diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index a98e209f461..22b75127d03 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -39226,6 +39226,48 @@
         "max_tokens": 8192,
         "mode": "embedding"
     },
+    "mistral/mistral-large-4": {
+        "cache_read_input_token_cost": 6.8e-08,
+        "input_cost_per_token": 6.8e-07,
+        "litellm_provider": "mistral",
+        "max_input_tokens": 524288,
+        "max_tokens": 524288,
+        "mode": "chat",
+        "output_cost_per_token": 2.09e-06,
+        "reasoning_effort_levels": [
+            "none",
+            "high"
+        ],
+        "source": "https://docs.mistral.ai/models/mistral-large-4",
+        "supports_assistant_prefill": true,
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "mistral/mistral-large-4-0": {
+        "cache_read_input_token_cost": 6.8e-08,
+        "input_cost_per_token": 6.8e-07,
+        "litellm_provider": "mistral",
+        "max_input_tokens": 524288,
+        "max_tokens": 524288,
+        "mode": "chat",
+        "output_cost_per_token": 2.09e-06,
+        "reasoning_effort_levels": [
+            "none",
+            "high"
+        ],
+        "source": "https://docs.mistral.ai/models/mistral-large-4",
+        "supports_assistant_prefill": true,
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "mistral/mistral-large-latest": {
         "cache_read_input_token_cost": 5e-08,
         "input_cost_per_token": 5e-07,
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index a98e209f461..22b75127d03 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -39226,6 +39226,48 @@
         "max_tokens": 8192,
         "mode": "embedding"
     },
+    "mistral/mistral-large-4": {
+        "cache_read_input_token_cost": 6.8e-08,
+        "input_cost_per_token": 6.8e-07,
+        "litellm_provider": "mistral",
+        "max_input_tokens": 524288,
+        "max_tokens": 524288,
+        "mode": "chat",
+        "output_cost_per_token": 2.09e-06,
+        "reasoning_effort_levels": [
+            "none",
+            "high"
+        ],
+        "source": "https://docs.mistral.ai/models/mistral-large-4",
+        "supports_assistant_prefill": true,
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "mistral/mistral-large-4-0": {
+        "cache_read_input_token_cost": 6.8e-08,
+        "input_cost_per_token": 6.8e-07,
+        "litellm_provider": "mistral",
+        "max_input_tokens": 524288,
+        "max_tokens": 524288,
+        "mode": "chat",
+        "output_cost_per_token": 2.09e-06,
+        "reasoning_effort_levels": [
+            "none",
+            "high"
+        ],
+        "source": "https://docs.mistral.ai/models/mistral-large-4",
+        "supports_assistant_prefill": true,
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
     "mistral/mistral-large-latest": {
         "cache_read_input_token_cost": 5e-08,
         "input_cost_per_token": 5e-07,
diff --git a/tests/unit/test_mistral_large_4_model_metadata.py b/tests/unit/test_mistral_large_4_model_metadata.py
new file mode 100644
index 00000000000..924265d2b41
--- /dev/null
+++ b/tests/unit/test_mistral_large_4_model_metadata.py
@@ -0,0 +1,191 @@
+"""Le Chonk (Mistral Large 4) metadata and offline API-contract regressions."""
+
+import json
+from pathlib import Path
+
+import pytest
+
+import litellm
+from litellm.llms.mistral.chat.transformation import MistralConfig
+
+REPO_ROOT = Path(__file__).parents[2]
+MODELS = ("mistral/mistral-large-4", "mistral/mistral-large-4-0")
+
+
+@pytest.fixture(autouse=True)
+def local_model_cost_map(monkeypatch):
+    """Never depend on the published cost map having this new model yet."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
+    litellm.get_model_info.cache_clear()
+    yield
+    litellm.get_model_info.cache_clear()
+
+
+@pytest.mark.parametrize("model", MODELS)
+def test_metadata_and_backup(model):
+    main = json.loads((REPO_ROOT / "model_prices_and_context_window.json").read_text())
+    backup = json.loads((REPO_ROOT / "litellm/model_prices_and_context_window_backup.json").read_text())
+    assert main[model] == backup[model] == main[MODELS[0]]
+    info = litellm.get_model_info(model)
+    assert info["litellm_provider"] == "mistral"
+    assert info["mode"] == "chat"
+    assert info["max_input_tokens"] == 524288
+    assert info["input_cost_per_token"] == 6.8e-07
+    assert info["output_cost_per_token"] == 2.09e-06
+    assert info["cache_read_input_token_cost"] == 6.8e-08
+    assert info["reasoning_effort_levels"] == ["none", "high"]
+    for capability in (
+        "supports_vision",
+        "supports_reasoning",
+        "supports_function_calling",
+        "supports_tool_choice",
+        "supports_response_schema",
+        "supports_assistant_prefill",
+        "supports_prompt_caching",
+    ):
+        assert info[capability] is True
+    assert litellm.get_llm_provider(model=model)[:2] == (model.split("/", 1)[1], "mistral")
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("effort", ["none", "high"])
+def test_reasoning_effort(model, effort):
+    config = MistralConfig()
+    assert "reasoning_effort" in config.get_supported_openai_params(model)
+    assert config.map_openai_params({"reasoning_effort": effort}, {}, model, False) == {"reasoning_effort": effort}
+
+
+@pytest.mark.parametrize("model", MODELS)
+def test_completion_cost(model):
+    uncached_response = litellm.ModelResponse(
+        model=model.split("/", 1)[1],
+        usage={"prompt_tokens": 1000, "completion_tokens": 100, "total_tokens": 1100},
+    )
+    assert litellm.completion_cost(completion_response=uncached_response, model=model) == pytest.approx(
+        1000 * 6.8e-07 + 100 * 2.09e-06
+    )
+    response = litellm.ModelResponse(
+        model=model.split("/", 1)[1],
+        usage={
+            "prompt_tokens": 1000,
+            "completion_tokens": 100,
+            "total_tokens": 1100,
+            "prompt_tokens_details": {"cached_tokens": 600},
+        },
+    )
+    assert litellm.completion_cost(completion_response=response, model=model) == pytest.approx(
+        400 * 6.8e-07 + 600 * 6.8e-08 + 100 * 2.09e-06
+    )
+
+
+def test_large_3_alias_is_not_retargeted():
+    info = litellm.get_model_info("mistral/mistral-large-latest")
+    assert info["input_cost_per_token"] == 5e-07
+    assert info["max_input_tokens"] == 262144
+    assert not info["supports_reasoning"]
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("sync_mode", [True, False])
+@pytest.mark.parametrize("effort", ["none", "high"])
+@pytest.mark.asyncio
+async def test_completion_contract(model, sync_mode, effort, respx_mock):
+    """Exercise the real adapter against explicitly mocked Mistral HTTP responses."""
+    api_model = model.split("/", 1)[1]
+    content = "Test answer"
+    if effort == "high":
+        content = [
+            {"type": "thinking", "thinking": [{"type": "text", "text": "Test reasoning"}]},
+            {"type": "text", "text": "Test answer"},
+        ]
+    route = respx_mock.post("https://api.mistral.ai/v1/chat/completions").respond(
+        json={
+            "id": "test-large-4",
+            "object": "chat.completion",
+            "created": 1,
+            "model": api_model,
+            "choices": [{"index": 0, "message": {"role": "assistant", "content": content}, "finish_reason": "stop"}],
+            "usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30},
+        }
+    )
+    kwargs = {
+        "model": model,
+        "messages": [{"role": "user", "content": "Hello"}],
+        "reasoning_effort": effort,
+        "max_tokens": 64,
+        "api_key": "test-key",
+        "num_retries": 0,
+    }
+    response = litellm.completion(**kwargs) if sync_mode else await litellm.acompletion(**kwargs)
+    assert response.choices[0].message.content == "Test answer"
+    if effort == "high":
+        assert response.choices[0].message.reasoning_content == "Test reasoning"
+    assert route.call_count == 1
+    payload = json.loads(route.calls[0].request.content)
+    assert payload["model"] == api_model
+    assert payload["reasoning_effort"] == effort
+    assert payload["max_tokens"] == 64
+    assert payload["messages"] == kwargs["messages"]
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("sync_mode", [True, False])
+@pytest.mark.asyncio
+async def test_streaming_completion_contract(model, sync_mode, respx_mock):
+    """Verify thinking chunks and text are normalized on the streaming path."""
+    api_model = model.split("/", 1)[1]
+    deltas = [
+        {
+            "role": "assistant",
+            "content": [{"type": "thinking", "thinking": [{"type": "text", "text": "Test reasoning"}]}],
+        },
+        {"content": "Test answer"},
+    ]
+    events = [
+        {
+            "id": "test-stream",
+            "object": "chat.completion.chunk",
+            "created": 1,
+            "model": api_model,
+            "choices": [{"index": 0, "delta": delta, "finish_reason": None}],
+        }
+        for delta in deltas
+    ]
+    events.append(
+        {
+            "id": "test-stream",
+            "object": "chat.completion.chunk",
+            "created": 1,
+            "model": api_model,
+            "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
+        }
+    )
+    route = respx_mock.post("https://api.mistral.ai/v1/chat/completions").respond(
+        text="".join(f"data: {json.dumps(event)}\n\n" for event in events) + "data: [DONE]\n\n",
+        headers={"Content-Type": "text/event-stream"},
+    )
+    kwargs = {
+        "model": model,
+        "messages": [{"role": "user", "content": "Hello"}],
+        "reasoning_effort": "high",
+        "stream": True,
+        "api_key": "test-key",
+        "num_retries": 0,
+    }
+    if sync_mode:
+        chunks = list(litellm.completion(**kwargs))
+    else:
+        stream = await litellm.acompletion(**kwargs)
+        chunks = [chunk async for chunk in stream]
+    assert "".join(chunk.choices[0].delta.content or "" for chunk in chunks) == "Test answer"
+    assert (
+        "".join(getattr(chunk.choices[0].delta, "reasoning_content", None) or "" for chunk in chunks)
+        == "Test reasoning"
+    )
+    assert chunks[-1].choices[0].finish_reason == "stop"
+    payload = json.loads(route.calls[0].request.content)
+    assert payload["model"] == api_model
+    assert payload["reasoning_effort"] == "high"
+    assert payload["stream"] is True