expected_none
-    assert m.get("supports_minimal_reasoning_effort") is expected_minimal
-    assert m.get("supports_xhigh_reasoning_effort") is expected_xhigh
-
-
 def test_string_cost_values():
     """Test that cost values defined as strings are properly converted to floats."""
     from unittest.mock import patch
@@ -3413,14 +3337,6 @@ GEMINI_38_FLASH_FIELDS_SHARED_WITH_37_FLASH = (
 )
 
 
-@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
-
-
 @pytest.mark.parametrize(
     ("response_quality", "requested_quality", "expected_cost"),
     [
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py
index 761eed868b5..7bae2eaa338 100644
--- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py
@@ -1,4 +1,3 @@
-from collections.abc import Mapping, Sequence
 
 import pytest
 
@@ -527,7 +526,6 @@ def _openai_responses_with_web_search_calls(model, num_calls):
         ResponseFunctionWebSearch,
     )
 
-    from litellm.types.llms.openai import ResponsesAPIResponse
 
     output = [
         ResponseFunctionWebSearch(
@@ -585,7 +583,6 @@ def test_web_search_call_count_reads_dict_output_items(local_model_cost_map):
     counter must read their "type" key like the detection gate does, instead of flooring
     a multi-search response to a single billable search.
     """
-    from litellm.types.llms.openai import ResponsesAPIResponse
     from litellm.types.utils import Usage
 
     model = "gpt-4o-search-preview"
@@ -631,7 +628,6 @@ def test_response_includes_output_type_reads_dict_output_items():
     items without an "action" field) stay plain dicts in the output union. The gate must
     read their "type" key instead of returning False and skipping the web search fee.
     """
-    from litellm.types.llms.openai import ResponsesAPIResponse
 
     response = ResponsesAPIResponse.model_validate(
         {
@@ -699,34 +695,3 @@ _BEDROCK_MANTLE_WEB_SEARCH_MODELS = (
 _BEDROCK_MANTLE_WEB_SEARCH_RATE = 0.012
 
 
-def _responses_with_web_search(
-    model: str, actions: Sequence[Mapping[str, str]], tool_usage: Mapping[str, object] | None = None
-) -> ResponsesAPIResponse:
-    payload = {
-        "id": "resp_1",
-        "created_at": 1756900000,
-        "model": model.split("/", 1)[-1],
-        "object": "response",
-        "status": "completed",
-        "output": [
-            {"type": "web_search_call", "id": f"ws_{i}", "status": "completed", "action": action}
-            for i, action in enumerate(actions)
-        ],
-    }
-    return ResponsesAPIResponse.model_validate(
-        payload if tool_usage is None else {**payload, "tool_usage": tool_usage}
-    )
-
-
-def _web_search_cost(model: str, response: ResponsesAPIResponse, custom_llm_provider: str) -> float:
-    from litellm.types.utils import Usage
-
-    return StandardBuiltInToolCostTracking.get_cost_for_built_in_tools(
-        model=model,
-        response_object=response,
-        usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
-        custom_llm_provider=custom_llm_provider,
-        standard_built_in_tools_params=None,
-    )
-
-
diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py
index 370ec4b6f60..83ee3437429 100644
--- a/tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py
+++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py
@@ -14,7 +14,6 @@ rather than forwarded as a no-op the provider can reject. See BerriAI/litellm#33
 import pytest
 
 from litellm.litellm_core_utils.prompt_templates.factory import _bedrock_tools_pt
-from litellm.llms.bedrock.common_utils import bedrock_converse_supports_strict_tools
 
 _STRICT_TOOL = [
     {
@@ -163,76 +162,3 @@ def test_bedrock_tools_pt_strict_dropped_for_non_anthropic(model_id: str) -> Non
     assert "strict" not in result[0]["toolSpec"]
 
 
-def test_bedrock_converse_supports_strict_tools_helper() -> None:
-    """Direct check for the gate helper used by factory.py."""
-    assert (
-        bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-opus-4-7")
-        is False
-    )
-    assert (
-        bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-opus-4-8")
-        is False
-    )
-    assert (
-        bedrock_converse_supports_strict_tools(
-            "anthropic.claude-sonnet-4-5-20250929-v1:0"
-        )
-        is True
-    )
-    assert (
-        bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-opus-4-6")
-        is True
-    )
-    assert bedrock_converse_supports_strict_tools("us.amazon.nova-micro-v1:0") is False
-    assert bedrock_converse_supports_strict_tools("") is False
-    # Sonnet 4 also rejects strict on Bedrock Converse
-    assert (
-        bedrock_converse_supports_strict_tools(
-            "anthropic.claude-sonnet-4-20250514-v1:0"
-        )
-        is False
-    )
-    assert (
-        bedrock_converse_supports_strict_tools(
-            "bedrock/global.anthropic.claude-sonnet-4-20250514-v1:0"
-        )
-        is False
-    )
-    assert bedrock_converse_supports_strict_tools("anthropic.claude-sonnet-5") is False
-    assert (
-        bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-sonnet-5")
-        is False
-    )
-    assert (
-        bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0")
-        is True
-    )
-
-
-@pytest.mark.parametrize(
-    "cost_map_key",
-    [
-        "anthropic.claude-opus-4-7",
-        "us.anthropic.claude-opus-4-7",
-        "anthropic.claude-opus-4-8",
-        "us.anthropic.claude-opus-4-8",
-        "anthropic.claude-sonnet-4-20250514-v1:0",
-        "global.anthropic.claude-sonnet-4-20250514-v1:0",
-        "us.anthropic.claude-sonnet-4-20250514-v1:0",
-        "eu.anthropic.claude-sonnet-4-20250514-v1:0",
-        "apac.anthropic.claude-sonnet-4-20250514-v1:0",
-        "anthropic.claude-sonnet-5",
-        "global.anthropic.claude-sonnet-5",
-        "us.anthropic.claude-sonnet-5",
-        "eu.anthropic.claude-sonnet-5",
-        "au.anthropic.claude-sonnet-5",
-        "jp.anthropic.claude-sonnet-5",
-    ],
-)
-def test_strict_tools_flag_set_in_model_cost_map(cost_map_key: str) -> None:
-    """The gate is driven by ``bedrock_converse_supports_strict_tools: false`` in
-    ``model_prices_and_context_window.json``, not hardcoded model patterns."""
-    from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap
-
-    cost_map = GetModelCostMap.load_local_model_cost_map()
-    assert cost_map[cost_map_key]["bedrock_converse_supports_strict_tools"] is False
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 034062826f6..6bc0e4105f1 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
@@ -1,5 +1,4 @@
 import base64
-import json
 import logging
 import os
 import re
@@ -10,7 +9,6 @@ import pytest
 
 import litellm
 from litellm.litellm_core_utils.prompt_templates.factory import (
-    BAD_MESSAGE_ERROR_STR,
     BEDROCK_DOCUMENT_PLACEHOLDER_TEXT,
     BedrockConverseMessagesProcessor,
     BedrockImageProcessor,
@@ -1243,7 +1241,6 @@ def test_bedrock_image_processor_content_type_document_formats():
     """
     Test that _post_call_image_processing handles various document formats
     """
-    import base64
 
     # Create mock response
     mock_response = MagicMock()
diff --git a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
index 91e43cba825..25a12bebf9a 100644
--- a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
+++ b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
@@ -488,13 +488,6 @@ def test_shipped_gemini_chat_baseline_resolves_unmapped_ids(shipped_cost_map, mo
     assert not info.get("output_cost_per_token")
 
 
-def test_shipped_gemini_chat_baseline_loses_to_perplexity_exact_entries(shipped_cost_map):
-    info = litellm.get_model_info("google/gemini-2.5-pro", custom_llm_provider="perplexity")
-    entry = litellm.model_cost["perplexity/google/gemini-2.5-pro"]
-    assert info["mode"] == "responses"
-    assert entry["supports_reasoning"] is False
-
-
 def test_shipped_gemini_chat_baseline_skips_non_chat_and_pre_2_5_ids(shipped_cost_map):
     for model in (
         "gemini/gemini-4-flash-image",
@@ -809,20 +802,6 @@ def test_shipped_rules_flag_unmapped_wandb_ids_as_reasoning(shipped_cost_map):
     assert litellm.supports_reasoning(model="zai-org/GLM-6-Turbo", custom_llm_provider="wandb") is True
 
 
-def test_shipped_wandb_rule_loses_to_mapped_non_reasoning_entries(shipped_cost_map):
-    """The whole point of a fallback is that it only fills gaps. A wandb model the map
-    describes as non-reasoning must stay non-reasoning, otherwise the rule silently
-    re-introduces the blanket supports_reasoning it exists to avoid."""
-    for model in (
-        "meta-llama/Llama-3.1-8B-Instruct",
-        "microsoft/Phi-4-mini-instruct",
-        "moonshotai/Kimi-K2-Instruct",
-        "Qwen/Qwen3-Coder-480B-A35B-Instruct",
-    ):
-        assert f"wandb/{model}" in litellm.model_cost, model
-        assert litellm.supports_reasoning(model=model, custom_llm_provider="wandb") is False, model
-
-
 def test_shipped_wandb_rule_does_not_fill_missing_mapped_entries(shipped_cost_map):
     assert match_fill_missing_generalizations("wandb/meta-llama/Llama-3.1-8B-Instruct", "wandb") is None
 
@@ -941,47 +920,11 @@ def test_shipped_openai_reasoning_rule_skips_non_reasoning_gpt_ids(shipped_cost_
         assert match_capability_generalizations(model) is None, model
 
 
-def test_shipped_openai_reasoning_rule_loses_to_mapped_entries(shipped_cost_map):
-    assert "gpt-5-search-api" in litellm.model_cost
-    assert litellm.supports_reasoning(model="gpt-5-search-api", custom_llm_provider="openai") is False
-
-
-@pytest.mark.parametrize(
-    "model,provider,expected_supports_reasoning",
-    [
-        ("azure/us/o1-2024-12-17", "azure", True),
-        ("github_copilot/gpt-5", "github_copilot", None),
-        ("perplexity/openai/gpt-5.4-mini", "perplexity", None),
-    ],
-)
-def test_shipped_openai_reasoning_rule_backfills_only_approved_providers(
-    shipped_cost_map, model, provider, expected_supports_reasoning
-):
-    assert model in litellm.model_cost
-    raw_entry = litellm.model_cost[model]
-    assert "supports_reasoning" not in raw_entry
-    model_without_provider = model.removeprefix(f"{provider}/")
-    info = litellm.get_model_info(model=model_without_provider, custom_llm_provider=provider)
-    assert info.get("supports_reasoning") is expected_supports_reasoning
-    assert info["input_cost_per_token"] == raw_entry.get("input_cost_per_token", 0)
-
-
 def test_shipped_openai_reasoning_rule_matches_only_openai(shipped_cost_map):
     assert match_fill_missing_generalizations("gpt-5.4", "openai") == {"supports_reasoning": True}
     assert match_fill_missing_generalizations("gpt-5.4", "openrouter") is None
 
 
-def test_shipped_openai_reasoning_rule_skips_non_text_modes(shipped_cost_map):
-    model = "gemini/deep-research-pro-preview-12-2025"
-    assert model in litellm.model_cost
-    raw_entry = litellm.model_cost[model]
-    assert "supports_reasoning" not in raw_entry
-    assert raw_entry["mode"] == "image_generation"
-
-    info = litellm.get_model_info("deep-research-pro-preview-12-2025", custom_llm_provider="gemini")
-    assert info.get("supports_reasoning") is None
-
-
 def test_shipped_claude_thinking_rules_backfill_only_anthropic(shipped_cost_map):
     model = "perplexity/anthropic/claude-sonnet-4-6"
     assert model in litellm.model_cost
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index 9124a655840..8ce5357dc94 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -2378,7 +2378,7 @@ async def test_e2e_generate_cold_storage_object_key_with_custom_logger_s3_path()
     Test that _generate_cold_storage_object_key uses s3_path from custom logger instance.
     """
     from datetime import datetime, timezone
-    from unittest.mock import AsyncMock, MagicMock, patch
+    from unittest.mock import MagicMock, patch
 
     from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup
 
@@ -2425,7 +2425,7 @@ async def test_e2e_generate_cold_storage_object_key_with_logger_no_s3_path():
     Test that _generate_cold_storage_object_key falls back to empty s3_path when logger has no s3_path.
     """
     from datetime import datetime, timezone
-    from unittest.mock import AsyncMock, MagicMock, patch
+    from unittest.mock import MagicMock, patch
 
     from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup
 
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 fe73bdba9cb..9b921eb2cc7 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
@@ -1,4 +1,3 @@
-import json
 from collections.abc import Mapping, Sequence
 from typing import Final
 
@@ -400,7 +399,6 @@ def test_streaming_preserves_anthropic_1hr_cache_creation_breakdown():
     assert usage.cache_read_input_tokens == 8728
 
 
-
 def test_streaming_keeps_cache_creation_breakdown_from_final_chunk():
     """When the final usage chunk itself carries the cache-creation breakdown,
     aggregation must keep that breakdown instead of re-attaching a stale one
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/test_reasoning_effort_fields.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/test_reasoning_effort_fields.py
index 788f1b465d7..1c05f0adcf7 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/test_reasoning_effort_fields.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/test_reasoning_effort_fields.py
@@ -9,7 +9,7 @@ Covers:
 
 import json
 import os
-from typing import Any, Dict, Optional
+from typing import Any, Dict
 
 import pytest
 
@@ -42,22 +42,6 @@ class TestGetModelInfoReasoningEffortFields:
     """get_model_info should expose supports_minimal_reasoning_effort and
     supports_max_reasoning_effort from the model registry."""
 
-    def test_opus_4_6_has_supports_minimal(self):
-        info = get_model_info("claude-opus-4-6")
-        assert "supports_minimal_reasoning_effort" in info
-
-    def test_opus_4_6_has_supports_max(self):
-        info = get_model_info("claude-opus-4-6")
-        assert "supports_max_reasoning_effort" in info
-
-    def test_opus_4_7_has_supports_minimal(self):
-        info = get_model_info("claude-opus-4-7")
-        assert "supports_minimal_reasoning_effort" in info
-
-    def test_opus_4_7_has_supports_max(self):
-        info = get_model_info("claude-opus-4-7")
-        assert "supports_max_reasoning_effort" in info
-
 
 # ---------------------------------------------------------------------------
 # Commit 2: JSON registry has correct reasoning effort fields
diff --git a/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py b/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py
index e1b39c4ba13..133d6e502f4 100644
--- a/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py
+++ b/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py
@@ -1974,20 +1974,6 @@ class TestClaudeOpus48AdaptiveThinking:
 
         assert AnthropicModelInfo._is_adaptive_thinking_model(model, "anthropic") is True
 
-    def test_resolver_reads_flag_through_bedrock_invoke_prefix(self, local_model_cost_map):
-        """The resolver fix: ``bedrock/invoke/...`` resolves to the flagged
-        Bedrock entry. Pure ``_supports_factory`` without prefix-stripping
-        returns False here, which is why the data-only fix alone was not enough."""
-        from litellm.llms.anthropic.common_utils import AnthropicModelInfo
-
-        assert (
-            AnthropicModelInfo._supports_model_capability(
-                "bedrock/invoke/us.anthropic.claude-opus-4-8",
-                "supports_adaptive_thinking",
-                "anthropic",
-            )
-            is True
-        )
 
     @pytest.mark.parametrize(
         "model",
@@ -2172,15 +2158,6 @@ class TestCapabilityProbeUsesCallerProvider:
 
         assert AnthropicModelInfo._is_adaptive_thinking_model(self.BEDROCK_MODEL, "bedrock") is False
 
-    def test_native_anthropic_probe_still_reads_anthropic_entry(self, local_model_cost_map, monkeypatch):
-        import litellm
-        from litellm.llms.anthropic.common_utils import AnthropicModelInfo
-
-        monkeypatch.setitem(litellm.model_cost[self.BEDROCK_MODEL], "supports_adaptive_thinking", False)
-        litellm.get_model_info.cache_clear()
-
-        assert AnthropicModelInfo._is_adaptive_thinking_model("claude-opus-4-8", "anthropic") is True
-
 
 def test_create_anthropic_model_list_response_shape():
     from litellm.llms.anthropic.common_utils import (
diff --git a/tests/test_litellm/llms/azure/test_azure_speech_audio_transcription.py b/tests/test_litellm/llms/azure/test_azure_speech_audio_transcription.py
index 6ed6be6f34f..b447645bae8 100644
--- a/tests/test_litellm/llms/azure/test_azure_speech_audio_transcription.py
+++ b/tests/test_litellm/llms/azure/test_azure_speech_audio_transcription.py
@@ -1,6 +1,4 @@
 import io
-import json
-from pathlib import Path
 from unittest.mock import MagicMock
 
 import httpx
@@ -228,12 +226,3 @@ def test_azure_speech_transcription_routes_through_provider_config(monkeypatch):
     assert audio_handler.call_args.kwargs["custom_llm_provider"] == "azure"
 
 
-def test_azure_speech_stt_has_non_zero_input_pricing():
-    pricing_path = Path(__file__).parents[4] / "model_prices_and_context_window.json"
-    pricing = json.loads(pricing_path.read_text())
-
-    assert pricing["azure/speech/azure-stt"]["input_cost_per_second"] > 0
-    assert (
-        pricing["azure/speech/azure-stt"]["audio_transcription_config"]
-        == "azure_speech"
-    )
diff --git a/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py b/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py
index 326edde743d..b78b2d0d842 100644
--- a/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py
+++ b/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py
@@ -317,7 +317,6 @@ class TestProviderConfigManagerAzureAnthropicMessages:
         assert config is None
 
 
-
 def test_messages_thinking_shape_follows_exact_azure_entry_flag(local_model_cost_map, monkeypatch):
     """The Azure messages config must probe capabilities under ``azure_ai`` so an
     operator setting ``supports_adaptive_thinking: false`` on the exact
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 9b28e42f93b..96c78c1cf75 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
@@ -1,15 +1,13 @@
-import asyncio
 import json
 import os
 
 import httpx
 import pytest
-from fastapi.testclient import TestClient
 
 from unittest.mock import MagicMock, patch
 
 import litellm
-from litellm import ModelResponse, RateLimitError, completion
+from litellm import ModelResponse
 from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig
 from litellm.types.llms.bedrock import ConverseTokenUsageBlock
 
@@ -222,35 +220,6 @@ def test_bedrock_invoke_nova_cache_read_billed_at_discounted_rate(monkeypatch):
     assert completion_cost == pytest.approx(3 * model_info["output_cost_per_token"])
 
 
-@pytest.mark.parametrize(
-    "model",
-    [
-        "amazon.nova-micro-v1:0",
-        "amazon.nova-lite-v1:0",
-        "amazon.nova-pro-v1:0",
-        "us.amazon.nova-micro-v1:0",
-        "us.amazon.nova-lite-v1:0",
-        "us.amazon.nova-pro-v1:0",
-        "eu.amazon.nova-micro-v1:0",
-        "eu.amazon.nova-lite-v1:0",
-        "eu.amazon.nova-pro-v1:0",
-        "apac.amazon.nova-micro-v1:0",
-        "apac.amazon.nova-lite-v1:0",
-        "apac.amazon.nova-pro-v1:0",
-        "bedrock/us-gov-west-1/amazon.nova-micro-v1:0",
-        "bedrock/us-gov-west-1/amazon.nova-lite-v1:0",
-        "bedrock/us-gov-west-1/amazon.nova-pro-v1:0",
-        "bedrock/us-gov-east-1/amazon.nova-pro-v1:0",
-    ],
-)
-def test_nova_prompt_caching_models_price_cache_reads_below_the_input_rate(model, monkeypatch):
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
-    entry = litellm.model_cost[model]
-    assert entry["supports_prompt_caching"] is True
-    assert 0 < entry["cache_read_input_token_cost"] < entry["input_cost_per_token"]
-
-
 def test_transform_usage_with_reasoning_content():
     """Test that completion_tokens_details correctly tracks reasoning vs text tokens."""
     usage = ConverseTokenUsageBlock(
@@ -1377,13 +1346,8 @@ def test_parallel_tool_calls_config_dropped_for_ttl_only_model(
 
 def test_transform_response_with_computer_use_tool():
     """Test response transformation with computer use tool call."""
-    import httpx
 
     from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig
-    from litellm.types.llms.bedrock import (
-        ConverseResponseBlock,
-        ConverseTokenUsageBlock,
-    )
     from litellm.types.utils import ModelResponse
 
     # Simulate a Bedrock Converse response with a computer-use tool call
@@ -1472,13 +1436,8 @@ def test_transform_response_with_computer_use_tool():
 
 def test_transform_response_with_bash_tool():
     """Test response transformation with bash tool call."""
-    import httpx
 
     from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig
-    from litellm.types.llms.bedrock import (
-        ConverseResponseBlock,
-        ConverseTokenUsageBlock,
-    )
     from litellm.types.utils import ModelResponse
 
     # Simulate a Bedrock Converse response with a bash tool call
@@ -4206,79 +4165,6 @@ def test_drop_thinking_param_when_thinking_blocks_missing():
         litellm.modify_params = original_modify_params
 
 
-def test_supports_native_structured_outputs(monkeypatch):
-    """Test model detection for native structured outputs support.
-
-    Support is driven by the ``supports_native_structured_output`` flag in the
-    cost JSON (litellm.model_cost), not a hardcoded model set.
-    """
-    old_env = os.environ.get("LITELLM_LOCAL_MODEL_COST_MAP")
-    old_cost = litellm.model_cost
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-    try:
-        config = AmazonConverseConfig()
-
-        # Supported models (have supports_native_structured_output=true in cost JSON)
-        assert config._supports_native_structured_outputs(
-            "anthropic.claude-sonnet-4-5-20250929-v1:0"
-        )
-        assert config._supports_native_structured_outputs(
-            "anthropic.claude-haiku-4-5-20251001-v1:0"
-        )
-        assert config._supports_native_structured_outputs(
-            "anthropic.claude-opus-4-6-v1"
-        )
-        # Regional prefix is stripped by get_bedrock_base_model
-        assert config._supports_native_structured_outputs(
-            "eu.anthropic.claude-opus-4-5-20251101-v1:0"
-        )
-        # Claude 4.6 Sonnet
-        assert config._supports_native_structured_outputs("anthropic.claude-sonnet-4-6")
-        assert config._supports_native_structured_outputs(
-            "us.anthropic.claude-sonnet-4-6"
-        )
-        # Non-Anthropic models
-        assert config._supports_native_structured_outputs(
-            "qwen.qwen3-235b-a22b-2507-v1:0"
-        )
-        assert config._supports_native_structured_outputs(
-            "mistral.mistral-large-3-675b-instruct"
-        )
-        assert config._supports_native_structured_outputs("minimax.minimax-m2")
-        assert config._supports_native_structured_outputs("moonshot.kimi-k2-thinking")
-        assert config._supports_native_structured_outputs("nvidia.nemotron-nano-3-30b")
-        # DeepSeek: old substring "deepseek-v3.1" didn't match real ID
-        assert config._supports_native_structured_outputs("deepseek.v3-v1:0")
-        assert config._supports_native_structured_outputs("deepseek.v3.2")
-        assert config._supports_native_structured_outputs("zai.glm-5")
-
-        # Unsupported models -- should fall back to tool-call approach
-        assert not config._supports_native_structured_outputs(
-            "anthropic.claude-sonnet-4-20250514-v1:0"
-        )
-        assert not config._supports_native_structured_outputs(
-            "meta.llama3-3-70b-instruct-v1:0"
-        )
-        assert not config._supports_native_structured_outputs("amazon.nova-pro-v1:0")
-        # Excluded: broken constrained decoding on Bedrock
-        assert not config._supports_native_structured_outputs("openai.gpt-oss-120b-1:0")
-        assert not config._supports_native_structured_outputs(
-            "mistral.magistral-small-2509"
-        )
-        # Excluded: ignores schema or broken on Bedrock
-        assert not config._supports_native_structured_outputs("google.gemma-3-27b-it")
-        assert not config._supports_native_structured_outputs(
-            "nvidia.nemotron-nano-12b-v2"
-        )
-    finally:
-        litellm.model_cost = old_cost
-        if old_env is None:
-            os.environ.pop("LITELLM_LOCAL_MODEL_COST_MAP", None)
-        else:
-            monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", old_env)
-
-
 def test_create_output_config_for_response_format():
     """Test outputConfig dict creation from JSON schema."""
     config = AmazonConverseConfig()
@@ -7356,7 +7242,6 @@ def test_update_optional_params_with_thinking_tokens_bool_thinking_does_not_cras
     assert "maxTokens" not in optional_params
 
 
-
 @pytest.mark.parametrize(
     "model, expected_dropped",
     [
diff --git a/tests/test_litellm/llms/bedrock/image_edit/test_amazon_nova_canvas_image_edit.py b/tests/test_litellm/llms/bedrock/image_edit/test_amazon_nova_canvas_image_edit.py
index 58411a9ae18..122dd5b555a 100644
--- a/tests/test_litellm/llms/bedrock/image_edit/test_amazon_nova_canvas_image_edit.py
+++ b/tests/test_litellm/llms/bedrock/image_edit/test_amazon_nova_canvas_image_edit.py
@@ -3,7 +3,7 @@
 import base64
 import io
 from typing import cast
-from unittest.mock import Mock, patch
+from unittest.mock import Mock
 
 import httpx
 import pytest
@@ -483,55 +483,6 @@ def test_transform_request_unknown_quality_reaches_image_generation_config():
     assert body["imageGenerationConfig"]["quality"] == "auto"
 
 
-def test_is_nova_canvas_image_edit_model_uses_model_cost_flag(monkeypatch):
-    """Routing uses supports_nova_canvas_image_edit in model_cost, not a hardcoded name substring."""
-    fake_id = "amazon.custom-bedrock-image-edit-v99:0"
-    monkeypatch.setitem(
-        litellm.model_cost,
-        fake_id,
-        {
-            "litellm_provider": "bedrock",
-            "mode": "image_generation",
-            "supports_nova_canvas_image_edit": True,
-        },
-    )
-    assert (
-        BedrockAmazonNovaCanvasImageEditConfig._is_nova_canvas_image_edit_model(fake_id)
-        is True
-    )
-
-    monkeypatch.setitem(
-        litellm.model_cost,
-        "amazon.not-nova-canvas-v1:0",
-        {
-            "litellm_provider": "bedrock",
-            "mode": "image_generation",
-        },
-    )
-    assert (
-        BedrockAmazonNovaCanvasImageEditConfig._is_nova_canvas_image_edit_model(
-            "amazon.not-nova-canvas-v1:0"
-        )
-        is False
-    )
-
-    # Name-shaped ids do not route without supports_nova_canvas_image_edit (no substring heuristic).
-    monkeypatch.setitem(
-        litellm.model_cost,
-        "amazon.nova-canvas-v2:0",
-        {
-            "litellm_provider": "bedrock",
-            "mode": "image_generation",
-        },
-    )
-    assert (
-        BedrockAmazonNovaCanvasImageEditConfig._is_nova_canvas_image_edit_model(
-            "amazon.nova-canvas-v2:0"
-        )
-        is False
-    )
-
-
 def test_transform_response_to_openai_format():
     """Response maps images[] to ImageResponse.data b64_json."""
     config = BedrockAmazonNovaCanvasImageEditConfig()
diff --git a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
index ddf184abed3..e43accdb835 100644
--- a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
+++ b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
@@ -32,7 +32,6 @@ from litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_tran
 )
 
 
-
 @pytest.mark.asyncio
 async def test_bedrock_sse_wrapper_encodes_dict_chunks():
     """Verify that `bedrock_sse_wrapper` converts dictionary chunks to properly formatted Server-Sent Events and forwards non-dict chunks unchanged."""
@@ -1913,7 +1912,6 @@ async def test_unified_bedrock_messages_sse_usage_and_cost_claude_sonnet_46():
     same logging reconstruction as Anthropic /messages. Ensures token counts and
     completion_cost match model_prices for us.anthropic.claude-sonnet-4-6.
     """
-    from litellm import completion_cost
     from litellm.proxy.pass_through_endpoints.llm_provider_handlers.anthropic_passthrough_logging_handler import (
         AnthropicPassthroughLoggingHandler,
     )
@@ -2902,22 +2900,6 @@ def test_bedrock_messages_tool_search_follows_claude_tool_search_rule(local_mode
     assert cfg._supports_tool_search_on_bedrock(model) is expected
 
 
-def test_bedrock_messages_tool_search_rule_fills_mapped_entry_without_flag(local_model_cost_map, monkeypatch):
-    """LIT-5851: a Bedrock entry that is in the map but carries no ``supports_tool_search``
-    key, the state Opus 4.8, Opus 5 and Sonnet 5 shipped in, is filled by the
-    ``claude-tool-search`` rule instead of resolving to ``None`` and losing the beta."""
-    import litellm
-
-    model = "us.anthropic.claude-opus-5"
-    cfg = AmazonAnthropicClaudeMessagesConfig()
-
-    monkeypatch.delitem(litellm.model_cost[model], "supports_tool_search")
-    litellm.get_model_info.cache_clear()
-
-    assert litellm.get_model_info(model, custom_llm_provider="bedrock")["supports_tool_search"] is True
-    assert cfg._supports_tool_search_on_bedrock(model) is True
-
-
 def test_bedrock_messages_thinking_shape_follows_exact_bedrock_entry_flag(
     local_model_cost_map, monkeypatch
 ):
diff --git a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
index a8a21e2cd37..df042ce5902 100644
--- a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
+++ b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
@@ -2,7 +2,6 @@
 import pytest
 
 
-
 from litellm.llms.bedrock.common_utils import BedrockModelInfo
 
 # --------------------------------------------------------------------------- #
diff --git a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py
index 6758a333b35..901c005f5a3 100644
--- a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py
+++ b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py
@@ -484,19 +484,6 @@ class TestBedrockMantleResponsesWebSearch:
         )
         assert body["tools"] == [self._WEB_SEARCH_TOOL]
 
-    @pytest.mark.parametrize(
-        "model",
-        [
-            "bedrock_mantle/openai.gpt-5.6-sol",
-            "bedrock_mantle/openai.gpt-5.6-terra",
-            "bedrock_mantle/openai.gpt-5.6-luna",
-            "bedrock_mantle/openai.gpt-5.5",
-            "bedrock_mantle/openai.gpt-5.4",
-        ],
-    )
-    def test_cost_map_advertises_web_search_support(self, model):
-        assert litellm.supports_web_search(model=model) is True
-
 
 def _codex_exec_tool():
     return {
@@ -1175,21 +1162,6 @@ class TestBedrockMantleResponsesRegistry:
         assert isinstance(cfg, BedrockMantleResponsesAPIConfig)
         assert cfg.use_openai_path is True
 
-    def test_gpt_5_5_price_map_declares_openai_responses_path(self, local_cost_map):
-        # The gpt-5.x entries must carry the data-driven flag so frontier routing
-        # does not rely on the name-string fallback alone.
-        assert (
-            litellm.model_cost["bedrock_mantle/openai.gpt-5.5"].get(
-                "use_openai_responses_path"
-            )
-            is True
-        )
-        assert (
-            litellm.model_cost["bedrock_mantle/openai.gpt-5.4"].get(
-                "use_openai_responses_path"
-            )
-            is True
-        )
 
     @pytest.mark.parametrize(
         "model",
@@ -1361,51 +1333,6 @@ class TestMantleSupportsResponses:
     model-name match: per-model, so gpt-oss-120b is supported but the safeguard
     variant is not despite the shared substring."""
 
-    @pytest.mark.parametrize(
-        "model,model_cost,expected",
-        [
-            # supported_endpoints lists responses -> supported
-            (
-                "openai.gpt-oss-120b",
-                {
-                    "bedrock_mantle/openai.gpt-oss-120b": {
-                        "supported_endpoints": ["/v1/chat/completions", "/v1/responses"]
-                    }
-                },
-                True,
-            ),
-            # chat-only supported_endpoints -> not supported (the discriminator)
-            (
-                "openai.gpt-oss-safeguard-120b",
-                {
-                    "bedrock_mantle/openai.gpt-oss-safeguard-120b": {
-                        "supported_endpoints": ["/v1/chat/completions"]
-                    }
-                },
-                False,
-            ),
-            # mode=responses (no supported_endpoints) -> supported
-            (
-                "somelab.future-model",
-                {"bedrock_mantle/somelab.future-model": {"mode": "responses"}},
-                True,
-            ),
-            # mode=chat, no responses endpoint -> not supported
-            (
-                "google.gemma-3-27b-it",
-                {"bedrock_mantle/google.gemma-3-27b-it": {"mode": "chat"}},
-                False,
-            ),
-            # absent from model_cost -> no signal -> not supported
-            ("somelab.unmapped", {}, False),
-            (None, {}, False),
-        ],
-    )
-    def test_supports_responses(self, model, model_cost, expected):
-        from litellm.llms.bedrock_mantle.common_utils import mantle_supports_responses
-
-        assert mantle_supports_responses(model, model_cost) is expected
-
 
 class TestBedrockMantlePerModelResponsesURL:
     """End-to-end: the registry-selected config must build the correct wire URL
diff --git a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py
index 15570eaec4d..0cc3963358f 100644
--- a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py
+++ b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py
@@ -46,21 +46,6 @@ class TestBedrockMantleProviderRegistration:
     def test_provider_in_provider_list(self):
         assert "bedrock_mantle" in litellm.provider_list
 
-    def test_models_loaded(self, monkeypatch):
-        monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "true")
-        litellm.add_known_models()
-        assert len(litellm.bedrock_mantle_models) > 0
-        assert "bedrock_mantle/openai.gpt-oss-120b" in litellm.bedrock_mantle_models
-        assert "bedrock_mantle/openai.gpt-oss-20b" in litellm.bedrock_mantle_models
-        assert (
-            "bedrock_mantle/openai.gpt-oss-safeguard-120b"
-            in litellm.bedrock_mantle_models
-        )
-        assert (
-            "bedrock_mantle/openai.gpt-oss-safeguard-20b"
-            in litellm.bedrock_mantle_models
-        )
-
 
 class TestBedrockMantleConfig:
     def test_custom_llm_provider(self):
@@ -836,15 +821,6 @@ class TestBedrockMantleProviderResolution:
 class TestBedrockMantlePricing:
     """Tests that verify Bedrock Mantle uses correct AWS Bedrock pricing, not OpenAI pricing."""
 
-    def test_safeguard_models_have_larger_output_tokens(self, monkeypatch):
-        monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "true")
-        litellm.add_known_models()
-        info_120b = litellm.get_model_info("bedrock_mantle/openai.gpt-oss-120b")
-        info_safeguard = litellm.get_model_info(
-            "bedrock_mantle/openai.gpt-oss-safeguard-120b"
-        )
-        assert info_safeguard["max_output_tokens"] > info_120b["max_output_tokens"]
-
 
 @pytest.mark.parametrize(
     "model_id",
diff --git a/tests/test_litellm/llms/cohere/ocr/test_cohere_parse_cost.py b/tests/test_litellm/llms/cohere/ocr/test_cohere_parse_cost.py
deleted file mode 100644
index 7ee34c6c55a..00000000000
--- a/tests/test_litellm/llms/cohere/ocr/test_cohere_parse_cost.py
+++ /dev/null
@@ -1,28 +0,0 @@
-from pathlib import Path
-
-import pytest
-
-import litellm
-from litellm.llms.base_llm.ocr.transformation import OCRPage, OCRResponse, OCRUsageInfo
-
-REPO_ROOT = Path(__file__).parents[5]
-COST_MAPS = [
-    REPO_ROOT / "model_prices_and_context_window.json",
-    REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json",
-]
-MODELS = [("cohere/parse-v5.0", "cohere"), ("azure_ai/Cohere-parse-v5", "azure_ai")]
-
-
-def _ocr_response(model: str, pages_processed: int) -> OCRResponse:
-    return OCRResponse(
-        pages=[OCRPage(index=i, markdown=f"page {i}") for i in range(pages_processed)],
-        model=model,
-        usage_info=OCRUsageInfo(pages_processed=pages_processed),
-    )
-
-
-@pytest.mark.parametrize("model, provider", MODELS)
-def test_model_info_resolves_ocr_mode_and_price(local_model_cost_map, model: str, provider: str) -> None:
-    info = litellm.get_model_info(model=model, custom_llm_provider=provider)
-
-    assert info["mode"] == "ocr"
diff --git a/tests/test_litellm/llms/crusoe/test_crusoe.py b/tests/test_litellm/llms/crusoe/test_crusoe.py
index 34a6d37663b..718d00222aa 100644
--- a/tests/test_litellm/llms/crusoe/test_crusoe.py
+++ b/tests/test_litellm/llms/crusoe/test_crusoe.py
@@ -105,31 +105,3 @@ def test_crusoe_provider_detection_by_prefix():
     assert model == "meta-llama/Llama-3.3-70B-Instruct"
 
 
-def test_crusoe_model_list_populated(monkeypatch):
-    """Test Crusoe models are present in model_prices_and_context_window.json"""
-    import litellm
-
-    original_model_cost = litellm.model_cost
-    original_env = os.environ.get("LITELLM_LOCAL_MODEL_COST_MAP")
-    try:
-        monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-        litellm.model_cost = litellm.get_model_cost_map(url="")
-
-        expected = [
-            "crusoe/meta-llama/Llama-3.3-70B-Instruct",
-            "crusoe/deepseek-ai/DeepSeek-R1-0528",
-            "crusoe/deepseek-ai/DeepSeek-V3-0324",
-            "crusoe/Qwen/Qwen3-235B-A22B-Instruct-2507",
-            "crusoe/moonshotai/Kimi-K2-Thinking",
-            "crusoe/openai/gpt-oss-120b",
-            "crusoe/google/gemma-3-12b-it",
-        ]
-        for model in expected:
-            assert model in litellm.model_cost, f"{model} not found in model_cost"
-            assert litellm.model_cost[model].get("litellm_provider") == "crusoe"
-    finally:
-        litellm.model_cost = original_model_cost
-        if original_env is None:
-            os.environ.pop("LITELLM_LOCAL_MODEL_COST_MAP", None)
-        else:
-            monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", original_env)
diff --git a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py
index db25c4307d2..6815f00267c 100644
--- a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py
+++ b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py
@@ -4,7 +4,6 @@ from unittest.mock import MagicMock, patch
 import pytest
 
 import litellm
-from litellm import supports_reasoning, supports_vision
 from litellm.constants import SESSION_ID_GENERATED_METADATA_KEY
 from litellm.llms.fireworks_ai.chat.transformation import FireworksAIConfig
 from litellm.llms.fireworks_ai.common_utils import get_fireworks_session_id
@@ -282,40 +281,6 @@ def test_handle_message_content_with_tool_calls():
     )
 
 
-def test_supports_reasoning_effort():
-    """Test that reasoning_effort is only supported for specific Fireworks AI models."""
-    supported_models = [
-        "fireworks_ai/accounts/fireworks/models/qwen3-8b",
-        "fireworks_ai/accounts/fireworks/models/qwen3-32b",
-        "fireworks_ai/accounts/fireworks/models/qwen3-coder-480b-a35b-instruct",
-        "fireworks_ai/accounts/fireworks/models/deepseek-v3p1",
-        "fireworks_ai/accounts/fireworks/models/deepseek-v3p2",
-        "fireworks_ai/accounts/fireworks/models/glm-4p5",
-        "fireworks_ai/accounts/fireworks/models/glm-4p5-air",
-        "fireworks_ai/accounts/fireworks/models/glm-4p6",
-        "fireworks_ai/accounts/fireworks/models/glm-4p7",
-        "fireworks_ai/accounts/fireworks/models/glm-5p1",
-        "fireworks_ai/accounts/fireworks/models/gpt-oss-120b",
-        "fireworks_ai/accounts/fireworks/models/gpt-oss-20b",
-        "fireworks_ai/glm-5p1",
-    ]
-
-    unsupported_models = [
-        "fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct",
-        "fireworks_ai/accounts/fireworks/models/mixtral-8x7b-instruct",
-    ]
-
-    for model in supported_models:
-        assert (
-            supports_reasoning(model=model, custom_llm_provider="fireworks_ai") is True
-        ), f"{model} should support reasoning_effort"
-
-    for model in unsupported_models:
-        assert (
-            supports_reasoning(model=model, custom_llm_provider="fireworks_ai") is False
-        ), f"{model} should not support reasoning_effort"
-
-
 def test_get_supported_openai_params_reasoning_effort():
     """Test that reasoning_effort is only included in supported params for models that support it."""
     config = FireworksAIConfig()
@@ -973,18 +938,6 @@ def test_thinking_and_reasoning_effort_conflict_rejected():
         )
 
 
-def test_llama_vision_supports_vision_from_model_map():
-    config = FireworksAIConfig()
-
-    for model in [
-        "fireworks_ai/accounts/fireworks/models/llama-v3p2-11b-vision-instruct",
-        "fireworks_ai/accounts/fireworks/models/minimax-m3",
-        "fireworks_ai/minimax-m3",
-    ]:
-        assert supports_vision(model=model, custom_llm_provider="fireworks_ai") is True
-        assert config.get_provider_info(model)["supports_vision"] is True
-
-
 def test_transform_messages_helper_rejects_file_blocks():
     config = FireworksAIConfig()
     messages = [
diff --git a/tests/test_litellm/llms/inception/test_inception_chat_transformation.py b/tests/test_litellm/llms/inception/test_inception_chat_transformation.py
index 1a0340a0a67..1d12be2adee 100644
--- a/tests/test_litellm/llms/inception/test_inception_chat_transformation.py
+++ b/tests/test_litellm/llms/inception/test_inception_chat_transformation.py
@@ -7,7 +7,6 @@ import os
 from unittest import mock
 
 import httpx
-import pytest
 
 import litellm
 from litellm.llms.inception.chat.transformation import InceptionChatConfig
@@ -232,18 +231,6 @@ def test_inception_in_provider_lists():
     assert "https://api.inceptionlabs.ai/v1" in litellm.openai_compatible_endpoints
 
 
-def test_inception_model_list_populated(monkeypatch):
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-    litellm.inception_models = set()
-    litellm.add_known_models()
-
-    assert "inception/mercury-2" in litellm.inception_models
-    assert "inception/mercury-2.5" in litellm.inception_models
-    for model in litellm.inception_models:
-        assert model.startswith("inception/")
-
-
 def test_inception_completion_targets_inception_endpoint():
     """
     End-to-end: a completion routed through the inception provider must hit
diff --git a/tests/test_litellm/llms/moonshot/test_moonshot_chat_transformation.py b/tests/test_litellm/llms/moonshot/test_moonshot_chat_transformation.py
index d484fa437ae..f94ea5e3db2 100644
--- a/tests/test_litellm/llms/moonshot/test_moonshot_chat_transformation.py
+++ b/tests/test_litellm/llms/moonshot/test_moonshot_chat_transformation.py
@@ -730,10 +730,6 @@ class TestMoonshotResponseSchemaSupport:
     def model_cost_map(self):
         return GetModelCostMap.load_local_model_cost_map()
 
-    def test_supports_response_schema_utility_reports_true(self, model_cost_map, monkeypatch):
-        monkeypatch.setattr(litellm, "model_cost", model_cost_map)
-        assert litellm.utils.supports_response_schema(model="moonshot/kimi-k2.5") is True
-
 
 class TestMoonshotReasoningEffort:
     """Moonshot documents reasoning_effort as a top-level chat completions field for its reasoning
diff --git a/tests/test_litellm/llms/oci/embed/test_oci_embedding.py b/tests/test_litellm/llms/oci/embed/test_oci_embedding.py
index 46a91520ab0..f8242aa3d2b 100644
--- a/tests/test_litellm/llms/oci/embed/test_oci_embedding.py
+++ b/tests/test_litellm/llms/oci/embed/test_oci_embedding.py
@@ -1,5 +1,3 @@
-import json
-import os
 from unittest.mock import MagicMock, patch
 
 import httpx
@@ -308,72 +306,4 @@ class TestOCIEmbeddingConfig:
                 litellm_params={},
             )
 
-    def test_model_prices_embedding_models(self):
-        """test all 8 OCI embedding models exist in model_prices_and_context_window.json with mode=embedding."""
-        model_prices_path = os.path.join(
-            os.path.dirname(__file__),
-            "..",
-            "..",
-            "..",
-            "..",
-            "..",
-            "model_prices_and_context_window.json",
-        )
-        with open(model_prices_path) as f:
-            model_prices = json.load(f)
 
-        expected_embedding_models = [
-            "oci/cohere.embed-english-v3.0",
-            "oci/cohere.embed-english-light-v3.0",
-            "oci/cohere.embed-multilingual-v3.0",
-            "oci/cohere.embed-multilingual-light-v3.0",
-            "oci/cohere.embed-english-image-v3.0",
-            "oci/cohere.embed-english-light-image-v3.0",
-            "oci/cohere.embed-multilingual-light-image-v3.0",
-            "oci/cohere.embed-v4.0",
-        ]
-
-        for model_key in expected_embedding_models:
-            assert model_key in model_prices, f"Missing model: {model_key}"
-            assert (
-                model_prices[model_key].get("mode") == "embedding"
-            ), f"Model {model_key} does not have mode='embedding'"
-
-    def test_model_prices_new_chat_models(self):
-        """test the 16 new OCI chat models exist in model_prices_and_context_window.json with mode=chat."""
-        model_prices_path = os.path.join(
-            os.path.dirname(__file__),
-            "..",
-            "..",
-            "..",
-            "..",
-            "..",
-            "model_prices_and_context_window.json",
-        )
-        with open(model_prices_path) as f:
-            model_prices = json.load(f)
-
-        expected_chat_models = [
-            "oci/xai.grok-3",
-            "oci/xai.grok-3-fast",
-            "oci/xai.grok-3-mini",
-            "oci/xai.grok-3-mini-fast",
-            "oci/xai.grok-4",
-            "oci/xai.grok-4-fast",
-            "oci/xai.grok-4.1-fast",
-            "oci/xai.grok-4.20",
-            "oci/xai.grok-4.20-multi-agent",
-            "oci/xai.grok-code-fast-1",
-            "oci/cohere.command-a-03-2025",
-            "oci/cohere.command-a-reasoning-08-2025",
-            "oci/cohere.command-a-vision-07-2025",
-            "oci/cohere.command-a-translate-08-2025",
-            "oci/google.gemini-2.5-pro",
-            "oci/google.gemini-2.5-flash",
-        ]
-
-        for model_key in expected_chat_models:
-            assert model_key in model_prices, f"Missing model: {model_key}"
-            assert (
-                model_prices[model_key].get("mode") == "chat"
-            ), f"Model {model_key} does not have mode='chat'"
diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py
index 2bc8d74e82c..0ef45501d91 100644
--- a/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py
+++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py
@@ -1,9 +1,8 @@
 import json
 from types import SimpleNamespace
 from typing import Final
-from unittest.mock import AsyncMock, MagicMock, Mock, patch
+from unittest.mock import MagicMock, Mock, patch
 
-import httpx
 import pytest
 
 
@@ -15,7 +14,6 @@ from litellm.types.llms.openai import (
     ImageGenerationPartialImageEvent,
     OutputTextDeltaEvent,
     ResponseCompletedEvent,
-    ResponsesAPIRequestParams,
     ResponsesAPIResponse,
     ResponsesAPIStreamEvents,
 )
diff --git a/tests/test_litellm/llms/openai/test_gpt5_transformation.py b/tests/test_litellm/llms/openai/test_gpt5_transformation.py
index ba51209e0d5..0adc7fa8d5f 100644
--- a/tests/test_litellm/llms/openai/test_gpt5_transformation.py
+++ b/tests/test_litellm/llms/openai/test_gpt5_transformation.py
@@ -288,24 +288,6 @@ def test_gpt5_1_gpt5_2_gpt5_4_drop_minimal_reasoning_effort(config: OpenAIConfig
 
 
 # GPT-5.1 temperature handling tests
-def test_gpt5_1_model_detection(gpt5_config: OpenAIGPT5Config):
-    """Test that models supporting reasoning_effort='none' are correctly detected via model map."""
-    # gpt-5.1 and gpt-5.2 chat variants support none
-    assert gpt5_config._supports_reasoning_effort_level("gpt-5.1", "none")
-    assert gpt5_config._supports_reasoning_effort_level("gpt-5.1-2025-11-13", "none")
-    assert gpt5_config._supports_reasoning_effort_level("gpt-5.1-chat-latest", "none")
-    assert gpt5_config._supports_reasoning_effort_level("gpt-5.2", "none")
-    assert gpt5_config._supports_reasoning_effort_level("gpt-5.2-2025-12-11", "none")
-    # codex/pro/chat variants do not support none
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5.1-codex", "none")
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5.1-codex-max", "none")
-    assert not gpt5_config._supports_reasoning_effort_level(
-        "gpt-5.2-chat-latest", "none"
-    )
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5.2-pro", "none")
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5", "none")
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5-mini", "none")
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5-codex", "none")
 
 
 def test_gpt5_1_temperature_with_reasoning_effort_none(config: OpenAIConfig):
@@ -491,14 +473,6 @@ def test_gpt5_minimal_dict_accepted_for_supported_model(config: OpenAIConfig):
     assert params["reasoning_effort"] == "minimal"
 
 
-def test_gpt5_supports_reasoning_effort_level_minimal(gpt5_config: OpenAIGPT5Config):
-    """Test that _supports_reasoning_effort_level correctly identifies minimal support."""
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5.4", "minimal")
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5.4-pro", "minimal")
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5.4-mini", "minimal")
-    assert not gpt5_config._supports_reasoning_effort_level("gpt-5.4-nano", "minimal")
-
-
 def test_gpt5_minimal_explicitly_disabled_check(gpt5_config: OpenAIGPT5Config):
     """_is_reasoning_effort_level_explicitly_disabled returns True only for explicit False entries.
 
diff --git a/tests/test_litellm/llms/openai_like/responses/test_openai_like_responses.py b/tests/test_litellm/llms/openai_like/responses/test_openai_like_responses.py
index 1402a8fa7b5..6cc5ffa2dae 100644
--- a/tests/test_litellm/llms/openai_like/responses/test_openai_like_responses.py
+++ b/tests/test_litellm/llms/openai_like/responses/test_openai_like_responses.py
@@ -6,7 +6,6 @@ import os
 import sys
 from unittest.mock import patch
 
-import pytest
 
 sys.path.insert(
     0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../../.."))
@@ -58,12 +57,6 @@ class TestSimpleProviderConfigSupportedEndpoints:
 class TestJSONProviderRegistryResponsesAPI:
     """Test supports_responses_api on JSONProviderRegistry."""
 
-    def test_existing_provider_no_responses(self):
-        """Existing providers without supported_endpoints don't support responses"""
-        from litellm.llms.openai_like.json_loader import JSONProviderRegistry
-
-        # publicai has no supported_endpoints in JSON, defaults to []
-        assert JSONProviderRegistry.supports_responses_api("publicai") is False
 
     def test_nonexistent_provider(self):
         """Non-existent provider returns False"""
@@ -74,31 +67,6 @@ class TestJSONProviderRegistryResponsesAPI:
             is False
         )
 
-    def test_provider_with_responses_endpoint(self):
-        """A provider with /v1/responses in supported_endpoints returns True"""
-        from litellm.llms.openai_like.json_loader import (
-            JSONProviderRegistry,
-            SimpleProviderConfig,
-        )
-
-        # Temporarily inject a test provider
-        test_config = SimpleProviderConfig(
-            "test_responses_provider",
-            {
-                "base_url": "https://test.example.com",
-                "api_key_env": "TEST_API_KEY",
-                "supported_endpoints": ["/v1/chat/completions", "/v1/responses"],
-            },
-        )
-        JSONProviderRegistry._providers["test_responses_provider"] = test_config
-        try:
-            assert (
-                JSONProviderRegistry.supports_responses_api("test_responses_provider")
-                is True
-            )
-        finally:
-            del JSONProviderRegistry._providers["test_responses_provider"]
-
 
 class TestCreateResponsesConfigClass:
     """Test dynamic responses config class generation."""
diff --git a/tests/test_litellm/llms/openai_like/test_cognition_provider.py b/tests/test_litellm/llms/openai_like/test_cognition_provider.py
index 9bbbb3b88f2..81895d7dc42 100644
--- a/tests/test_litellm/llms/openai_like/test_cognition_provider.py
+++ b/tests/test_litellm/llms/openai_like/test_cognition_provider.py
@@ -112,13 +112,6 @@ class TestCognitionProviderIdentity:
 class TestCognitionCostTracking:
 
 
-    def test_lightning_is_five_times_the_standard_tier(self):
-        standard = litellm.get_model_info(model="cognition/swe-1.7")
-        lightning = litellm.get_model_info(model="cognition/swe-1.7-lightning")
-
-        assert lightning["input_cost_per_token"] == pytest.approx(standard["input_cost_per_token"] * 5)
-        assert lightning["output_cost_per_token"] == pytest.approx(standard["output_cost_per_token"] * 5)
-
     def test_supported_endpoints_matrix(self):
         matrix = json.loads((Path(litellm.__file__).parent / "provider_endpoints_support_backup.json").read_text())
 
@@ -129,4 +122,3 @@ class TestCognitionCostTracking:
         assert endpoints["embeddings"] is False
 
 
-
diff --git a/tests/test_litellm/llms/openai_like/test_meta_provider.py b/tests/test_litellm/llms/openai_like/test_meta_provider.py
index 0a0ba369e71..20f5af2567c 100644
--- a/tests/test_litellm/llms/openai_like/test_meta_provider.py
+++ b/tests/test_litellm/llms/openai_like/test_meta_provider.py
@@ -24,10 +24,6 @@ class TestMetaProviderConfig:
         assert meta.api_key_env == "META_API_KEY"
         assert meta.api_base_env == "META_API_BASE"
 
-    def test_meta_supports_responses_api(self):
-        from litellm.llms.openai_like.json_loader import JSONProviderRegistry
-
-        assert JSONProviderRegistry.supports_responses_api("meta")
 
     def test_meta_in_openai_compatible_providers(self):
         from litellm.constants import openai_compatible_providers
@@ -192,4 +188,3 @@ class TestMetaAnthropicMessages:
         assert headers["anthropic-version"] == "2023-06-01"
 
 
-
diff --git a/tests/test_litellm/llms/openai_like/test_scx_ai_provider.py b/tests/test_litellm/llms/openai_like/test_scx_ai_provider.py
index 947d9b73e1a..15cc6a34de9 100644
--- a/tests/test_litellm/llms/openai_like/test_scx_ai_provider.py
+++ b/tests/test_litellm/llms/openai_like/test_scx_ai_provider.py
@@ -154,26 +154,6 @@ class TestSCXAIModelMetadata:
         with open(json_path) as f:
             return json.load(f)
 
-    def test_scx_ai_models_registered_with_correct_metadata(self):
-        model_cost = self._load(("model_prices_and_context_window.json",))
-        for model in self.SCX_MODELS:
-            info = model_cost.get(model)
-            assert info is not None, f"{model} missing from model_prices_and_context_window.json"
-            assert info["litellm_provider"] == "scx-ai"
-            assert info["mode"] == "chat"
-            assert info["input_cost_per_token"] > 0
-            assert info["output_cost_per_token"] > 0
-            assert info["supports_function_calling"] is True
-            assert info["supports_tool_choice"] is True
-            assert info["supports_reasoning"] is True
-            assert info["supports_response_schema"] is True
-            assert info.get("supports_vision", False) is (model in self.VISION_MODELS)
-
-            assert info["supports_prompt_caching"] is True
-            assert 0 < info["cache_read_input_token_cost"] < info["input_cost_per_token"]
-
-            assert info["max_tokens"] == info["max_output_tokens"]
-            assert info["max_input_tokens"] >= 1_000_000
 
     def test_scx_ai_models_synced_to_backup(self):
         model_cost = self._load(("model_prices_and_context_window.json",))
diff --git a/tests/test_litellm/llms/openai_like/test_tensormesh_provider.py b/tests/test_litellm/llms/openai_like/test_tensormesh_provider.py
index 66dd18fc8d7..1e2e20d2d37 100644
--- a/tests/test_litellm/llms/openai_like/test_tensormesh_provider.py
+++ b/tests/test_litellm/llms/openai_like/test_tensormesh_provider.py
@@ -129,15 +129,6 @@ class TestTensormeshCostMap:
             litellm.model_cost = original_model_cost
             litellm.get_model_info.cache_clear()
 
-    def test_models_registered_with_capabilities(self):
-        for model in TENSORMESH_MODELS:
-            info = litellm.get_model_info(model)
-            assert info["litellm_provider"] == "tensormesh"
-            assert info["mode"] == "chat"
-            assert litellm.supports_function_calling(model) is True, model
-            assert litellm.supports_response_schema(model) is True, model
-            assert litellm.model_cost[model]["supports_tool_choice"] is True, model
-            assert litellm.model_cost[model]["supports_prompt_caching"] is True, model
 
     def test_reasoning_flag_matches_expected_set(self):
         reasoning_models = {
diff --git a/tests/test_litellm/llms/reducto/test_model_info.py b/tests/test_litellm/llms/reducto/test_model_info.py
index de7a3ccba64..499adf0d179 100644
--- a/tests/test_litellm/llms/reducto/test_model_info.py
+++ b/tests/test_litellm/llms/reducto/test_model_info.py
@@ -1,9 +1,6 @@
-import uuid
 
 import litellm
 
-from litellm.utils import _invalidate_model_cost_lowercase_map
-
 
 def test_reducto_provider_registration():
     model, custom_llm_provider, _, _ = litellm.get_llm_provider(
@@ -14,31 +11,3 @@ def test_reducto_provider_registration():
     assert custom_llm_provider == "reducto"
 
 
-def test_get_model_info_preserves_ocr_cost_per_credit():
-    test_model_name = f"reducto/test-cost-propagation-{uuid.uuid4().hex[:12]}"
-    previous_model_entry = litellm.model_cost.get(test_model_name)
-    _invalidate_model_cost_lowercase_map()
-
-    try:
-        litellm.register_model(
-            {
-                test_model_name: {
-                    "litellm_provider": "reducto",
-                    "mode": "ocr",
-                    "ocr_cost_per_credit": 0.003,
-                }
-            }
-        )
-
-        model_info = litellm.get_model_info(
-            model=test_model_name,
-            custom_llm_provider="reducto",
-        )
-
-        assert model_info.get("ocr_cost_per_credit") == 0.003
-    finally:
-        if previous_model_entry is None:
-            litellm.model_cost.pop(test_model_name, None)
-        else:
-            litellm.model_cost[test_model_name] = previous_model_entry
-        _invalidate_model_cost_lowercase_map()
diff --git a/tests/test_litellm/llms/tencent/chat/test_tencent_chat_transformation.py b/tests/test_litellm/llms/tencent/chat/test_tencent_chat_transformation.py
index 9f510786d50..4d6d252ae6e 100644
--- a/tests/test_litellm/llms/tencent/chat/test_tencent_chat_transformation.py
+++ b/tests/test_litellm/llms/tencent/chat/test_tencent_chat_transformation.py
@@ -247,23 +247,6 @@ class TestAdaptiveThinkingCoercion:
         assert config._is_adaptive_thinking_model("tencent/no-such-model") is False
 
 
-def test_minimax_m3_cost_map_entry_marks_adaptive_thinking():
-    """The capability flag driving the coercion must exist in the cost map
-    (and its backup, which is shipped with the package)."""
-    import json
-    from pathlib import Path
-
-    repo_root = Path(__file__).parents[5]
-    for filename in ("model_prices_and_context_window.json", "litellm/model_prices_and_context_window_backup.json"):
-        with open(repo_root / filename) as f:
-            entry = json.load(f).get("tencent/minimax-m3")
-
-        assert entry is not None, f"tencent/minimax-m3 not found in {filename}"
-        assert entry["litellm_provider"] == "tencent"
-        assert entry.get("supports_adaptive_thinking") is True
-        assert entry.get("supports_reasoning") is True
-
-
 def test_get_complete_url_default():
     config = TencentChatConfig()
 
diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py
index 7d2dfbb962e..04a7ee451c4 100644
--- a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py
+++ b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py
@@ -389,7 +389,6 @@ def test_build_vertex_schema_array_branch_missing_items_in_anyof():
 
 
 def test_vertex_ai_complex_response_schema():
-    import json
     from copy import deepcopy
 
     from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
@@ -1192,7 +1191,7 @@ async def test_vertex_ai_token_counter_routes_partner_models():
     Test that VertexAITokenCounter correctly routes partner models (Claude, Mistral, etc.)
     to the partner models token counter instead of the Gemini token counter.
     """
-    from unittest.mock import AsyncMock, patch
+    from unittest.mock import patch
 
     from litellm.llms.vertex_ai.common_utils import VertexAITokenCounter
     from litellm.types.utils import TokenCountResponse
@@ -1242,7 +1241,6 @@ async def test_vertex_ai_token_counter_uses_count_tokens_location():
     from unittest.mock import patch
 
     from litellm.llms.vertex_ai.common_utils import VertexAITokenCounter
-    from litellm.types.utils import TokenCountResponse
 
     token_counter = VertexAITokenCounter()
 
@@ -1283,7 +1281,7 @@ async def test_vertex_ai_token_counter_routes_gemini_models():
     Test that VertexAITokenCounter correctly routes Gemini models
     to the Gemini token counter (not partner models).
     """
-    from unittest.mock import AsyncMock, patch
+    from unittest.mock import patch
 
     from litellm.llms.vertex_ai.common_utils import VertexAITokenCounter
     from litellm.types.utils import TokenCountResponse
@@ -1757,17 +1755,3 @@ def test_get_vertex_ai_lyria_model_info_is_none_for_non_lyria_speech_models(mode
     assert get_vertex_ai_lyria_model_info(model=model) is None
 
 
-def test_get_vertex_ai_lyria_model_info_falls_back_to_bundled_map(monkeypatch):
-    import litellm
-    from litellm.llms.vertex_ai.common_utils import get_vertex_ai_lyria_model_info
-
-    stale_runtime_model_cost = {
-        key: value for key, value in litellm.model_cost.items() if not key.startswith("vertex_ai/lyria")
-    }
-    monkeypatch.setattr(litellm, "model_cost", stale_runtime_model_cost)
-
-    model_info = get_vertex_ai_lyria_model_info(model="lyria-3-pro-preview")
-
-    assert model_info is not None
-    assert model_info["vertex_ai_audio_api"] == "lyria_interactions"
-    assert model_info["supported_audio_formats"] == ("mp3", "wav")
diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py
index a57672cfbfb..37a619d6400 100644
--- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py
+++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py
@@ -34,7 +34,6 @@ def test_get_supported_params_thinking():
 
 def test_vertex_ai_anthropic_web_search_header_in_completion():
     """Test that web search tool adds the required beta header for Vertex AI completion requests"""
-    from unittest.mock import MagicMock, patch
 
     from litellm.llms.anthropic.common_utils import AnthropicModelInfo
 
@@ -463,9 +462,6 @@ def test_vertex_ai_partner_models_anthropic_remove_prompt_caching_scope_beta_hea
     Test that remove_unsupported_beta correctly filters out prompt-caching-scope-2026-01-05
     from the anthropic-beta headers.
     """
-    from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
-        VertexAIPartnerModelsAnthropicMessagesConfig,
-    )
 
     # This beta header should be removed
     PROMPT_CACHING_BETA_HEADER = "prompt-caching-scope-2026-01-05"
diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py
index 957d7475d91..e9b58622a4b 100644
--- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py
+++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gemma/test_vertex_ai_gemma_global_endpoint.py
@@ -180,28 +180,6 @@ class TestCreateVertexURLGemma:
 # ---------------------------------------------------------------------------
 
 
-def test_gemma_maas_supports_function_calling():
-    """supports_function_calling=true in model_cost must be surfaced by the utility."""
-    with patch.dict(litellm.model_cost, _GEMMA_MODEL_COST_ENTRY, clear=False):
-        assert (
-            litellm.utils.supports_function_calling(
-                model="vertex_ai/google/gemma-4-26b-a4b-it-maas"
-            )
-            is True
-        )
-
-
-def test_gemma_maas_supports_vision():
-    """supports_vision=true in model_cost must be surfaced by the utility."""
-    with patch.dict(litellm.model_cost, _GEMMA_MODEL_COST_ENTRY, clear=False):
-        assert (
-            litellm.utils.supports_vision(
-                model="vertex_ai/google/gemma-4-26b-a4b-it-maas"
-            )
-            is True
-        )
-
-
 # ---------------------------------------------------------------------------
 # Integration tests: verify payloads reach the global OpenAI endpoint
 #
diff --git a/tests/test_litellm/llms/vertex_ai/videos/test_vertex_video_transformation.py b/tests/test_litellm/llms/vertex_ai/videos/test_vertex_video_transformation.py
index b6b638c6dbe..5c90d54ae90 100644
--- a/tests/test_litellm/llms/vertex_ai/videos/test_vertex_video_transformation.py
+++ b/tests/test_litellm/llms/vertex_ai/videos/test_vertex_video_transformation.py
@@ -14,7 +14,6 @@ import pytest
 
 import litellm
 from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
-from litellm.llms.openai.cost_calculation import video_generation_cost
 from litellm.llms.vertex_ai.videos.transformation import (
     VertexAIVideoConfig,
     _convert_image_to_vertex_format,
diff --git a/tests/test_litellm/llms/xai/test_xai_model_registry.py b/tests/test_litellm/llms/xai/test_xai_model_registry.py
index a455d1fb233..a596afa963f 100644
--- a/tests/test_litellm/llms/xai/test_xai_model_registry.py
+++ b/tests/test_litellm/llms/xai/test_xai_model_registry.py
@@ -29,24 +29,6 @@ def cost_map(request: pytest.FixtureRequest) -> dict:
     return json.loads(path.read_text(encoding="utf-8"))
 
 
-@pytest.mark.parametrize("model", RESPONSES_ONLY_MODELS)
-def test_multi_agent_models_are_responses_only(cost_map: dict, model: str):
-    entry = cost_map[model]
-    assert entry["supported_endpoints"] == ["/v1/responses"]
-    assert entry["mode"] == "responses"
-
-
-def test_surviving_xai_chat_models_still_serve_chat_completions(cost_map: dict):
-    """Guard against the removal above over-reaching into live models."""
-    chat_models = [
-        key
-        for key, value in cost_map.items()
-        if isinstance(value, dict) and value.get("litellm_provider") == "xai" and value.get("mode") == "chat"
-    ]
-    assert "xai/grok-4.3" in chat_models
-    assert "xai/grok-4.6" in chat_models
-
-
 def test_both_cost_maps_agree_on_xai_entries():
     prices = json.loads(PRICES_PATH.read_text(encoding="utf-8"))
     backup = json.loads(BACKUP_PRICES_PATH.read_text(encoding="utf-8"))
diff --git a/tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py b/tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py
index bbbcfb1b9dc..83e8925f70b 100644
--- a/tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py
+++ b/tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py
@@ -85,11 +85,6 @@ def test_code_slug_bills_at_grok_build_rate(cost_map: dict, slug: str):
         assert entry[field] == target[field], field
 
 
-def test_a_live_xai_model_is_untouched(cost_map: dict):
-    """Guard against the repricing leaking onto models xAI still serves directly."""
-    assert cost_map["xai/grok-4.6"]["input_cost_per_token"] != cost_map[REDIRECT_TARGET]["input_cost_per_token"]
-
-
 @pytest.mark.parametrize("slug", REDIRECTED_SLUGS)
 def test_redirected_slug_carries_the_target_tier_rates(cost_map: dict, slug: str):
     """The request executes as grok-4.3, so it is tiered at grok-4.3's 200k boundary."""
diff --git a/tests/test_litellm/proxy/auth/test_model_checks.py b/tests/test_litellm/proxy/auth/test_model_checks.py
index 36bfc4c5dd3..3c6733cb86d 100644
--- a/tests/test_litellm/proxy/auth/test_model_checks.py
+++ b/tests/test_litellm/proxy/auth/test_model_checks.py
@@ -1,10 +1,7 @@
-from unittest.mock import AsyncMock, patch
+from unittest.mock import patch
 
 import pytest
 
-from litellm.proxy._types import LiteLLM_TeamTable, LiteLLM_UserTable, Member
-from litellm.proxy.auth.handle_jwt import JWTAuthManager
-
 
 def test_get_team_models_for_all_models_and_team_only_models():
     from litellm.proxy.auth.model_checks import get_team_models
@@ -858,23 +855,6 @@ def test_add_known_models_refreshes_models_by_provider_for_wildcard_expansion():
     assert fake_model not in litellm.models_by_provider["vertex_ai"]
 
 
-def test_azure_ai_wildcard_lists_the_foundry_gpt_6_astra_entry(monkeypatch):
-    import litellm
-    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
-
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    foundry_key = "azure_ai/gpt-6-astra"
-    local_entry = litellm.get_model_cost_map(url="")[foundry_key]
-    registered_before = foundry_key in litellm.azure_ai_models
-    try:
-        litellm.add_known_models(model_cost_map={foundry_key: local_entry})
-        assert foundry_key in get_known_models_from_wildcard("azure_ai/*")
-    finally:
-        if not registered_before:
-            litellm.azure_ai_models.discard(foundry_key)
-            litellm.add_known_models(model_cost_map={})
-
-
 def test_get_complete_model_list_drops_no_default_models_sentinel():
     from litellm.proxy.auth.model_checks import get_complete_model_list
 
diff --git a/tests/test_litellm/test_azure_audio_price_aliases.py b/tests/test_litellm/test_azure_audio_price_aliases.py
deleted file mode 100644
index b87744aeae1..00000000000
--- a/tests/test_litellm/test_azure_audio_price_aliases.py
+++ /dev/null
@@ -1,75 +0,0 @@
-"""Undated azure aliases for the audio models must exist and match their dated
-variants. Azure deployments are commonly created under an admin-chosen name, so
-the served model name means nothing to the cost lookup and `base_model:
-azure/gpt-audio-mini` is what prices the call. That key resolved to nothing, the
-lookup raised "This model isn't mapped yet", and the proxy logged the request at
-$0. Issue #33170."""
-
-import json
-from pathlib import Path
-
-import pytest
-
-import litellm
-
-pytestmark = pytest.mark.usefixtures("local_model_cost_map")
-
-
-COST_FIELDS = (
-    "input_cost_per_token",
-    "output_cost_per_token",
-    "input_cost_per_audio_token",
-    "output_cost_per_audio_token",
-)
-
-ALIAS_PAIRS = (
-    ("azure/gpt-audio-mini", "azure/gpt-audio-mini-2025-10-06"),
-    ("azure/gpt-realtime-mini", "azure/gpt-realtime-mini-2025-10-06"),
-)
-
-
-def _load_root_cost_map() -> dict:
-    root_map_path = Path(__file__).parents[2] / "model_prices_and_context_window.json"
-    with open(root_map_path) as f:
-        return json.load(f)
-
-
-@pytest.mark.parametrize("undated, dated", ALIAS_PAIRS)
-def test_undated_azure_audio_alias_matches_dated_entry(undated, dated):
-    undated_info = litellm.get_model_info(undated)
-    dated_info = litellm.get_model_info(dated)
-
-    for field in COST_FIELDS:
-        assert undated_info.get(field) == dated_info.get(field), field
-        assert (undated_info.get(field) or 0) > 0, f"{undated}.{field} must be non-zero"
-
-    assert undated_info.get("litellm_provider") == "azure"
-    assert undated_info.get("mode") == dated_info.get("mode")
-
-
-@pytest.mark.parametrize("undated, dated", ALIAS_PAIRS)
-def test_undated_azure_audio_alias_is_exact_mirror(undated, dated):
-    """The undated alias must be a byte-for-byte mirror of its dated entry, covering
-    every field (incl. realtime-specific cache/audio cost keys) so any future drift
-    between the pair is caught, not just the core COST_FIELDS."""
-    model_map = litellm.model_cost
-    assert undated in model_map, f"{undated} missing from model cost map"
-    assert model_map[undated] == model_map[dated], (
-        f"{undated} must exactly mirror {dated}; "
-        f"diff keys: {[k for k in set(model_map[undated]) | set(model_map[dated]) if model_map[undated].get(k) != model_map[dated].get(k)]}"
-    )
-
-
-@pytest.mark.parametrize("undated, dated", ALIAS_PAIRS)
-def test_undated_azure_audio_alias_is_in_the_root_cost_map(undated, dated):
-    """`local_model_cost_map` pins `litellm.model_cost` to the packaged backup, but a
-    proxy left on its defaults fetches the root map instead, and that is the copy
-    that ships to the CDN. An alias added to only one of the two files still bills
-    $0 for every proxy reading the other, which is the very bug this file guards, so
-    assert the root map directly and assert the two files agree."""
-    root_map = _load_root_cost_map()
-    assert undated in root_map, f"{undated} missing from the root cost map"
-    assert root_map[undated] == root_map[dated], f"{undated} must exactly mirror {dated} in the root cost map"
-    assert root_map[undated] == litellm.model_cost[undated], (
-        f"{undated} differs between the root cost map and the packaged backup"
-    )
diff --git a/tests/test_litellm/test_baseten_glm_5_3_model_metadata.py b/tests/test_litellm/test_baseten_glm_5_3_model_metadata.py
index 31f3a67beac..f573c79434a 100644
--- a/tests/test_litellm/test_baseten_glm_5_3_model_metadata.py
+++ b/tests/test_litellm/test_baseten_glm_5_3_model_metadata.py
@@ -4,7 +4,6 @@ from pathlib import Path
 import pytest
 
 import litellm
-from litellm.utils import supports_function_calling, supports_prompt_caching
 
 REPO_ROOT = Path(__file__).parents[2]
 MAIN_PATH = REPO_ROOT / "model_prices_and_context_window.json"
@@ -33,17 +32,6 @@ def local_model_cost_map(monkeypatch):
     litellm.get_model_info.cache_clear()
 
 
-def test_baseten_glm_5_3_capabilities_are_visible_to_callers(local_model_cost_map):
-    """The entry advertises prompt caching and tool calling, so the helpers every
-    caller checks before sending a request must say so too."""
-    assert supports_prompt_caching(model=MODEL) is True
-    assert supports_function_calling(model=MODEL) is True
-
-    info = litellm.get_model_info(model="zai-org/GLM-5.3", custom_llm_provider="baseten")
-    assert info["max_input_tokens"] > 0
-    assert info["max_output_tokens"] > 0
-
-
 def test_backup_matches_main():
     """Ensure the bundled (backup) cost map stays in sync with the canonical file.
 
diff --git a/tests/test_litellm/test_bedrock_marengo_embed_3_model_metadata.py b/tests/test_litellm/test_bedrock_marengo_embed_3_model_metadata.py
index 1a0e1665556..21e9b26d996 100644
--- a/tests/test_litellm/test_bedrock_marengo_embed_3_model_metadata.py
+++ b/tests/test_litellm/test_bedrock_marengo_embed_3_model_metadata.py
@@ -3,7 +3,6 @@ from pathlib import Path
 
 import pytest
 
-import litellm
 from litellm.constants import bedrock_embedding_models
 
 REPO_ROOT = Path(__file__).parents[2]
@@ -31,13 +30,6 @@ def _load(path):
         return json.load(f)
 
 
-@pytest.mark.parametrize("model", ALL_MODELS)
-def test_marengo_embed_3_is_visible_to_callers(model, local_model_cost_map):
-    info = litellm.get_model_info(model=model, custom_llm_provider="bedrock")
-    assert info["mode"] == "embedding"
-    assert info["output_vector_size"] == 512
-
-
 def test_marengo_embed_3_is_a_known_bedrock_embedding_model():
     assert BASE_MODEL in bedrock_embedding_models
 
diff --git a/tests/test_litellm/test_bedrock_usgov_pricing.py b/tests/test_litellm/test_bedrock_usgov_pricing.py
deleted file mode 100644
index a3a7fc4ed7a..00000000000
--- a/tests/test_litellm/test_bedrock_usgov_pricing.py
+++ /dev/null
@@ -1,77 +0,0 @@
-"""
-Validate AWS GovCloud (Bedrock us-gov-*) Anthropic pricing entries.
-
-AWS Bedrock pricing in GovCloud carries a +20% premium over the global
-Anthropic prices (not the +10% commercial-US premium). Until 2026-05-22
-these entries silently mirrored commercial US, undercharging customers
-by ~9%.
-
-Source: https://aws.amazon.com/bedrock/pricing/
-
-  Sonnet 4.5 in us-gov-* (per million tokens):
-    input          = $3.60
-    output         = $18.00
-    cache write 5m = $4.50
-    cache write 1h = $7.20
-    cache read     = $0.36
-
-Reference: https://github.com/BerriAI/litellm/issues/27120
-"""
-
-import json
-import os
-
-import pytest
-
-
-@pytest.fixture(scope="module")
-def model_data():
-    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)
-
-
-def test_usgov_east_haiku_profile_mirrors_in_region_row(model_data):
-    """us-gov-east-1 serves claude-3-haiku through the us-gov. inference profile
-    only, so the profile row must bill exactly like the in-region gov row.
-    """
-    profile = model_data["us-gov.anthropic.claude-3-haiku-20240307-v1:0"]
-    in_region = model_data["bedrock/us-gov-east-1/anthropic.claude-3-haiku-20240307-v1:0"]
-    assert profile["litellm_provider"] == "bedrock_converse"
-    assert {k: v for k, v in profile.items() if k != "litellm_provider"} == {
-        k: v for k, v in in_region.items() if k != "litellm_provider"
-    }
-
-
-GOV_ROW_SOURCES = {
-    "us-gov.anthropic.claude-fable-5-1": "anthropic.claude-fable-5-1",
-    "bedrock/us-gov-west-1/anthropic.claude-fable-5-1": "anthropic.claude-fable-5-1",
-    "bedrock/us-gov-east-1/anthropic.claude-fable-5-1": "anthropic.claude-fable-5-1",
-    "us-gov.nvidia.nemotron-nano-9b-v2": "nvidia.nemotron-nano-9b-v2",
-    "bedrock/us-gov-west-1/nvidia.nemotron-nano-9b-v2": "nvidia.nemotron-nano-9b-v2",
-    "bedrock/us-gov-east-1/nvidia.nemotron-nano-9b-v2": "nvidia.nemotron-nano-9b-v2",
-    "us-gov.xai.grok-4.6": "us.xai.grok-4.6",
-    "bedrock_mantle/us-gov-west-1/xai.grok-4.6": "bedrock_mantle/xai.grok-4.6",
-    "bedrock_mantle/us-gov-east-1/xai.grok-4.6": "bedrock_mantle/xai.grok-4.6",
-    "bedrock/us-gov-west-1/amazon.nova-2-multimodal-embeddings-v1:0": "amazon.nova-2-multimodal-embeddings-v1:0",
-    "bedrock/us-gov-west-1/amazon.nova-lite-v1:0": "amazon.nova-lite-v1:0",
-    "bedrock/us-gov-west-1/amazon.nova-micro-v1:0": "amazon.nova-micro-v1:0",
-    "bedrock_mantle/us-gov-west-1/google.gemma-4-e2b": "bedrock_mantle/google.gemma-4-e2b",
-    "bedrock_mantle/us-gov-west-1/google.gemma-4-26b-a4b": "bedrock_mantle/google.gemma-4-26b-a4b",
-    "bedrock_mantle/us-gov-west-1/google.gemma-4-31b": "bedrock_mantle/google.gemma-4-31b",
-    "bedrock_mantle/us-gov-west-1/openai.gpt-oss-20b": "bedrock_mantle/openai.gpt-oss-20b",
-    "bedrock_mantle/us-gov-east-1/openai.gpt-oss-20b": "bedrock_mantle/openai.gpt-oss-20b",
-    "bedrock_mantle/us-gov-west-1/openai.gpt-oss-120b": "bedrock_mantle/openai.gpt-oss-120b",
-    "bedrock_mantle/us-gov-east-1/openai.gpt-oss-120b": "bedrock_mantle/openai.gpt-oss-120b",
-}
-
-
-def _non_pricing_fields(info):
-    return {k: v for k, v in info.items() if "cost" not in k and k not in ("litellm_provider", "source")}
-
-
-@pytest.mark.parametrize("gov_key", GOV_ROW_SOURCES)
-def test_usgov_rows_keep_commercial_limits_and_capabilities(model_data, gov_key):
-    """Gov rows preserve the commercial row's non-pricing fields."""
-    gov = model_data[gov_key]
-    assert _non_pricing_fields(gov) == _non_pricing_fields(model_data[GOV_ROW_SOURCES[gov_key]])
diff --git a/tests/test_litellm/test_claude_fable_5_config.py b/tests/test_litellm/test_claude_fable_5_config.py
index 4b03848da2c..dfbda795c7a 100644
--- a/tests/test_litellm/test_claude_fable_5_config.py
+++ b/tests/test_litellm/test_claude_fable_5_config.py
@@ -26,67 +26,10 @@ def _load_root_cost_map() -> dict:
         return json.load(f)
 
 
-def test_fable_5_present_in_bundled_backup():
-    """The bundled backup is the runtime fallback (and what tests load with
-    ``LITELLM_LOCAL_MODEL_COST_MAP=True``) — it must carry the same entries as
-    the root cost map, otherwise the model resolves on one path but not the
-    other."""
-    backup = GetModelCostMap.load_local_model_cost_map()
-    root = _load_root_cost_map()
-    for model_name in (
-        "claude-fable-5",
-        "anthropic.claude-fable-5",
-        "global.anthropic.claude-fable-5",
-        "us.anthropic.claude-fable-5",
-        "eu.anthropic.claude-fable-5",
-        "vertex_ai/claude-fable-5",
-        "vertex_ai/claude-fable-5@default",
-        "azure_ai/claude-fable-5",
-    ):
-        assert model_name in backup, f"Missing from backup cost map: {model_name}"
-        assert backup[model_name] == root[model_name], model_name
-
-
 def test_fable_5_registered_for_bedrock_converse():
     assert "anthropic.claude-fable-5" in BEDROCK_CONVERSE_MODELS
 
 
-@pytest.mark.parametrize(
-    "cost_map",
-    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
-    ids=["root", "bundled_backup"],
-)
-def test_fable_5_all_variants_carry_adaptive_thinking_flag(cost_map):
-    """Every Fable 5 entry must advertise ``supports_adaptive_thinking``.
-
-    Adaptive-thinking detection is cost-map driven, so a single variant missing
-    the flag silently sends the legacy ``thinking.type='enabled'`` shape and the
-    provider 400s (issue #29188 for the Opus 4.8 equivalent). Fable 5 is even
-    stricter than Opus 4.8: an explicit ``thinking.type='disabled'`` also 400s,
-    so adaptive is the only valid thinking shape LiteLLM can emit for it."""
-    variants = [k for k in cost_map if "claude-fable-5" in k]
-    assert variants, "no claude-fable-5 entries found in cost map"
-    missing = [k for k in variants if cost_map[k].get("supports_adaptive_thinking") is not True]
-    assert not missing, f"missing supports_adaptive_thinking: {missing}"
-
-
-@pytest.mark.parametrize(
-    "cost_map",
-    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
-    ids=["root", "bundled_backup"],
-)
-def test_fable_5_all_variants_carry_thinking_always_on_flag(cost_map):
-    """Every Fable 5 entry must advertise ``thinking_always_on``.
-
-    The flag drives the Anthropic transformations to omit an explicit
-    ``thinking.type='disabled'``, which Fable 5 rejects with a 400; a variant
-    missing the flag forwards the param verbatim and the provider 400s."""
-    variants = [k for k in cost_map if "claude-fable-5" in k]
-    assert variants, "no claude-fable-5 entries found in cost map"
-    missing = [k for k in variants if cost_map[k].get("thinking_always_on") is not True]
-    assert not missing, f"missing thinking_always_on: {missing}"
-
-
 @pytest.mark.parametrize(
     "model",
     [
@@ -151,22 +94,3 @@ def test_adaptive_thinking_detected_for_fable_5_1(local_model_cost_map, model):
     assert AnthropicModelInfo._is_adaptive_thinking_model(model, "anthropic") is True
 
 
-@pytest.mark.parametrize(
-    "cost_map",
-    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
-    ids=["root", "bundled_backup"],
-)
-def test_sampling_params_flag_on_all_models_that_removed_them(cost_map):
-    """Fable 5 and Opus 4.7/4.8 reject ``top_p``/``top_k``/``temperature != 1``;
-    the drop/raise gating is cost-map driven, so every variant must carry an
-    explicit ``supports_sampling_params: false``. The perplexity route is
-    exempt: it is OpenAI-compatible and maps sampling params upstream."""
-    variants = [
-        k
-        for k in cost_map
-        if any(v in k for v in ("claude-fable-5", "claude-opus-4-7", "claude-opus-4-8"))
-        and not k.startswith("perplexity/")
-    ]
-    assert variants, "no matching entries found in cost map"
-    missing = [k for k in variants if cost_map[k].get("supports_sampling_params") is not False]
-    assert not missing, f"missing supports_sampling_params=false: {missing}"
diff --git a/tests/test_litellm/test_claude_haiku_4_5_config.py b/tests/test_litellm/test_claude_haiku_4_5_config.py
deleted file mode 100644
index d0b7f4f8a2c..00000000000
--- a/tests/test_litellm/test_claude_haiku_4_5_config.py
+++ /dev/null
@@ -1,46 +0,0 @@
-"""
-Test Claude Haiku 4.5 model configurations for Bedrock
-https://github.com/BerriAI/litellm/issues/15818
-"""
-
-import json
-import os
-
-
-def test_bedrock_haiku_4_5_matches_sonnet_capabilities():
-    """
-    Test that Haiku 4.5 has same capabilities as Sonnet 4.5
-    (including computer_use, vision, tools, etc.)
-    """
-    # Load model configuration
-    json_path = os.path.join(os.path.dirname(__file__), "../../model_prices_and_context_window.json")
-    with open(json_path) as f:
-        model_data = json.load(f)
-
-    haiku_model = "us.anthropic.claude-haiku-4-5-20251001-v1:0"
-    sonnet_model = "us.anthropic.claude-sonnet-4-5-20250929-v1:0"
-
-    haiku_info = model_data[haiku_model]
-    sonnet_info = model_data[sonnet_model]
-
-    # Both should use bedrock_converse
-    assert haiku_info["litellm_provider"] == "bedrock_converse"
-    assert sonnet_info["litellm_provider"] == "bedrock_converse"
-
-    # Shared capabilities that should match
-    shared_capabilities = [
-        "supports_vision",
-        "supports_computer_use",
-        "supports_function_calling",
-        "supports_tool_choice",
-        "supports_prompt_caching",
-        "supports_response_schema",
-        "supports_pdf_input",
-        "supports_assistant_prefill",
-        "supports_reasoning",
-    ]
-
-    for capability in shared_capabilities:
-        assert haiku_info.get(capability) == sonnet_info.get(capability), (
-            f"Capability {capability} mismatch: Haiku={haiku_info.get(capability)}, Sonnet={sonnet_info.get(capability)}"
-        )
diff --git a/tests/test_litellm/test_claude_opus_4_6_config.py b/tests/test_litellm/test_claude_opus_4_6_config.py
index 9a8632924f2..7bded3b6ed3 100644
--- a/tests/test_litellm/test_claude_opus_4_6_config.py
+++ b/tests/test_litellm/test_claude_opus_4_6_config.py
@@ -2,100 +2,10 @@
 Validate Claude Opus 4.6 model configuration entries.
 """
 
-import json
-import os
 
 import litellm
 
 
-def test_claude_4_6_australia_region_uses_au_prefix_not_apac():
-    """
-    Test that Australia region Claude 4.6 models use 'au.' prefix instead of incorrect 'apac.' prefix.
-
-    AWS Bedrock cross-region inference uses specific regional prefixes:
-    - 'us.' for United States
-    - 'eu.' for Europe
-    - 'au.' for Australia (ap-southeast-2)
-    - 'apac.' for Asia-Pacific (Singapore, ap-southeast-1)
-
-    This test ensures the Claude 4.6 models correctly use 'au.' for Australia,
-    and that 'apac.' is NOT incorrectly used for Australia region.
-
-    Related: The 'apac.' prefix is valid for Asia-Pacific (Singapore) region models,
-    but should not be used for Australia which has its own 'au.' prefix.
-    """
-    json_path = os.path.join(
-        os.path.dirname(__file__), "../../model_prices_and_context_window.json"
-    )
-    with open(json_path) as f:
-        model_data = json.load(f)
-
-    # Verify au.anthropic.claude-opus-4-6-v1 exists (correct)
-    assert (
-        "au.anthropic.claude-opus-4-6-v1" in model_data
-    ), "Missing Australia region model: au.anthropic.claude-opus-4-6-v1"
-
-    # Verify apac.anthropic.claude-opus-4-6-v1 does NOT exist (incorrect)
-    assert (
-        "apac.anthropic.claude-opus-4-6-v1" not in model_data
-    ), "Incorrect model entry exists: apac.anthropic.claude-opus-4-6-v1 should be au.anthropic.claude-opus-4-6-v1"
-
-    # Verify au.anthropic.claude-sonnet-4-6 exists (correct)
-    assert (
-        "au.anthropic.claude-sonnet-4-6" in model_data
-    ), "Missing Australia region model: au.anthropic.claude-sonnet-4-6"
-
-    # Verify apac.anthropic.claude-sonnet-4-6 does NOT exist (incorrect)
-    assert (
-        "apac.anthropic.claude-sonnet-4-6" not in model_data
-    ), "Incorrect model entry exists: apac.anthropic.claude-sonnet-4-6 should be au.anthropic.claude-sonnet-4-6"
-
-    # Verify the au. model is registered in bedrock_converse_models
-    assert (
-        "au.anthropic.claude-opus-4-6-v1" in litellm.bedrock_converse_models
-    ), "au.anthropic.claude-opus-4-6-v1 not registered in bedrock_converse_models"
-
-    # Verify apac. is NOT registered for this model
-    assert (
-        "apac.anthropic.claude-opus-4-6-v1" not in litellm.bedrock_converse_models
-    ), "apac.anthropic.claude-opus-4-6-v1 should not be in bedrock_converse_models"
-
-    # Verify the au. model is registered in bedrock_converse_models
-    assert (
-        "au.anthropic.claude-sonnet-4-6" in litellm.bedrock_converse_models
-    ), "au.anthropic.claude-sonnet-4-6 not registered in bedrock_converse_models"
-
-    # Verify apac. is NOT registered for this model
-    assert (
-        "apac.anthropic.claude-sonnet-4-6" not in litellm.bedrock_converse_models
-    ), "apac.anthropic.claude-sonnet-4-6 should not be in bedrock_converse_models"
-
-
-def test_opus_4_6_alias_and_dated_metadata_match():
-    json_path = os.path.join(
-        os.path.dirname(__file__), "../../model_prices_and_context_window.json"
-    )
-    with open(json_path) as f:
-        model_data = json.load(f)
-
-    alias = model_data["claude-opus-4-6"]
-    dated = model_data["claude-opus-4-6-20260205"]
-
-    keys_to_match = [
-        "max_input_tokens",
-        "max_output_tokens",
-        "max_tokens",
-        "input_cost_per_token",
-        "output_cost_per_token",
-        "cache_creation_input_token_cost",
-        "cache_creation_input_token_cost_above_1hr",
-        "cache_read_input_token_cost",
-        "supports_assistant_prefill",
-    ]
-    for key in keys_to_match:
-        assert alias[key] == dated[key], f"Mismatch for {key}"
-
-
 def test_opus_4_6_bedrock_converse_registration():
     assert "anthropic.claude-opus-4-6-v1" in litellm.BEDROCK_CONVERSE_MODELS
     assert "global.anthropic.claude-opus-4-6-v1" in litellm.bedrock_converse_models
diff --git a/tests/test_litellm/test_claude_opus_4_8_config.py b/tests/test_litellm/test_claude_opus_4_8_config.py
index 1a4bab249fd..9471ef4ef4f 100644
--- a/tests/test_litellm/test_claude_opus_4_8_config.py
+++ b/tests/test_litellm/test_claude_opus_4_8_config.py
@@ -11,43 +11,15 @@ for Anthropic, Bedrock, Vertex AI, and Azure AI; those entries are what populate
 in ``get_llm_provider`` consumes.
 """
 
-import json
 import os
 
-import pytest
 
 from litellm.constants import BEDROCK_CONVERSE_MODELS
-from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap
 
 REPO_ROOT = os.path.join(os.path.dirname(__file__), "../..")
 
 
-def _load_root_cost_map() -> dict:
-    json_path = os.path.join(REPO_ROOT, "model_prices_and_context_window.json")
-    with open(json_path) as f:
-        return json.load(f)
-
-
 def test_opus_4_8_registered_for_bedrock_converse():
     assert "anthropic.claude-opus-4-8" in BEDROCK_CONVERSE_MODELS
 
 
-@pytest.mark.parametrize(
-    "cost_map",
-    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
-    ids=["root", "bundled_backup"],
-)
-def test_opus_4_8_all_variants_carry_adaptive_thinking_flag(cost_map):
-    """Every Opus 4.8 entry must advertise ``supports_adaptive_thinking``.
-
-    Adaptive-thinking detection is cost-map driven, so a single variant missing
-    the flag silently sends the legacy ``thinking.type='enabled'`` shape and the
-    provider 400s (issue #29188, which the Bedrock/Vertex/Azure variants hit
-    because only the bare ``claude-opus-4-8`` entry carried the flag). This guards
-    against a future variant being added without it."""
-    variants = [k for k in cost_map if "claude-opus-4-8" in k]
-    assert variants, "no claude-opus-4-8 entries found in cost map"
-    missing = [
-        k for k in variants if cost_map[k].get("supports_adaptive_thinking") is not True
-    ]
-    assert not missing, f"missing supports_adaptive_thinking: {missing}"
diff --git a/tests/test_litellm/test_claude_opus_5_config.py b/tests/test_litellm/test_claude_opus_5_config.py
index 07e493af914..aaf179e0216 100644
--- a/tests/test_litellm/test_claude_opus_5_config.py
+++ b/tests/test_litellm/test_claude_opus_5_config.py
@@ -12,13 +12,11 @@ validator accepts the full effort ladder, so the entries must not carry the
 ``anthropic/*`` wildcard deployment).
 """
 
-import json
 import os
 
 import pytest
 
 from litellm.constants import BEDROCK_CONVERSE_MODELS
-from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap
 
 REPO_ROOT = os.path.join(os.path.dirname(__file__), "../..")
 
@@ -45,12 +43,6 @@ BEDROCK_OPUS_5_VARIANTS = (
 )
 
 
-def _load_root_cost_map() -> dict:
-    json_path = os.path.join(REPO_ROOT, "model_prices_and_context_window.json")
-    with open(json_path) as f:
-        return json.load(f)
-
-
 @pytest.mark.parametrize("model_name", BEDROCK_OPUS_5_VARIANTS)
 def test_opus_5_bedrock_rejects_strict_tools(model_name, local_model_cost_map):
     """Bedrock Converse routes Opus through a validator that rejects
@@ -62,31 +54,7 @@ def test_opus_5_bedrock_rejects_strict_tools(model_name, local_model_cost_map):
     assert bedrock_converse_supports_strict_tools(model_name) is False
 
 
-def test_opus_5_present_in_bundled_backup():
-    """The bundled backup is the runtime fallback (and what tests load with
-    ``LITELLM_LOCAL_MODEL_COST_MAP=True``); it must carry the same entries as the
-    root cost map, otherwise the model resolves on one path but not the other."""
-    backup = GetModelCostMap.load_local_model_cost_map()
-    for model_name in ALL_OPUS_5_VARIANTS:
-        assert model_name in backup, f"Missing from backup cost map: {model_name}"
-
-
 def test_opus_5_registered_for_bedrock_converse():
     assert "anthropic.claude-opus-5" in BEDROCK_CONVERSE_MODELS
 
 
-@pytest.mark.parametrize(
-    "cost_map",
-    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
-    ids=["root", "bundled_backup"],
-)
-def test_opus_5_all_variants_carry_adaptive_thinking_flag(cost_map):
-    """Every Opus 5 entry must advertise ``supports_adaptive_thinking``.
-
-    Adaptive-thinking detection is cost-map driven, so a single variant missing
-    the flag silently sends the legacy ``thinking.type='enabled'`` shape, which
-    Opus 5 rejects with a 400."""
-    variants = [k for k in cost_map if "claude-opus-5" in k]
-    assert variants, "no claude-opus-5 entries found in cost map"
-    missing = [k for k in variants if cost_map[k].get("supports_adaptive_thinking") is not True]
-    assert not missing, f"missing supports_adaptive_thinking: {missing}"
diff --git a/tests/test_litellm/test_claude_sonnet_4_6_config.py b/tests/test_litellm/test_claude_sonnet_4_6_config.py
deleted file mode 100644
index a669c21be30..00000000000
--- a/tests/test_litellm/test_claude_sonnet_4_6_config.py
+++ /dev/null
@@ -1,38 +0,0 @@
-"""
-Test Claude Sonnet 4.6 model configurations for Bedrock cross-region inference.
-
-Pins the set of region-prefixed entries in model_prices_and_context_window.json
-so future drops of a region (or pricing drift between regions) is caught.
-
-https://github.com/BerriAI/litellm/issues/22972
-"""
-
-import json
-import os
-
-
-def test_bedrock_sonnet_4_6_jp_matches_other_regional_pricing():
-    """The jp. cross-region inference profile shares pricing with the other
-    regional profiles (us./eu./au.), which carry a 10% premium over the
-    base/global entries.
-    """
-    json_path = os.path.join(
-        os.path.dirname(__file__), "../../model_prices_and_context_window.json"
-    )
-    with open(json_path) as f:
-        model_data = json.load(f)
-
-    jp_info = model_data["jp.anthropic.claude-sonnet-4-6"]
-    au_info = model_data["au.anthropic.claude-sonnet-4-6"]
-
-    pricing_fields = [
-        "input_cost_per_token",
-        "output_cost_per_token",
-        "cache_creation_input_token_cost",
-        "cache_read_input_token_cost",
-    ]
-    for field in pricing_fields:
-        assert jp_info[field] == au_info[field], (
-            f"{field} mismatch between jp. and au. variants: "
-            f"jp={jp_info[field]}, au={au_info[field]}"
-        )
diff --git a/tests/test_litellm/test_claude_sonnet_5_config.py b/tests/test_litellm/test_claude_sonnet_5_config.py
index 8c6d2cd1851..5e7d5797a62 100644
--- a/tests/test_litellm/test_claude_sonnet_5_config.py
+++ b/tests/test_litellm/test_claude_sonnet_5_config.py
@@ -10,13 +10,10 @@ populate ``litellm.anthropic_models`` at import, which is what lets a bare
 ``anthropic/*`` wildcard deployment).
 """
 
-import json
 import os
 
-import pytest
 
 from litellm.constants import BEDROCK_CONVERSE_MODELS
-from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap
 
 REPO_ROOT = os.path.join(os.path.dirname(__file__), "../..")
 
@@ -34,37 +31,7 @@ ALL_SONNET_5_VARIANTS = (
 )
 
 
-def _load_root_cost_map() -> dict:
-    json_path = os.path.join(REPO_ROOT, "model_prices_and_context_window.json")
-    with open(json_path) as f:
-        return json.load(f)
-
-
-def test_sonnet_5_present_in_bundled_backup():
-    """The bundled backup is the runtime fallback (and what tests load with
-    ``LITELLM_LOCAL_MODEL_COST_MAP=True``); it must carry the same entries as the
-    root cost map, otherwise the model resolves on one path but not the other."""
-    backup = GetModelCostMap.load_local_model_cost_map()
-    for model_name in ALL_SONNET_5_VARIANTS:
-        assert model_name in backup, f"Missing from backup cost map: {model_name}"
-
-
 def test_sonnet_5_registered_for_bedrock_converse():
     assert "anthropic.claude-sonnet-5" in BEDROCK_CONVERSE_MODELS
 
 
-@pytest.mark.parametrize(
-    "cost_map",
-    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
-    ids=["root", "bundled_backup"],
-)
-def test_sonnet_5_all_variants_carry_adaptive_thinking_flag(cost_map):
-    """Every Sonnet 5 entry must advertise ``supports_adaptive_thinking``.
-
-    Adaptive-thinking detection is cost-map driven, so a single variant missing
-    the flag silently sends the legacy ``thinking.type='enabled'`` shape and the
-    provider 400s. This guards against a future variant being added without it."""
-    variants = [k for k in cost_map if "claude-sonnet-5" in k]
-    assert variants, "no claude-sonnet-5 entries found in cost map"
-    missing = [k for k in variants if cost_map[k].get("supports_adaptive_thinking") is not True]
-    assert not missing, f"missing supports_adaptive_thinking: {missing}"
diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py
index ff28e69a909..b6bd03adc86 100644
--- a/tests/test_litellm/test_cost_calculator.py
+++ b/tests/test_litellm/test_cost_calculator.py
@@ -27,7 +27,6 @@ from litellm.types.utils import (
     PromptTokensDetailsWrapper,
     Usage,
 )
-from litellm.utils import TranscriptionResponse
 
 
 @pytest.fixture
@@ -2375,28 +2374,6 @@ def test_anthropic_geo_and_fast_multipliers_compose(_local_model_cost_map, monke
     assert completion_cost == pytest.approx(500 * 25e-6 * 2.0 * 1.1)
 
 
-@pytest.mark.parametrize(
-    "model,expected_fast",
-    [
-        ("claude-opus-5", 2.0),
-        ("claude-opus-4-8", 2.0),
-        ("claude-opus-4-6", None),
-        ("claude-opus-4-6-20260205", None),
-        ("claude-opus-4-7", None),
-        ("claude-opus-4-7-20260416", None),
-    ],
-)
-def test_anthropic_fast_multiplier_only_on_models_with_fast_mode(_local_model_cost_map, model, expected_fast):
-    """
-    Anthropic serves fast mode on Opus 5 and Opus 4.8 only, at 2x. Opus 4.6 and
-    4.7 accept the ``speed`` request param but are always served standard, so a
-    ``fast`` multiplier on their map entries overbills every request that asked
-    for fast and was served standard.
-    """
-    entry = litellm.model_cost[model]
-    assert entry["provider_specific_entry"].get("fast") == expected_fast
-
-
 @pytest.mark.parametrize(
     "model",
     ["claude-sonnet-4-6", "claude-mythos-5", "claude-mythos-preview"],
@@ -3376,24 +3353,6 @@ def test_combine_usage_objects_sums_mirrored_cache_write_fields_once():
     assert combined_pair.prompt_tokens_details.cache_creation_tokens == 100
 
 
-def _together_chat_response(
-    model: str, prompt_tokens: int, completion_tokens: int, cached_tokens: int
-) -> ModelResponse:
-    return ModelResponse(
-        id="chatcmpl-together-cache",
-        choices=[{"finish_reason": "stop", "index": 0, "message": {"content": "acknowledged", "role": "assistant"}}],
-        created=1756164000,
-        model=model,
-        object="chat.completion",
-        usage=Usage(
-            prompt_tokens=prompt_tokens,
-            completion_tokens=completion_tokens,
-            total_tokens=prompt_tokens + completion_tokens,
-            prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=cached_tokens),
-        ),
-    )
-
-
 def test_select_model_name_strips_unregistered_alias_prefix(_local_model_cost_map):
     """A router-facing model_name alias containing "/" whose leading segment is NOT a
     registered provider must not be double-prefixed into a non-existent cost key.
diff --git a/tests/test_litellm/test_dashscope_image_generation.py b/tests/test_litellm/test_dashscope_image_generation.py
index 119efa010e0..1dd0b322623 100644
--- a/tests/test_litellm/test_dashscope_image_generation.py
+++ b/tests/test_litellm/test_dashscope_image_generation.py
@@ -5,7 +5,6 @@ qwen-image-3.0, qwen-image-3.0-pro).
 Run in docker: pytest tests/test_litellm/test_dashscope_image_generation.py -v
 """
 
-import json
 from unittest.mock import MagicMock, patch
 
 import httpx
@@ -16,7 +15,7 @@ from litellm.llms.dashscope.image_generation.transformation import (
     DashScopeImageGenerationConfig,
     DEFAULT_API_BASE,
 )
-from litellm.types.utils import ImageObject, ImageResponse
+from litellm.types.utils import ImageResponse
 from litellm.utils import get_llm_provider
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
@@ -46,40 +45,6 @@ def test_get_llm_provider_returns_dashscope(model_string: str):
 # ---------------------------------------------------------------------------
 
 
-@pytest.mark.parametrize(
-    "model_string, custom_provider",
-    [
-        ("dashscope/qwen-image-2.0", "dashscope"),
-        ("dashscope/qwen-image-2.0-pro", "dashscope"),
-        ("dashscope/qwen-image-3.0", "dashscope"),
-        ("dashscope/qwen-image-3.0-pro", "dashscope"),
-    ],
-)
-def test_get_model_info_mode_is_image_generation(
-    model_string: str, custom_provider: str
-):
-    import os
-
-    prev_env = os.environ.get("LITELLM_LOCAL_MODEL_COST_MAP")
-    prev_model_cost = litellm.model_cost
-    try:
-        os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-        litellm.model_cost = litellm.get_model_cost_map(url="")
-
-        info = litellm.get_model_info(
-            model=model_string, custom_llm_provider=custom_provider
-        )
-        assert (
-            info["mode"] == "image_generation"
-        ), f"Expected mode='image_generation', got '{info['mode']}'"
-    finally:
-        if prev_env is None:
-            os.environ.pop("LITELLM_LOCAL_MODEL_COST_MAP", None)
-        else:
-            os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = prev_env
-        litellm.model_cost = prev_model_cost
-
-
 # ---------------------------------------------------------------------------
 # 3. Request transformation
 # ---------------------------------------------------------------------------
diff --git a/tests/test_litellm/test_deepseek_model_metadata.py b/tests/test_litellm/test_deepseek_model_metadata.py
index 264f5e65fc5..91ed54b826c 100644
--- a/tests/test_litellm/test_deepseek_model_metadata.py
+++ b/tests/test_litellm/test_deepseek_model_metadata.py
@@ -15,7 +15,6 @@ import os
 import litellm
 from litellm.utils import (
     _supports_factory,
-    supports_response_schema,
 )
 
 # ---------------------------------------------------------------------------
@@ -59,18 +58,6 @@ class TestSupportsResponseSchemaDeepSeek:
     """All calling conventions for DeepSeek should return True for
     ``supports_response_schema``."""
 
-    def test_provider_slash_model(self):
-        assert supports_response_schema(model="deepseek/deepseek-chat") is True
-
-    def test_explicit_provider(self):
-        assert supports_response_schema(model="deepseek-chat", custom_llm_provider="deepseek") is True
-
-    def test_reasoner_provider_slash_model(self):
-        assert supports_response_schema(model="deepseek/deepseek-reasoner") is True
-
-    def test_reasoner_explicit_provider(self):
-        assert supports_response_schema(model="deepseek-reasoner", custom_llm_provider="deepseek") is True
-
 
 # ---------------------------------------------------------------------------
 # Fallback-logic test – bare model entry used when prefixed is incomplete
diff --git a/tests/test_litellm/test_mistral_zai_glm_5_2_model_metadata.py b/tests/test_litellm/test_mistral_zai_glm_5_2_model_metadata.py
index 8467cbd43b1..c5fe247aa51 100644
--- a/tests/test_litellm/test_mistral_zai_glm_5_2_model_metadata.py
+++ b/tests/test_litellm/test_mistral_zai_glm_5_2_model_metadata.py
@@ -4,7 +4,6 @@ from pathlib import Path
 import pytest
 
 import litellm
-from litellm.utils import supports_prompt_caching, supports_reasoning
 
 REPO_ROOT = Path(__file__).parents[2]
 MAIN_PATH = REPO_ROOT / "model_prices_and_context_window.json"
@@ -33,16 +32,6 @@ def local_model_cost_map(monkeypatch):
     litellm.get_model_info.cache_clear()
 
 
-@pytest.mark.parametrize("model", GLM_5_2_MODELS)
-def test_zai_glm_5_2_capabilities_are_visible_to_callers(local_model_cost_map, model):
-    """Mistral advertises reasoning and prompt caching on this model, so the helpers
-    every caller checks before sending a request must say so too."""
-    assert supports_reasoning(model=model) is True
-    assert supports_prompt_caching(model=model) is True
-
-    assert litellm.get_model_info(model=model)
-
-
 @pytest.mark.parametrize("model", GLM_5_2_MODELS)
 def test_backup_matches_main(model):
     """Ensure the bundled (backup) cost map stays in sync with the canonical file."""
diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py
index 4618c156046..876c36b1071 100644
--- a/tests/test_litellm/test_utils.py
+++ b/tests/test_litellm/test_utils.py
@@ -162,15 +162,6 @@ def test_prompt_tokens_details_cache_write_creation_stay_in_sync_on_assignment()
     assert details.cache_write_tokens == details.cache_creation_tokens == 375
 
 
-def test_get_model_info_surfaces_supported_endpoints(local_model_cost_map):
-    """supported_endpoints ships in the cost map and is declared on ModelInfoBase,
-    but the constructor never copied it, so get_model_info always returned None.
-    The realtime health check reads it to spot GA-only transcription models
-    (LIT-6240)."""
-    info = litellm.get_model_info(model="gpt-realtime-whisper", custom_llm_provider="azure")
-    assert info["supported_endpoints"] == ["/v1/realtime", "/v1/realtime/transcription_sessions"]
-
-
 def test_potential_model_names_keeps_provider_prefixed_candidate():
     """A provider whose own model ids repeat the litellm provider name (Perplexity's
     Agent API serves `perplexity/glm-5.2`, mapped as `perplexity/perplexity/glm-5.2`)
@@ -236,23 +227,6 @@ def test_check_provider_match_github_allows_upstream_provider_metadata():
     )
 
 
-def test_supports_function_calling_github_openai_alias():
-    assert litellm.utils.supports_function_calling(model="github/gpt-4o-mini") is True
-    assert litellm.utils.supports_function_calling(model="gpt-4o-mini", custom_llm_provider="github") is True
-
-
-def test_supports_function_calling_github_anthropic_alias():
-    assert litellm.utils.supports_function_calling(model="github/claude-3-7-sonnet-20250219") is True
-
-
-def test_supports_function_calling_deepinfra_llama():
-    """Test that deepinfra Llama models correctly report function calling support.
-
-    Regression test for https://github.com/BerriAI/litellm/issues/22619
-    """
-    assert litellm.utils.supports_function_calling(model="deepinfra/meta-llama/Llama-3.3-70B-Instruct-Turbo") is True
-
-
 def test_supports_function_calling_unknown_github_alias_returns_false():
     assert litellm.utils.supports_function_calling(model="github/non-existent-model-for-capability-check") is False
 
@@ -565,25 +539,6 @@ def test_all_model_configs():
     ) == {"max_output_tokens": 10}
 
 
-def test_anthropic_web_search_in_model_info(monkeypatch):
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-
-    supported_models = [
-        "anthropic/claude-4-sonnet-20250514",
-        "anthropic/claude-sonnet-4-5-20250929",
-    ]
-    for model in supported_models:
-        from litellm.utils import get_model_info
-
-        model_info = get_model_info(model)
-        assert model_info is not None
-        assert model_info["supports_web_search"] is True, f"Model {model} should support web search"
-        assert model_info["search_context_cost_per_query"] is not None, (
-            f"Model {model} should have a search context cost per query"
-        )
-
-
 def test_cohere_embedding_optional_params():
     from litellm import get_optional_params_embeddings
 
@@ -1129,13 +1084,6 @@ def test_get_model_info_bedrock_regional_inference_profile_pricing(local_model_c
     assert control["key"] == "au.anthropic.claude-opus-4-8"
 
 
-def test_get_model_info_bedrock_double_provider_prefix_resolves(local_model_cost_map):
-    """A doubled bedrock/ prefix routes at runtime via strip_bedrock_routing_prefix,
-    so model info must resolve it to the same entry the request actually bills as."""
-    info = litellm.get_model_info(model="bedrock/bedrock/us.anthropic.claude-sonnet-4-6")
-    assert info["key"] == "us.anthropic.claude-sonnet-4-6"
-
-
 def test_openai_models_in_model_info(monkeypatch):
     monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
     litellm.model_cost = litellm.get_model_cost_map(url="")
@@ -1149,51 +1097,6 @@ def test_openai_models_in_model_info(monkeypatch):
     assert len(violated_models) == 0, f"The following models should support pdf input: {violated_models}"
 
 
-def test_supports_tool_choice_simple_tests():
-    """
-    simple sanity checks
-    """
-    assert litellm.utils.supports_tool_choice(model="gpt-4o") == True
-    assert litellm.utils.supports_tool_choice(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0") == True
-    assert litellm.utils.supports_tool_choice(model="anthropic.claude-3-sonnet-20240229-v1:0") is True
-
-    assert (
-        litellm.utils.supports_tool_choice(
-            model="anthropic.claude-3-sonnet-20240229-v1:0",
-            custom_llm_provider="bedrock_converse",
-        )
-        is True
-    )
-
-    assert litellm.utils.supports_tool_choice(model="perplexity/sonar") is False
-
-
-@pytest.mark.usefixtures("local_model_cost_map")
-@pytest.mark.parametrize(
-    "model",
-    [
-        "amazon.nova-lite-v1:0",
-        "amazon.nova-micro-v1:0",
-        "amazon.nova-pro-v1:0",
-        "apac.amazon.nova-lite-v1:0",
-        "apac.amazon.nova-micro-v1:0",
-        "apac.amazon.nova-pro-v1:0",
-        "bedrock/us-gov-east-1/amazon.nova-pro-v1:0",
-        "bedrock/us-gov-west-1/amazon.nova-lite-v1:0",
-        "bedrock/us-gov-west-1/amazon.nova-micro-v1:0",
-        "bedrock/us-gov-west-1/amazon.nova-pro-v1:0",
-        "eu.amazon.nova-lite-v1:0",
-        "eu.amazon.nova-micro-v1:0",
-        "eu.amazon.nova-pro-v1:0",
-        "us.amazon.nova-lite-v1:0",
-        "us.amazon.nova-micro-v1:0",
-        "us.amazon.nova-pro-v1:0",
-    ],
-)
-def test_amazon_nova_v1_understanding_models_support_tool_choice(model: str) -> None:
-    assert litellm.utils.supports_tool_choice(model=model) is True
-
-
 def test_check_provider_match():
     """
     Test the _check_provider_match function for various provider scenarios
@@ -1303,42 +1206,6 @@ for commitment in BEDROCK_COMMITMENTS:
 print("block_list", block_list)
 
 
-def test_supports_computer_use_utility(monkeypatch):
-    """
-    Tests the litellm.utils.supports_computer_use utility function.
-    """
-    from litellm.utils import supports_computer_use
-
-    # Ensure LITELLM_LOCAL_MODEL_COST_MAP is set for consistent test behavior,
-    # as supports_computer_use relies on get_model_info.
-    # This also requires litellm.model_cost to be populated.
-    original_env_var = os.getenv("LITELLM_LOCAL_MODEL_COST_MAP")
-    original_model_cost = getattr(litellm, "model_cost", None)
-
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    litellm.model_cost = litellm.get_model_cost_map(url="")  # Load with local/backup
-
-    try:
-        # Test a model known to support computer_use from backup JSON
-        supports_cu_anthropic = supports_computer_use(model="anthropic/claude-4-sonnet-20250514")
-        assert supports_cu_anthropic is True
-
-        # Test a model known not to have the flag or set to false (defaults to False via get_model_info)
-        supports_cu_gpt = supports_computer_use(model="gpt-3.5-turbo")
-        assert supports_cu_gpt is False
-    finally:
-        # Restore original environment and model_cost to avoid side effects
-        if original_env_var is None:
-            del os.environ["LITELLM_LOCAL_MODEL_COST_MAP"]
-        else:
-            monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", original_env_var)
-
-        if original_model_cost is not None:
-            litellm.model_cost = original_model_cost
-        elif hasattr(litellm, "model_cost"):
-            delattr(litellm, "model_cost")
-
-
 @pytest.mark.parametrize(
     "model, custom_llm_provider",
     [
@@ -1658,32 +1525,6 @@ class TestProxyFunctionCalling:
         # For now, we expect False (current behavior), but document the limitation
         assert proxy_result is False, f"Current limitation: {proxy_model_with_hints} returns False without inference"
 
-    @pytest.mark.parametrize(
-        "proxy_model,expected_result",
-        [
-            # Test specific proxy models that should support function calling
-            ("litellm_proxy/gpt-3.5-turbo", True),
-            ("litellm_proxy/gpt-4", True),
-            ("litellm_proxy/gpt-4o", True),
-            ("litellm_proxy/claude-sonnet-4-6", True),
-            ("litellm_proxy/gemini/gemini-2.5-pro", True),
-            # Test proxy models that should not support function calling
-            ("litellm_proxy/command-nightly", False),
-            ("litellm_proxy/anthropic.claude-instant-v1", False),
-        ],
-    )
-    def test_proxy_only_function_calling_support(self, proxy_model, expected_result):
-        """
-        Test proxy models independently to ensure they report correct function calling support.
-
-        This test focuses on proxy models without comparing to direct models,
-        useful for cases where we only care about the proxy behavior.
-        """
-        try:
-            result = supports_function_calling(model=proxy_model)
-            assert result == expected_result, f"Proxy model {proxy_model} returned {result}, expected {expected_result}"
-        except Exception as e:
-            pytest.fail(f"Error testing proxy model {proxy_model}: {e}")
 
     def test_litellm_utils_supports_function_calling_import(self):
         """Test that supports_function_calling can be imported from litellm.utils."""
@@ -1704,28 +1545,6 @@ class TestProxyFunctionCalling:
         except Exception as e:
             pytest.fail(f"Failed to access litellm.supports_function_calling: {e}")
 
-    @pytest.mark.parametrize(
-        "model_name",
-        [
-            "litellm_proxy/gpt-3.5-turbo",
-            "litellm_proxy/gpt-4",
-            "litellm_proxy/claude-sonnet-4-6",
-            "litellm_proxy/gemini/gemini-2.5-pro",
-        ],
-    )
-    def test_proxy_model_with_custom_llm_provider_none(self, model_name):
-        """
-        Test proxy models with custom_llm_provider=None parameter.
-
-        This tests the supports_function_calling function with the custom_llm_provider
-        parameter explicitly set to None, which is a common usage pattern.
-        """
-        try:
-            result = supports_function_calling(model=model_name, custom_llm_provider=None)
-            # All the models in this test should support function calling
-            assert result is True, f"Model {model_name} should support function calling but returned {result}"
-        except Exception as e:
-            pytest.fail(f"Error testing {model_name} with custom_llm_provider=None: {e}")
 
     def test_edge_cases_and_malformed_proxy_models(self):
         """Test edge cases and malformed proxy model names."""
@@ -1963,84 +1782,6 @@ class TestProxyFunctionCalling:
             f"(without config context). Description: {description}"
         )
 
-    def test_real_world_proxy_config_documentation(self):
-        """
-        Document how real-world proxy configurations would handle model mappings.
-
-        This test provides documentation on how the proxy server configuration
-        would typically map custom model names to underlying models.
-        """
-        print("""
-        
-        REAL-WORLD PROXY SERVER CONFIGURATION EXAMPLE:
-        ===============================================
-        
-        In a proxy_server_config.yaml file, you would define:
-        
-        model_list:
-          - model_name: bedrock-claude-3-haiku
-            litellm_params:
-              model: bedrock/converse/anthropic.claude-3-haiku-20240307-v1:0
-              aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID
-              aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY
-              aws_region_name: us-east-1
-              
-          - model_name: bedrock-claude-3-sonnet
-            litellm_params:
-              model: bedrock/converse/anthropic.claude-3-sonnet-20240229-v1:0
-              aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID
-              aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY
-              aws_region_name: us-east-1
-              
-          - model_name: prod-claude-haiku
-            litellm_params:
-              model: bedrock/converse/anthropic.claude-3-haiku-20240307-v1:0
-              aws_access_key_id: os.environ/PROD_AWS_ACCESS_KEY_ID
-              aws_secret_access_key: os.environ/PROD_AWS_SECRET_ACCESS_KEY
-              aws_region_name: us-west-2
-        
-        
-        FUNCTION CALLING WITH PROXY SERVER:
-        ===================================
-        
-        When using the proxy server with this configuration:
-        
-        1. Client calls: supports_function_calling("bedrock-claude-3-haiku")
-        2. Proxy server resolves to: bedrock/converse/anthropic.claude-3-haiku-20240307-v1:0
-        3. LiteLLM evaluates the underlying model's capabilities
-        4. Returns: True (because Claude 3 Haiku supports function calling)
-        
-        Without the proxy server configuration context, LiteLLM cannot resolve
-        the custom model name and returns False.
-        
-        
-        BEDROCK CONVERSE API BENEFITS:
-        ==============================
-        
-        The Bedrock Converse API provides:
-        - Standardized function calling interface across providers
-        - Better tool use capabilities compared to legacy APIs
-        - Consistent request/response format
-        - Enhanced streaming support for function calls
-        
-        """)
-
-        # Verify that direct underlying models work as expected
-        bedrock_models = [
-            "bedrock/converse/anthropic.claude-3-haiku-20240307-v1:0",
-            "bedrock/converse/anthropic.claude-3-sonnet-20240229-v1:0",
-            "bedrock/converse/anthropic.claude-sonnet-4-5-20250929-v1:0",
-        ]
-
-        for model in bedrock_models:
-            try:
-                result = supports_function_calling(model)
-                print(f"Direct test - {model}: {result}")
-                # Claude 3 models should support function calling
-                assert result is True, f"Claude 3 model should support function calling: {model}"
-            except Exception as e:
-                print(f"Could not test {model}: {e}")
-
 
 def test_register_model_with_scientific_notation():
     """
@@ -3637,28 +3378,6 @@ _FIREWORKS_ROUTER_SHORT_FORMS = [
 ]
 
 
-def _assert_fireworks_entry(
-    model_cost,
-    model_path,
-    expected_max_input,
-    expected_max_output,
-    expected_vision,
-    expected_reasoning,
-):
-    info = model_cost.get(f"fireworks_ai/{model_path}")
-    assert info is not None, f"fireworks_ai/{model_path} missing from model cost map"
-    assert info["litellm_provider"] == "fireworks_ai"
-    assert info["mode"] == "chat"
-    assert info["input_cost_per_token"] > 0
-    assert info["output_cost_per_token"] > 0
-    assert "cache_read_input_token_cost" in info
-    assert info["supports_function_calling"] is True
-    assert info["supports_tool_choice"] is True
-    assert info["supports_reasoning"] is expected_reasoning
-    assert info["supports_response_schema"] is True
-    assert info["supports_vision"] is expected_vision
-
-
 @pytest.fixture
 def fireworks_short_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]:
     monkeypatch.setattr(
@@ -3985,21 +3704,6 @@ def test_get_prompt_cache_min_tokens_resolves_per_model(
     assert get_prompt_cache_min_tokens(model=model) == expected_min_tokens
 
 
-def test_get_prompt_cache_min_tokens_uniform_for_fable_5_across_platforms(local_model_cost_map: None) -> None:
-    """Anthropic removed the Amazon Bedrock override for Claude Fable 5, so its 512-token minimum
-    now applies on every platform. The Bedrock entries carried the old 1024 and the re-export
-    entries carried nothing, so the router judged 512-1023-token prefixes uncacheable and skipped
-    prompt-cache-affinity routing for prompts the provider demonstrably caches (issue #35011)."""
-    wrong: Final = {
-        model: get_prompt_cache_min_tokens(model=model)
-        for model, info in litellm.model_cost.items()
-        if "fable-5" in model
-        and info.get("supports_prompt_caching")
-        and get_prompt_cache_min_tokens(model=model) != 512
-    }
-    assert not wrong, f"every Claude Fable 5 entry must carry prompt_cache_min_tokens 512: {wrong}"
-
-
 ANTHROPIC_REEXPORT_CACHE_MIN: Final = {
     "azure_ai/claude-fable-5": 512,
     "azure_ai/claude-haiku-4-5": 4096,
@@ -4048,21 +3752,6 @@ ANTHROPIC_REEXPORT_CACHE_MIN: Final = {
 }
 
 
-def test_anthropic_reexport_entries_carry_explicit_prompt_cache_min_tokens(local_model_cost_map: None) -> None:
-    """Regression for issue #35011: these re-export entries carried no prompt_cache_min_tokens, so
-    they silently inherited the 1024 default. That skipped cache-affinity routing for Fable 5's
-    512-1023-token prefixes and reported 1024-4095-token prompts as cacheable on the 2048/4096
-    models. The entry must be explicit so a default change can never re-break them, which is why
-    this asserts the cost-map value itself and not just the resolver's answer."""
-    wrong: Final = {
-        model: (litellm.model_cost[model].get("prompt_cache_min_tokens"), get_prompt_cache_min_tokens(model=model))
-        for model, expected in ANTHROPIC_REEXPORT_CACHE_MIN.items()
-        if litellm.model_cost[model].get("prompt_cache_min_tokens") != expected
-        or get_prompt_cache_min_tokens(model=model) != expected
-    }
-    assert not wrong, f"(cost-map value, resolved value) diverge from Anthropic's published minimums: {wrong}"
-
-
 GEMINI_4096_CACHE_MIN_MODELS: Final = tuple(
     prefix + base
     for base in (
@@ -5981,82 +5670,6 @@ def test_completion_finishes_response_metadata_before_handing_the_response_to_th
     assert snapshot["api_base"]
 
 
-def test_fireworks_models_in_backup_cost_map():
-    import json
-    from pathlib import Path
-
-    json_path = Path(__file__).parents[2] / "litellm" / "model_prices_and_context_window_backup.json"
-    with open(json_path) as f:
-        model_cost = json.load(f)
-
-    for entry in _FIREWORKS_MODELS:
-        _assert_fireworks_entry(model_cost, *entry)
-
-    for short in _FIREWORKS_SHORT_FORMS:
-        long_key = f"fireworks_ai/accounts/fireworks/models/{short}"
-        short_key = f"fireworks_ai/{short}"
-        assert model_cost.get(short_key) == model_cost.get(long_key), (
-            f"short-form {short_key} does not match long-form {long_key}"
-        )
-
-    for short in _FIREWORKS_ROUTER_SHORT_FORMS:
-        long_key = f"fireworks_ai/accounts/fireworks/routers/{short}"
-        short_key = f"fireworks_ai/{short}"
-        assert model_cost.get(short_key) == model_cost.get(long_key), (
-            f"short-form {short_key} does not match long-form {long_key}"
-        )
-
-
-def test_fireworks_models_in_cost_map():
-    import json
-    from pathlib import Path
-
-    json_path = Path(__file__).parents[2] / "model_prices_and_context_window.json"
-    with open(json_path) as f:
-        model_cost = json.load(f)
-
-    for entry in _FIREWORKS_MODELS:
-        _assert_fireworks_entry(model_cost, *entry)
-
-    for short in _FIREWORKS_SHORT_FORMS:
-        long_key = f"fireworks_ai/accounts/fireworks/models/{short}"
-        short_key = f"fireworks_ai/{short}"
-        assert model_cost.get(short_key) == model_cost.get(long_key), (
-            f"short-form {short_key} does not match long-form {long_key}"
-        )
-
-    for short in _FIREWORKS_ROUTER_SHORT_FORMS:
-        long_key = f"fireworks_ai/accounts/fireworks/routers/{short}"
-        short_key = f"fireworks_ai/{short}"
-        assert model_cost.get(short_key) == model_cost.get(long_key), (
-            f"short-form {short_key} does not match long-form {long_key}"
-        )
-
-
-def test_fireworks_short_model_names_resolve_to_long_cost_map_keys(fireworks_short_model_cost_map: None) -> None:
-    model_info = litellm.get_model_info("fireworks_ai/glm-5p3")
-    assert model_info["key"] == "fireworks_ai/accounts/fireworks/models/glm-5p3"
-
-    model_info = litellm.get_model_info("glm-5p3", custom_llm_provider="fireworks_ai")
-    assert model_info["key"] == "fireworks_ai/accounts/fireworks/models/glm-5p3"
-
-    model_info = litellm.get_model_info("fireworks_ai/glm-5p3-fast")
-    assert model_info["key"] == "fireworks_ai/accounts/fireworks/routers/glm-5p3-fast"
-
-    model_info = litellm.get_model_info("fireworks_ai/nomic-ai/nomic-embed-text-v1.5")
-    assert model_info["key"] == "fireworks_ai/nomic-ai/nomic-embed-text-v1.5"
-
-    with pytest.raises(Exception, match="isn't mapped"):
-        litellm.get_model_info("fireworks_ai/does-not-exist")
-
-
-def test_get_model_info_bedrock_regional_profile_without_entry_falls_back_to_base(local_model_cost_map):
-    """A regional profile with no dedicated cost-map entry must still resolve to its
-    region-stripped base entry."""
-    info = litellm.get_model_info(model="bedrock/apac.anthropic.claude-opus-4-8")
-    assert info["key"] == "anthropic.claude-opus-4-8"
-
-
 def test_get_model_info_gemini(monkeypatch):
     """
     Tests if ALL gemini models have 'tpm' and 'rpm' in the model info
@@ -6079,153 +5692,3 @@ def test_get_model_info_gemini(monkeypatch):
             assert info.get("rpm") is not None, f"{model} does not have rpm"
 
 
-def test_get_model_info_resolves_provider_prefixed_model_ids(local_model_cost_map):
-    """Perplexity's Agent API third-party models are keyed `perplexity/perplexity/<id>`
-    because Perplexity's own id already starts with `perplexity/`. Callers run
-    `get_llm_provider` first, which hands `_get_potential_model_names` model
-    `perplexity/glm-5.2` with provider `perplexity`, and every candidate but the
-    provider-prefixed one strips that second `perplexity/` off. Regression: the
-    entries were unreachable from `supports_reasoning` and from the cost calculator's
-    per-token fallback, so a mapped model reported no reasoning support and raised
-    "This model isn't mapped yet" on the only path where its rates are ever used."""
-    for model, reasoning in (
-        ("perplexity/perplexity/glm-5.2", True),
-        ("perplexity/perplexity/kimi-k3", True),
-        ("perplexity/perplexity/deepseek-v4-flash-0731", True),
-        ("perplexity/perplexity/kimi-k2.7-code", False),
-        ("perplexity/perplexity/nemotron-3.5-lightning-30b-a3b", True),
-        ("perplexity/perplexity/nemotron-3-ultra-550b-a55b", True),
-    ):
-        assert litellm.supports_reasoning(model=model) is reasoning, model
-
-    via_provider = litellm.get_model_info(model="perplexity/glm-5.2", custom_llm_provider="perplexity")
-    assert via_provider["key"] == "perplexity/perplexity/glm-5.2"
-    assert via_provider["mode"] == "responses"
-
-    lightning = litellm.get_model_info(
-        model="perplexity/nemotron-3.5-lightning-30b-a3b", custom_llm_provider="perplexity"
-    )
-    assert lightning["key"] == "perplexity/perplexity/nemotron-3.5-lightning-30b-a3b"
-    assert lightning["mode"] == "responses"
-
-    ultra = litellm.get_model_info(model="perplexity/perplexity/nemotron-3-ultra-550b-a55b")
-    assert ultra["key"] == "perplexity/perplexity/nemotron-3-ultra-550b-a55b"
-
-
-def test_get_model_info_shows_supports_computer_use(monkeypatch):
-    """
-    Tests if 'supports_computer_use' is correctly retrieved by get_model_info.
-    We'll use 'claude-4-sonnet-20250514' as it's configured
-    in the backup JSON to have supports_computer_use: True.
-    """
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    # Ensure litellm.model_cost is loaded, relying on the backup mechanism if primary fails
-    # as per previous debugging.
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-
-    # This model should have 'supports_computer_use': True in the backup JSON
-    model_known_to_support_computer_use = "claude-4-sonnet-20250514"
-    info = litellm.get_model_info(model_known_to_support_computer_use)
-
-    # After the fix in utils.py, this should now be present and True
-    assert info.get("supports_computer_use") is True
-
-
-def test_get_model_info_surfaces_supports_adaptive_thinking(local_model_cost_map):
-    """supports_adaptive_thinking must flow through get_model_info like every other
-    capability flag: both from an explicit cost-map entry and from a
-    fallback-generalization rule for an unmapped model. Regression: the field shipped
-    in the JSON but was never declared on ModelInfo nor copied during construction, so
-    get_model_info (and _supports_factory) silently dropped it for any provider-prefixed
-    or unmapped name."""
-    explicit = litellm.get_model_info(model="claude-opus-4-8")
-    assert explicit["supports_adaptive_thinking"] is True
-
-    generalized = litellm.get_model_info(model="claude-opus-4-9", custom_llm_provider="anthropic")
-    assert generalized["supports_adaptive_thinking"] is True
-
-
-def test_get_model_info_surfaces_supports_parallel_function_calling(local_model_cost_map):
-    """A registry entry's supports_parallel_function_calling must read back through get_model_info
-    and litellm.supports_parallel_function_calling. Regression: the key was never copied into
-    ModelInfo, so provider-prefixed entries read None / False even when the map said True, and an
-    explicit False was indistinguishable from unset."""
-    declared_true = litellm.get_model_info(model="together_ai/zai-org/GLM-5.3-Flash")
-    assert declared_true["supports_parallel_function_calling"] is True
-    assert litellm.supports_parallel_function_calling(model="together_ai/zai-org/GLM-5.3-Flash") is True
-
-
-def test_model_info_for_fireworks_short_form_models():
-    """
-    Test that fireworks_ai short-form model entries (fireworks_ai/<model>)
-    are correctly configured in model_prices_and_context_window.json.
-
-    These entries enable cost attribution for models called via short-form
-    names (e.g., fireworks_ai/glm-4p7 instead of
-    fireworks_ai/accounts/fireworks/models/glm-4p7).
-    """
-    import json
-    from pathlib import Path
-
-    json_path = Path(__file__).parents[2] / "model_prices_and_context_window.json"
-    with open(json_path) as f:
-        model_cost = json.load(f)
-
-    # glm-4p7: short-form and long-form
-    for key in [
-        "fireworks_ai/glm-4p7",
-        "fireworks_ai/accounts/fireworks/models/glm-4p7",
-    ]:
-        info = model_cost.get(key)
-        assert info is not None, f"{key} not found in model_prices_and_context_window.json"
-        assert info["litellm_provider"] == "fireworks_ai"
-        assert info["mode"] == "chat"
-        assert info["supports_reasoning"] is True
-
-    # minimax-m2p1: short-form and long-form
-    for key in [
-        "fireworks_ai/minimax-m2p1",
-        "fireworks_ai/accounts/fireworks/models/minimax-m2p1",
-    ]:
-        info = model_cost.get(key)
-        assert info is not None, f"{key} not found in model_prices_and_context_window.json"
-        assert info["litellm_provider"] == "fireworks_ai"
-        assert info["mode"] == "chat"
-
-    # kimi-k2p5: short-form only (long-form already existed)
-    info = model_cost.get("fireworks_ai/kimi-k2p5")
-    assert info is not None, "fireworks_ai/kimi-k2p5 not found in model_prices_and_context_window.json"
-    assert info["litellm_provider"] == "fireworks_ai"
-    assert info["mode"] == "chat"
-
-
-def test_model_info_for_vertex_ai_deepseek_model():
-    model_info = litellm.get_model_info(model="vertex_ai/deepseek-ai/deepseek-r1-0528-maas")
-    assert model_info is not None
-    assert model_info["litellm_provider"] == "vertex_ai-deepseek_models"
-    assert model_info["mode"] == "chat"
-
-    assert model_info["input_cost_per_token"] is not None
-    assert model_info["output_cost_per_token"] is not None
-
-
-def test_provider_prefixed_lookup_never_outranks_an_existing_row(local_model_cost_map):
-    """The provider-prefixed candidate is tried last, after every candidate that
-    already existed, so no model that resolves today can change answer. `perplexity/sonar`
-    is the case that proves it: both `perplexity/sonar` and `perplexity/perplexity/sonar`
-    are cost-map keys, and the shorter one must keep winning."""
-    sonar = litellm.get_model_info(model="sonar", custom_llm_provider="perplexity")
-    assert sonar["key"] == "perplexity/sonar"
-    assert sonar["mode"] == "chat"
-
-    still_sonar = litellm.get_model_info(model="perplexity/sonar", custom_llm_provider="perplexity")
-    assert still_sonar["key"] == "perplexity/sonar"
-    assert still_sonar["mode"] == "chat"
-
-    for model, provider, expected_key in (
-        ("claude-sonnet-4-5", "anthropic", "claude-sonnet-4-5"),
-        ("anthropic/claude-sonnet-4-5", "anthropic", "claude-sonnet-4-5"),
-        ("gemini/gemini-2.0-flash", "gemini", "gemini/gemini-2.0-flash"),
-        ("openrouter/openai/gpt-4o", "openrouter", "openrouter/openai/gpt-4o"),
-    ):
-        assert litellm.get_model_info(model=model, custom_llm_provider=provider)["key"] == expected_key