diff --git a/litellm/llms/openai/openai.py b/litellm/llms/openai/openai.py
index 0c1eaaaae26..73f40f5e0e4 100644
--- a/litellm/llms/openai/openai.py
+++ b/litellm/llms/openai/openai.py
@@ -11,13 +11,14 @@ if TYPE_CHECKING:
     from litellm.litellm_core_utils.tokenizer import Encoding as Tokenizer
 
 import openai
-from openai import AsyncOpenAI, OpenAI
+from openai import AsyncOpenAI, AsyncStream, OpenAI, Stream
 from openai._base_client import make_request_options
 from openai._constants import RAW_RESPONSE_HEADER
 from openai._legacy_response import LegacyAPIResponse
 from openai._types import RequestOptions
 from openai.types import CreateEmbeddingResponse
 from openai.types.beta.assistant_deleted import AssistantDeleted
+from openai.types.chat import ChatCompletion, ChatCompletionChunk
 from openai.types.file_deleted import FileDeleted
 from pydantic import BaseModel, TypeAdapter
 from typing_extensions import overload
@@ -354,7 +355,14 @@ _NO_EXTRA_HEADERS: Final[Mapping[str, str]] = types.MappingProxyType({})
 _SDK_OPTION_KEYS: Final = frozenset(("extra_headers", "extra_query", "extra_body"))
 
 
-def _embedding_request_without_sdk_defaults(
+def _raw_chat_response(
+    result: ChatCompletion | Stream[ChatCompletionChunk] | AsyncStream[ChatCompletionChunk],
+) -> LegacyAPIResponse[ChatCompletion]:
+    assert isinstance(result, LegacyAPIResponse)
+    return result
+
+
+def _request_without_sdk_transform(
     data: Mapping[str, object], timeout: float | httpx.Timeout
 ) -> tuple[Mapping[str, object], RequestOptions]:
     body: Final = {k: v for k, v in data.items() if k not in _SDK_OPTION_KEYS}
@@ -517,7 +525,17 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
         """
         start_time: Final = time.time()
         try:
-            raw_response = await openai_aclient.chat.completions.with_raw_response.create(**data, timeout=timeout)
+            body, options = _request_without_sdk_transform(data, timeout)
+            raw_response = _raw_chat_response(
+                await openai_aclient.post(
+                    "/chat/completions",
+                    body=body,
+                    cast_to=ChatCompletion,
+                    options=options,
+                    stream=bool(data.get("stream")),
+                    stream_cls=AsyncStream[ChatCompletionChunk],
+                )
+            )
             end_time = time.time()
 
             if hasattr(raw_response, "headers"):
@@ -558,7 +576,17 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
         """
         raw_response = None
         try:
-            raw_response = openai_client.chat.completions.with_raw_response.create(**data, timeout=timeout)
+            body, options = _request_without_sdk_transform(data, timeout)
+            raw_response = _raw_chat_response(
+                openai_client.post(
+                    "/chat/completions",
+                    body=body,
+                    cast_to=ChatCompletion,
+                    options=options,
+                    stream=bool(data.get("stream")),
+                    stream_cls=Stream[ChatCompletionChunk],
+                )
+            )
 
             if hasattr(raw_response, "headers"):
                 headers = dict(raw_response.headers)
@@ -1257,7 +1285,7 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
         logging_obj: LiteLLMLoggingObj,
     ) -> LegacyAPIResponse[CreateEmbeddingResponse]:
         if "encoding_format" not in data:
-            body, options = _embedding_request_without_sdk_defaults(data, timeout)
+            body, options = _request_without_sdk_transform(data, timeout)
             bypass_response: Final = await openai_aclient.post(
                 "/embeddings", body=body, options=options, cast_to=CreateEmbeddingResponse
             )
@@ -1274,7 +1302,7 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
         logging_obj: LiteLLMLoggingObj,
     ) -> LegacyAPIResponse[CreateEmbeddingResponse]:
         if "encoding_format" not in data:
-            body, options = _embedding_request_without_sdk_defaults(data, timeout)
+            body, options = _request_without_sdk_transform(data, timeout)
             bypass_response: Final = openai_client.post(
                 "/embeddings", body=body, options=options, cast_to=CreateEmbeddingResponse
             )
diff --git a/tests/unit/litellm_core_utils/test_chat_completion_agentic_loop.py b/tests/unit/litellm_core_utils/test_chat_completion_agentic_loop.py
index e891706df13..3cbc3591009 100644
--- a/tests/unit/litellm_core_utils/test_chat_completion_agentic_loop.py
+++ b/tests/unit/litellm_core_utils/test_chat_completion_agentic_loop.py
@@ -25,13 +25,13 @@ from typing import Any, Dict, Final, List, Optional, Tuple
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
-
+from openai._legacy_response import LegacyAPIResponse
 
 import litellm
-from litellm.integrations.custom_logger import CustomLogger
 from litellm.integrations.code_interpreter_interception.handler import (
     CodeInterpreterInterceptionLogger,
 )
+from litellm.integrations.custom_logger import CustomLogger
 from litellm.litellm_core_utils.chat_completion_agentic_loop import (
     maybe_run_chat_completion_agentic_loop,
 )
@@ -45,9 +45,9 @@ from litellm.types.integrations.custom_logger import (
     AgenticLoopRequestPatch,
 )
 from litellm.types.utils import (
+    ChatCompletionMessageToolCall,
     Choices,
     Function,
-    ChatCompletionMessageToolCall,
     Message,
     ModelResponse,
 )
@@ -142,7 +142,7 @@ def _raw_response_for(model_response: ModelResponse) -> MagicMock:
     (an object exposing `.headers` and `.parse()` -> something with model_dump)."""
     parsed = MagicMock()
     parsed.model_dump.return_value = model_response.model_dump()
-    raw = MagicMock()
+    raw = MagicMock(spec=LegacyAPIResponse)
     raw.headers = {}
     raw.parse.return_value = parsed
     return raw
@@ -171,7 +171,7 @@ async def test_internal_control_fields_never_leak_into_provider_body(restore_cal
         ]
     )
     mock_client = MagicMock()
-    mock_client.chat.completions.with_raw_response.create = create
+    mock_client.post = create
 
     response = await litellm.acompletion(
         model="openai/gpt-4o-mini",
diff --git a/tests/unit/litellm_core_utils/test_exception_mapping_utils.py b/tests/unit/litellm_core_utils/test_exception_mapping_utils.py
index 02ebae6dcf6..b24348cfaa8 100644
--- a/tests/unit/litellm_core_utils/test_exception_mapping_utils.py
+++ b/tests/unit/litellm_core_utils/test_exception_mapping_utils.py
@@ -2462,7 +2462,6 @@ def test_openai_gateway_timeout_error():
     Test that the OpenAI gateway timeout error is raised
     """
     openai_client = OpenAI()
-    mapped_target = openai_client.chat.completions.with_raw_response  # type: ignore
 
     def _return_exception(*args, **kwargs):
 
@@ -2498,8 +2497,8 @@ def test_openai_gateway_timeout_error():
 
     with pytest.raises(litellm.Timeout) as exc_info:
         with patch.object(
-            mapped_target,
-            "create",
+            openai_client,
+            "post",
             side_effect=_return_exception,
         ):
             litellm.completion(
diff --git a/tests/unit/llms/azure/chat/test_azure_chat_o_series_transformation.py b/tests/unit/llms/azure/chat/test_azure_chat_o_series_transformation.py
index 3630ef1e354..1cdc288ff87 100644
--- a/tests/unit/llms/azure/chat/test_azure_chat_o_series_transformation.py
+++ b/tests/unit/llms/azure/chat/test_azure_chat_o_series_transformation.py
@@ -1,9 +1,10 @@
 import json
 import traceback
-from typing import Callable, Optional
+from typing import Callable, Final, Optional
 from unittest.mock import MagicMock, patch
 
 import pytest
+from openai._legacy_response import LegacyAPIResponse
 
 import litellm
 from litellm import ModelResponse
@@ -130,7 +131,7 @@ def test_azure_o3_streaming():
         api_version="2024-02-15-preview",
     )
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_create:
+    with patch.object(client, "post") as mock_create:
         try:
             completion(
                 model="azure/o3-mini",
@@ -141,7 +142,7 @@ def test_azure_o3_streaming():
         except Exception as e:
             print(e)
         assert mock_create.call_count == 1
-        assert "stream" in mock_create.call_args.kwargs
+        assert "stream" in mock_create.call_args.kwargs["body"]
 
 
 def test_azure_o_series_routing():
@@ -157,7 +158,7 @@ def test_azure_o_series_routing():
         api_version="2024-02-15-preview",
     )
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_create:
+    with patch.object(client, "post") as mock_create:
         try:
             completion(
                 model="azure/o_series/my-random-deployment-name",
@@ -168,17 +169,19 @@ def test_azure_o_series_routing():
         except Exception as e:
             print(e)
         assert mock_create.call_count == 1
-        assert "stream" not in mock_create.call_args.kwargs
+        assert "stream" not in mock_create.call_args.kwargs["body"]
 
 
 @patch("litellm.main.azure_o1_chat_completions._get_openai_client")
 def test_openai_o_series_max_retries_0(mock_get_openai_client):
     import litellm
 
-    mock_get_openai_client.return_value.chat.completions.with_raw_response.create.return_value.headers = {}
-    mock_get_openai_client.return_value.chat.completions.with_raw_response.create.return_value.parse.return_value = (
-        ModelResponse(choices=[{"message": {"role": "assistant", "content": "Hello"}}])
-    )
+    raw_response: Final = MagicMock(spec=LegacyAPIResponse)
+    raw_response.headers = {}
+    raw_response.parse.return_value = ModelResponse(choices=[{"message": {"role": "assistant", "content": "Hello"}}])
+    client_stub: Final = MagicMock()
+    client_stub.post.return_value = raw_response
+    mock_get_openai_client.return_value = client_stub
     litellm.set_verbose = True
     response = litellm.completion(
         model="azure/o1-preview",
@@ -233,7 +236,7 @@ async def test_azure_o1_series_response_format_extra_params():
     response_format = {"type": "json_object"}
     tool_choice = "auto"
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             await litellm.acompletion(
@@ -251,7 +254,7 @@ async def test_azure_o1_series_response_format_extra_params():
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         print("request_body: ", json.dumps(request_body, indent=4))
         assert request_body["tools"] == tools
diff --git a/tests/unit/llms/azure/test_azure.py b/tests/unit/llms/azure/test_azure.py
index 7907344ae64..7d5afde68ef 100644
--- a/tests/unit/llms/azure/test_azure.py
+++ b/tests/unit/llms/azure/test_azure.py
@@ -313,7 +313,7 @@ def test_azure_openai_gpt_4o_naming(monkeypatch):
         number: str = Field(description="total number of days in a week")
         days: list[str] = Field(description="name of days in a week")
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_post:
+    with patch.object(client, "post") as mock_post:
         try:
             completion(
                 model="azure/gpt4o",
@@ -326,9 +326,9 @@ def test_azure_openai_gpt_4o_naming(monkeypatch):
 
         mock_post.assert_called_once()
 
-        print(mock_post.call_args.kwargs)
+        print(mock_post.call_args.kwargs["body"])
 
-        assert "tool_calls" not in mock_post.call_args.kwargs
+        assert "tool_calls" not in mock_post.call_args.kwargs["body"]
 
 
 @pytest.mark.parametrize(
@@ -382,7 +382,7 @@ def test_azure_gpt_4o_with_tool_call_and_response_format(api_version):
         }
     ]
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_post:
+    with patch.object(client, "post") as mock_post:
         mock_post.return_value.headers = {}
         mock_post.return_value.parse.return_value = litellm.ModelResponse(
             choices=[{"message": {"role": "assistant", "content": InvestigationOutput().model_dump_json()}}]
@@ -411,9 +411,9 @@ def test_azure_gpt_4o_with_tool_call_and_response_format(api_version):
         mock_post.assert_called_once()
 
         if api_version == "2024-10-21":
-            assert "response_format" in mock_post.call_args.kwargs
+            assert "response_format" in mock_post.call_args.kwargs["body"]
         else:
-            assert "response_format" not in mock_post.call_args.kwargs
+            assert "response_format" not in mock_post.call_args.kwargs["body"]
         assert response.choices[0].message.content == InvestigationOutput().model_dump_json()
 
 
diff --git a/tests/unit/llms/litellm_proxy/chat/test_litellm_proxy_chat_transformation.py b/tests/unit/llms/litellm_proxy/chat/test_litellm_proxy_chat_transformation.py
index 86fb6fa15d8..9b8788d3769 100644
--- a/tests/unit/llms/litellm_proxy/chat/test_litellm_proxy_chat_transformation.py
+++ b/tests/unit/llms/litellm_proxy/chat/test_litellm_proxy_chat_transformation.py
@@ -1,15 +1,16 @@
 import json
+import re
 from io import BytesIO
 from pathlib import Path
 from typing import Final
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import httpx
+import pytest
 from openai import AsyncOpenAI, OpenAI
+from openai._legacy_response import LegacyAPIResponse
 from openai.types import CreateEmbeddingResponse, Embedding
 from openai.types.create_embedding_response import Usage
-import pytest
-import re
 
 import litellm
 from litellm import completion
@@ -18,7 +19,6 @@ from litellm.llms.litellm_proxy.chat.transformation import LiteLLMProxyChatConfi
 from tests._vcr_conftest_common import rewound_new_episodes_cassette
 from tests.capturing_transport import CapturingTransport
 
-
 _GATEWAY_EMBEDDING_RESPONSE: Final = CreateEmbeddingResponse(
     object="list",
     data=(Embedding(object="embedding", index=0, embedding=(0.1, 0.2, 0.3)),),
@@ -98,7 +98,7 @@ async def test_litellm_gateway_from_sdk():
     openai_client = OpenAI(api_key="fake-key")
 
     with patch.object(
-        openai_client.chat.completions.with_raw_response, "create", new=MagicMock()
+        openai_client, "post", new=MagicMock()
     ) as mock_call:
         try:
             completion(
@@ -114,9 +114,9 @@ async def test_litellm_gateway_from_sdk():
 
         mock_call.assert_called_once()
 
-        print("Call KWARGS - {}".format(mock_call.call_args.kwargs))
+        print("Call KWARGS - {}".format(mock_call.call_args.kwargs["body"]))
 
-        assert "hello" in mock_call.call_args.kwargs["extra_body"]
+        assert "hello" in mock_call.call_args.kwargs["options"]["extra_json"]
 
 
 @pytest.mark.parametrize("is_async", (False, True))
@@ -264,7 +264,7 @@ async def test_litellm_gateway_from_sdk_rerank(is_async):
         patch_target = client.post
 
     with patch.object(client, "post", new=mock_method):
-        mock_response = MagicMock()
+        mock_response = MagicMock(spec=LegacyAPIResponse)
 
         # Create a mock response similar to OpenAI's rerank response
         mock_response.text = json.dumps(
@@ -408,7 +408,7 @@ async def test_litellm_gateway_from_sdk_structured_output():
     openai_client = OpenAI(api_key="fake-key")
 
     with patch.object(
-        openai_client.chat.completions, "create", new=MagicMock()
+        openai_client, "post", new=MagicMock()
     ) as mock_call:
         try:
             litellm.completion(
@@ -427,8 +427,8 @@ async def test_litellm_gateway_from_sdk_structured_output():
 
         mock_call.assert_called_once()
 
-        print("Call KWARGS - {}".format(mock_call.call_args.kwargs))
-        json_schema = mock_call.call_args.kwargs["response_format"]
+        print("Call KWARGS - {}".format(mock_call.call_args.kwargs["body"]))
+        json_schema = mock_call.call_args.kwargs["body"]["response_format"]
         assert "json_schema" in json_schema
 
 
@@ -486,7 +486,7 @@ def test_litellm_gateway_from_sdk_with_response_cost_in_additional_headers():
     openai_client = OpenAI(api_key="fake-key")
 
     # Create mock response object
-    mock_response = MagicMock()
+    mock_response = MagicMock(spec=LegacyAPIResponse)
     mock_response.headers = {"x-litellm-response-cost": "120"}
     mock_response.parse.return_value = litellm.ModelResponse(
         **{
@@ -528,8 +528,7 @@ def test_litellm_gateway_from_sdk_with_response_cost_in_additional_headers():
     )
 
     with patch.object(
-        openai_client.chat.completions.with_raw_response,
-        "create",
+        openai_client, "post",
         return_value=mock_response,
     ) as mock_call:
         response = litellm.completion(
@@ -564,7 +563,7 @@ async def test_litellm_gateway_image_generation_direct(is_async):
         "created": 1,
         "data": [{"url": "https://example.com/image.png"}],
     }
-    mock_raw_response = MagicMock()
+    mock_raw_response = MagicMock(spec=LegacyAPIResponse)
     mock_raw_response.parse.return_value = mock_openai_response
     mock_raw_response.headers = {}
 
diff --git a/tests/unit/llms/nvidia_nim/test_nvidia_nim.py b/tests/unit/llms/nvidia_nim/test_nvidia_nim.py
index e5298c7ba39..3633ac97265 100644
--- a/tests/unit/llms/nvidia_nim/test_nvidia_nim.py
+++ b/tests/unit/llms/nvidia_nim/test_nvidia_nim.py
@@ -94,7 +94,7 @@ def test_chat_completion_nvidia_nim_with_tools():
     ]
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             completion(
@@ -116,7 +116,7 @@ def test_chat_completion_nvidia_nim_with_tools():
 
         # Add assertions to check the request
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         print("request_body: ", request_body)
 
@@ -208,7 +208,7 @@ def test_completion_nvidia_nim():
         api_key="fake-api-key",
     )
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_client:
+    with patch.object(client, "post") as mock_client:
         try:
             completion(
                 model=model_name,
@@ -226,7 +226,7 @@ def test_completion_nvidia_nim():
             print(e)
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         assert request_body["messages"] == [
             {
diff --git a/tests/unit/llms/openai/test_o_series_transformation.py b/tests/unit/llms/openai/test_o_series_transformation.py
index 6ee882b7d32..121fab66c15 100644
--- a/tests/unit/llms/openai/test_o_series_transformation.py
+++ b/tests/unit/llms/openai/test_o_series_transformation.py
@@ -70,7 +70,7 @@ async def test_o1_handle_system_role(model):
     client = AsyncOpenAI(api_key="fake-api-key")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             await litellm.acompletion(
@@ -83,7 +83,7 @@ async def test_o1_handle_system_role(model):
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         print("request_body: ", request_body)
 
@@ -141,7 +141,7 @@ async def test_o1_max_completion_tokens(model: str):
     client = AsyncOpenAI(api_key="fake-api-key")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             await litellm.acompletion(
@@ -154,7 +154,7 @@ async def test_o1_max_completion_tokens(model: str):
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         print("request_body: ", request_body)
 
diff --git a/tests/unit/llms/openai/test_openai.py b/tests/unit/llms/openai/test_openai.py
index d7ca9319f3a..11d7c7d6d3c 100644
--- a/tests/unit/llms/openai/test_openai.py
+++ b/tests/unit/llms/openai/test_openai.py
@@ -5,12 +5,13 @@ import os
 from collections.abc import Mapping
 from types import ModuleType
 from typing import Final, Literal, Protocol
-from unittest.mock import Mock, patch
+from unittest.mock import MagicMock, Mock, patch
 
 import httpx
 import pytest
 import respx
 from openai import AsyncOpenAI, AzureOpenAI, OpenAI
+from openai._legacy_response import LegacyAPIResponse
 from openai._types import Response as SDKResponse
 from pydantic import BaseModel, ConfigDict, JsonValue
 
@@ -1669,7 +1670,7 @@ async def test_openai_prediction_param_mock():
     client = AsyncOpenAI(api_key="fake-api-key")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             await litellm.acompletion(
@@ -1688,7 +1689,7 @@ async def test_openai_prediction_param_mock():
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         # Verify the request contains the prediction parameter
         assert "prediction" in request_body
@@ -1700,10 +1701,12 @@ async def test_openai_prediction_param_mock():
 def test_openai_max_retries_0(mock_get_openai_client):
     import litellm
 
-    mock_get_openai_client.return_value.chat.completions.with_raw_response.create.return_value.headers = {}
-    mock_get_openai_client.return_value.chat.completions.with_raw_response.create.return_value.parse.return_value = (
-        ModelResponse(choices=[{"message": {"role": "assistant", "content": "Hello"}}])
-    )
+    raw_response: Final = MagicMock(spec=LegacyAPIResponse)
+    raw_response.headers = {}
+    raw_response.parse.return_value = ModelResponse(choices=[{"message": {"role": "assistant", "content": "Hello"}}])
+    client_stub: Final = MagicMock()
+    client_stub.post.return_value = raw_response
+    mock_get_openai_client.return_value = client_stub
     litellm.set_verbose = True
     response = litellm.completion(
         model="gpt-4o-mini",
@@ -1812,7 +1815,7 @@ async def test_openai_safety_identifier_parameter():
     client = AsyncOpenAI(api_key="fake-api-key")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             await litellm.acompletion(
@@ -1825,7 +1828,7 @@ async def test_openai_safety_identifier_parameter():
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         # Verify the request contains the safety_identifier parameter
         assert "safety_identifier" in request_body
@@ -1841,7 +1844,7 @@ def test_openai_safety_identifier_parameter_sync():
     client = OpenAI(api_key="fake-api-key")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             litellm.completion(
@@ -1854,7 +1857,7 @@ def test_openai_safety_identifier_parameter_sync():
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         # Verify the request contains the safety_identifier parameter
         assert "safety_identifier" in request_body
@@ -1871,7 +1874,7 @@ async def test_openai_service_tier_parameter():
     client = AsyncOpenAI(api_key="fake-api-key")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             await litellm.acompletion(
@@ -1884,7 +1887,7 @@ async def test_openai_service_tier_parameter():
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         # Verify the request contains the service_tier parameter
         assert "service_tier" in request_body, "service_tier should be in request body"
@@ -1902,7 +1905,7 @@ def test_openai_service_tier_parameter_sync():
     client = OpenAI(api_key="fake-api-key")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create"
+        client, "post"
     ) as mock_client:
         try:
             litellm.completion(
@@ -1915,7 +1918,7 @@ def test_openai_service_tier_parameter_sync():
             print(f"Error: {e}")
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
 
         # Verify the request contains the service_tier parameter
         assert "service_tier" in request_body, "service_tier should be in request body"
@@ -1947,3 +1950,63 @@ def test_responses_gpt54_with_xhigh_reasoning():
         assert request_body["model"] == "openai/gpt-5.4"
 
         assert request_body["reasoning"] == {"effort": "xhigh"}
+
+
+_CHAT_RESPONSE_JSON: Final = {
+    "id": "chatcmpl-wire",
+    "object": "chat.completion",
+    "created": 1,
+    "model": "gpt-5.4",
+    "choices": [{"index": 0, "message": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"}],
+    "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+}
+_WIRE_REQUEST: Final = {
+    "model": "gpt-5.4",
+    "messages": [
+        {"role": "system", "content": "sys"},
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "what is in the image"},
+                {"type": "image_url", "image_url": {"url": "https://example.com/a.png", "detail": "low"}},
+            ],
+        },
+    ],
+    "tools": [{"type": "function", "function": {"name": "f", "parameters": {"type": "object", "properties": {}}}}],
+    "tool_choice": "auto",
+    "response_format": {"type": "json_schema", "json_schema": {"name": "r", "schema": {"type": "object"}}},
+    "max_completion_tokens": 7,
+    "reasoning_effort": "none",
+    "n": 2,
+    "seed": 3,
+}
+
+
+@pytest.mark.parametrize("is_async", (False, True))
+@respx.mock
+async def test_chat_completion_sends_the_caller_params_extra_body_and_extra_headers_unchanged(
+    is_async: bool, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
+    route: Final = respx.post("https://api.openai.com/v1/chat/completions").mock(
+        return_value=httpx.Response(200, json=_CHAT_RESPONSE_JSON)
+    )
+    kwargs: Final = {
+        **_WIRE_REQUEST,
+        "model": "openai/gpt-5.4",
+        "api_base": "https://api.openai.com/v1",
+        "api_key": "sk-test",
+        "num_retries": 0,
+        "extra_body": {"vendor_flag": True},
+        "extra_headers": {"x-caller": "unit"},
+    }
+
+    if is_async:
+        await litellm.acompletion(**kwargs)
+    else:
+        litellm.completion(**kwargs)
+
+    sent: Final = route.calls.last.request
+    assert json.loads(sent.content) == {**_WIRE_REQUEST, "vendor_flag": True}
+    assert sent.headers["x-caller"] == "unit"
+    assert sent.headers["authorization"] == "Bearer sk-test"
diff --git a/tests/unit/llms/openai/test_openai_empty_response.py b/tests/unit/llms/openai/test_openai_empty_response.py
index 26b28f967db..1505d9ef049 100644
--- a/tests/unit/llms/openai/test_openai_empty_response.py
+++ b/tests/unit/llms/openai/test_openai_empty_response.py
@@ -2,13 +2,13 @@
 Test for issue #17209: Clearer error when LLM endpoint returns empty response
 """
 
-from unittest.mock import MagicMock, patch
+from unittest.mock import MagicMock
 
 import pytest
+from openai._legacy_response import LegacyAPIResponse
 
-
-from litellm.llms.openai.openai import OpenAIChatCompletion
 from litellm.llms.openai.common_utils import OpenAIError
+from litellm.llms.openai.openai import OpenAIChatCompletion
 
 
 class TestEmptyResponseHandling:
@@ -22,12 +22,12 @@ class TestEmptyResponseHandling:
         openai_chat = OpenAIChatCompletion()
 
         # Mock the raw response to return an empty string from parse()
-        mock_raw_response = MagicMock()
+        mock_raw_response = MagicMock(spec=LegacyAPIResponse)
         mock_raw_response.headers = {}
         mock_raw_response.parse.return_value = ""  # Empty string response
 
         mock_client = MagicMock()
-        mock_client.chat.completions.with_raw_response.create.return_value = (
+        mock_client.post.return_value = (
             mock_raw_response
         )
 
@@ -48,12 +48,12 @@ class TestEmptyResponseHandling:
         """Test that None response also produces a clear error"""
         openai_chat = OpenAIChatCompletion()
 
-        mock_raw_response = MagicMock()
+        mock_raw_response = MagicMock(spec=LegacyAPIResponse)
         mock_raw_response.headers = {}
         mock_raw_response.parse.return_value = None
 
         mock_client = MagicMock()
-        mock_client.chat.completions.with_raw_response.create.return_value = (
+        mock_client.post.return_value = (
             mock_raw_response
         )
 
@@ -75,12 +75,12 @@ class TestEmptyResponseHandling:
         mock_response = MagicMock()
         mock_response.model_dump.return_value = {"choices": []}
 
-        mock_raw_response = MagicMock()
+        mock_raw_response = MagicMock(spec=LegacyAPIResponse)
         mock_raw_response.headers = {"x-request-id": "123"}
         mock_raw_response.parse.return_value = mock_response
 
         mock_client = MagicMock()
-        mock_client.chat.completions.with_raw_response.create.return_value = (
+        mock_client.post.return_value = (
             mock_raw_response
         )
 
@@ -104,12 +104,12 @@ class TestEmptyResponseHandling:
         # Create a mock response WITHOUT model_dump (like an AsyncStream/Iterator)
         mock_stream = MagicMock(spec=[])  # spec=[] means no attributes
 
-        mock_raw_response = MagicMock()
+        mock_raw_response = MagicMock(spec=LegacyAPIResponse)
         mock_raw_response.headers = {"x-request-id": "123"}
         mock_raw_response.parse.return_value = mock_stream
 
         mock_client = MagicMock()
-        mock_client.chat.completions.with_raw_response.create.return_value = (
+        mock_client.post.return_value = (
             mock_raw_response
         )
 
diff --git a/tests/unit/llms/openai/test_use_chat_completions_api_no_leak.py b/tests/unit/llms/openai/test_use_chat_completions_api_no_leak.py
index 7013afc7a5f..58f1ff60ba5 100644
--- a/tests/unit/llms/openai/test_use_chat_completions_api_no_leak.py
+++ b/tests/unit/llms/openai/test_use_chat_completions_api_no_leak.py
@@ -9,6 +9,7 @@ body. OpenAI/Anthropic reject unknown body params with HTTP 400.
 
 from unittest.mock import MagicMock
 
+from openai._legacy_response import LegacyAPIResponse
 
 import litellm
 from litellm.types.utils import all_litellm_params
@@ -47,12 +48,12 @@ def test_completion_does_not_leak_flag_into_provider_request_body():
         },
     }
 
-    mock_raw_response = MagicMock()
+    mock_raw_response = MagicMock(spec=LegacyAPIResponse)
     mock_raw_response.headers = {}
     mock_raw_response.parse.return_value = mock_response
 
     mock_client = MagicMock()
-    mock_client.chat.completions.with_raw_response.create.return_value = (
+    mock_client.post.return_value = (
         mock_raw_response
     )
 
@@ -65,7 +66,7 @@ def test_completion_does_not_leak_flag_into_provider_request_body():
     )
 
     create_kwargs = (
-        mock_client.chat.completions.with_raw_response.create.call_args.kwargs
+        mock_client.post.call_args.kwargs
     )
     assert "use_chat_completions_api" not in create_kwargs
     assert "use_chat_completions_api" not in (create_kwargs.get("extra_body") or {})
diff --git a/tests/unit/llms/perplexity/chat/test_transformation.py b/tests/unit/llms/perplexity/chat/test_transformation.py
index 6a70fd1232d..0cb6335f5a8 100644
--- a/tests/unit/llms/perplexity/chat/test_transformation.py
+++ b/tests/unit/llms/perplexity/chat/test_transformation.py
@@ -4,6 +4,7 @@ import os
 from unittest.mock import MagicMock, patch
 
 import pytest
+from openai._legacy_response import LegacyAPIResponse
 
 import litellm
 from litellm import completion
@@ -92,7 +93,7 @@ class TestPerplexityReasoning:
         pydantic_obj = ChatCompletion(**response_object)
 
         def _return_pydantic_obj(*args, **kwargs):
-            new_response = MagicMock()
+            new_response = MagicMock(spec=LegacyAPIResponse)
             new_response.headers = {"content-type": "application/json"}
             new_response.parse.return_value = pydantic_obj
             return new_response
@@ -100,8 +101,7 @@ class TestPerplexityReasoning:
         openai_client = OpenAI(api_key="fake-api-key")
 
         with patch.object(
-            openai_client.chat.completions.with_raw_response,
-            "create",
+            openai_client, "post",
             side_effect=_return_pydantic_obj,
         ) as mock_client:
             response = completion(
@@ -121,7 +121,7 @@ class TestPerplexityReasoning:
 
             # Get the request data from the mock call
             call_args = mock_client.call_args
-            request_data = call_args.kwargs
+            request_data = call_args.kwargs["body"]
 
             # Verify reasoning_effort was included in the request
             assert "reasoning_effort" in request_data
diff --git a/tests/unit/llms/volcengine/test_volcengine.py b/tests/unit/llms/volcengine/test_volcengine.py
index d472d52d2db..dff9a0c62b2 100644
--- a/tests/unit/llms/volcengine/test_volcengine.py
+++ b/tests/unit/llms/volcengine/test_volcengine.py
@@ -2,6 +2,7 @@ import os
 import sys
 from unittest.mock import MagicMock, patch
 
+from openai._legacy_response import LegacyAPIResponse
 from pydantic import BaseModel
 
 from litellm.llms.volcengine.chat.transformation import (
@@ -117,7 +118,7 @@ class TestVolcEngineConfig:
 
         client = OpenAI(api_key="test_api_key")
 
-        mock_raw_response = MagicMock()
+        mock_raw_response = MagicMock(spec=LegacyAPIResponse)
         mock_raw_response.headers = {
             "x-request-id": "123",
             "openai-organization": "org-123",
@@ -126,9 +127,7 @@ class TestVolcEngineConfig:
         }
         mock_raw_response.parse.return_value = ModelResponse()
 
-        with patch.object(
-            client.chat.completions.with_raw_response, "create", mock_raw_response
-        ) as mock_create:
+        with patch.object(client, "post", MagicMock(return_value=mock_raw_response)) as mock_create:
             completion(
                 model="volcengine/doubao-seed-1.6",
                 messages=[
@@ -144,11 +143,6 @@ class TestVolcEngineConfig:
             )
 
             mock_create.assert_called_once()
-            print(mock_create.call_args.kwargs)
+            print(mock_create.call_args.kwargs["body"])
             # Fixed: thinking disabled should appear in extra_body with original structure
-            assert (
-                "extra_body" in mock_create.call_args.kwargs
-                and "thinking" in mock_create.call_args.kwargs.get("extra_body", {})
-                and mock_create.call_args.kwargs.get("extra_body", {})["thinking"]
-                == {"type": "disabled"}
-            )
+            assert mock_create.call_args.kwargs["options"]["extra_json"]["thinking"] == {"type": "disabled"}
diff --git a/tests/unit/test_main.py b/tests/unit/test_main.py
index 14cea8f0c2c..bb0e8db7f1c 100644
--- a/tests/unit/test_main.py
+++ b/tests/unit/test_main.py
@@ -21,15 +21,22 @@ import httpx
 import pytest
 import respx
 from openai import APITimeoutError, AsyncOpenAI
+from openai._legacy_response import LegacyAPIResponse
 from openai.types.chat.chat_completion import ChatCompletion
 
 import litellm
-from litellm import acompletion, completion
-from litellm import acompletion_with_retries, aresponses_with_retries, completion_with_retries, responses_with_retries
+from litellm import (
+    acompletion,
+    acompletion_with_retries,
+    aresponses_with_retries,
+    completion,
+    completion_with_retries,
+    responses_with_retries,
+)
 from litellm import main as litellm_main
-from litellm.constants import CONTROL_OPTIONS_KEY
 from litellm.caching.base_cache import BaseCache
 from litellm.caching.caching import Cache
+from litellm.constants import CONTROL_OPTIONS_KEY
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.integrations.custom_prompt_management import CustomPromptManagement
 from litellm.litellm_core_utils.core_helpers import get_litellm_metadata_from_kwargs
@@ -130,7 +137,7 @@ def test_completion_missing_role(openai_api_response):
 
     client = OpenAI(api_key="test_api_key")
 
-    mock_raw_response = MagicMock()
+    mock_raw_response = MagicMock(spec=LegacyAPIResponse)
     mock_raw_response.headers = {
         "x-request-id": "123",
         "openai-organization": "org-123",
@@ -142,7 +149,7 @@ def test_completion_missing_role(openai_api_response):
     print(f"openai_api_response: {openai_api_response}")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create", MagicMock(return_value=mock_raw_response)
+        client, "post", MagicMock(return_value=mock_raw_response)
     ) as mock_create:
         litellm.completion(
             model="gpt-4o-mini",
@@ -218,7 +225,7 @@ async def test_url_with_format_param_openai(model, sync_mode):
             }
         ],
     }
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_client:
+    with patch.object(client, "post") as mock_client:
         try:
             if sync_mode:
                 response = completion(**args, client=client)
@@ -232,7 +239,7 @@ async def test_url_with_format_param_openai(model, sync_mode):
 
         print(mock_client.call_args.kwargs)
 
-        json_str = json.dumps(mock_client.call_args.kwargs)
+        json_str = json.dumps(mock_client.call_args.kwargs["body"])
 
         assert "format" not in json_str
 
@@ -3005,9 +3012,10 @@ def test_stream_chunk_builder_thinking_blocks():
     assert response.choices[0].message.thinking_blocks is not None
 
 
-from litellm.llms.openai.openai import OpenAIChatCompletion
 import traceback
 
+from litellm.llms.openai.openai import OpenAIChatCompletion
+
 user_message = "Write a short poem about the sky"
 messages = [{"content": user_message, "role": "user"}]
 
@@ -3777,7 +3785,7 @@ def test_completion_forwards_store_and_prompt_cache_key_to_openai():
 
     client = OpenAI(api_key="fake-api-key")
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_client:
+    with patch.object(client, "post") as mock_client:
         try:
             litellm.completion(
                 model="openai/gpt-4o",
@@ -3790,7 +3798,7 @@ def test_completion_forwards_store_and_prompt_cache_key_to_openai():
             print(e)
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
         assert request_body["store"] is False
         assert request_body["prompt_cache_key"] == "test-cache-key"
 
@@ -3805,7 +3813,7 @@ async def test_acompletion_forwards_store_and_prompt_cache_key_to_openai():
 
     client = AsyncOpenAI(api_key="fake-api-key")
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_client:
+    with patch.object(client, "post") as mock_client:
         try:
             await litellm.acompletion(
                 model="openai/gpt-4o",
@@ -3818,7 +3826,7 @@ async def test_acompletion_forwards_store_and_prompt_cache_key_to_openai():
             print(e)
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
         assert request_body["store"] is False
         assert request_body["prompt_cache_key"] == "test-cache-key"
 
@@ -3832,7 +3840,7 @@ def test_completion_omits_store_and_prompt_cache_key_when_not_passed():
 
     client = OpenAI(api_key="fake-api-key")
 
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_client:
+    with patch.object(client, "post") as mock_client:
         try:
             litellm.completion(
                 model="openai/gpt-4o",
@@ -3843,7 +3851,7 @@ def test_completion_omits_store_and_prompt_cache_key_when_not_passed():
             print(e)
 
         mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
+        request_body = mock_client.call_args.kwargs["body"]
         assert "store" not in request_body
         assert "prompt_cache_key" not in request_body
 
@@ -4038,8 +4046,7 @@ def test_openai_model_without_a_provider_still_routes_to_openai():
     from openai import OpenAI
 
     client = OpenAI(api_key="fake-key")
-    raw_response = client.chat.completions.with_raw_response
-    with patch.object(raw_response, "create") as mock_create, contextlib.suppress(Exception):
+    with patch.object(client, "post") as mock_create, contextlib.suppress(Exception):
         litellm.completion(
             model="gpt-4o",
             messages=[{"role": "user", "content": "hello"}],
@@ -4050,7 +4057,7 @@ def test_openai_model_without_a_provider_still_routes_to_openai():
 
 
 def _openai_chat_create_kwargs(client, **completion_kwargs):
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_client:
+    with patch.object(client, "post") as mock_client:
         with contextlib.suppress(Exception):
             litellm.completion(
                 messages=[{"role": "system", "content": "sys"}, {"role": "user", "content": "hi"}],
@@ -4075,7 +4082,7 @@ def test_completion_custom_api_base_sends_no_prompt_cache_breakpoint_for_gpt_5_6
     from openai import OpenAI
 
     client = OpenAI(api_key="fake-api-key", base_url="http://127.0.0.1:9/v1")
-    request_body = _openai_chat_create_kwargs(client, model="gpt-5.6", api_base="http://127.0.0.1:9/v1")
+    request_body = _openai_chat_create_kwargs(client, model="gpt-5.6", api_base="http://127.0.0.1:9/v1")["body"]
 
     assert request_body["messages"][0] == {"role": "system", "content": "sys", "cache_control": {"type": "ephemeral"}}
     assert "prompt_cache_breakpoint" not in json.dumps(request_body["messages"])
@@ -4087,7 +4094,7 @@ def test_completion_custom_base_url_sends_no_prompt_cache_breakpoint_for_gpt_5_6
     from openai import OpenAI
 
     client = OpenAI(api_key="fake-api-key", base_url="http://127.0.0.1:9/v1")
-    request_body = _openai_chat_create_kwargs(client, model="gpt-5.6", base_url="http://127.0.0.1:9/v1")
+    request_body = _openai_chat_create_kwargs(client, model="gpt-5.6", base_url="http://127.0.0.1:9/v1")["body"]
 
     assert request_body["messages"][0] == {"role": "system", "content": "sys", "cache_control": {"type": "ephemeral"}}
     assert "prompt_cache_breakpoint" not in json.dumps(request_body["messages"])
@@ -4100,7 +4107,7 @@ async def test_acompletion_custom_base_url_sends_no_prompt_cache_breakpoint_for_
     from openai import AsyncOpenAI
 
     client = AsyncOpenAI(api_key="fake-api-key", base_url="http://127.0.0.1:9/v1")
-    with patch.object(client.chat.completions.with_raw_response, "create") as mock_create:
+    with patch.object(client, "post") as mock_create:
         with contextlib.suppress(Exception):
             await litellm.acompletion(
                 model="gpt-5.6",
@@ -4111,7 +4118,7 @@ async def test_acompletion_custom_base_url_sends_no_prompt_cache_breakpoint_for_
             )
 
         mock_create.assert_called_once()
-        request_body = mock_create.call_args.kwargs
+        request_body = mock_create.call_args.kwargs["body"]
 
     assert request_body["messages"][0] == {"role": "system", "content": "sys", "cache_control": {"type": "ephemeral"}}
     assert "prompt_cache_breakpoint" not in json.dumps(request_body["messages"])
@@ -4123,12 +4130,12 @@ def test_completion_default_api_base_sends_prompt_cache_breakpoint_for_gpt_5_6()
     from openai import OpenAI
 
     client = OpenAI(api_key="fake-api-key")
-    request_body = _openai_chat_create_kwargs(client, model="gpt-5.6")
+    request = _openai_chat_create_kwargs(client, model="gpt-5.6")
 
-    assert request_body["messages"][0]["content"] == [
+    assert request["body"]["messages"][0]["content"] == [
         {"type": "text", "text": "sys", "prompt_cache_breakpoint": {"mode": "explicit"}}
     ]
-    assert request_body["extra_body"]["prompt_cache_options"] == {"mode": "implicit"}
+    assert request["options"]["extra_json"]["prompt_cache_options"] == {"mode": "implicit"}
 
 
 _SUBSCRIPTION_OAUTH_CREDENTIAL = "Bearer sk-ant-oat01-fake-subscription-token-for-testing-0123456789"
@@ -5141,6 +5148,7 @@ def test_drop_params_false_still_rejects_an_invalid_stream_chunk_size() -> None:
 
 def test_acompletion_params():
     import inspect
+
     from litellm.types.completion import CompletionRequest
 
     acompletion_params_odict = inspect.signature(acompletion).parameters
@@ -5171,7 +5179,7 @@ def test_acompletion_params():
 
 
 def _openai_mock_response(*args: object, **kwargs: object) -> MagicMock:
-    new_response: Final = MagicMock()
+    new_response: Final = MagicMock(spec=LegacyAPIResponse)
     new_response.headers = {"hello": "world"}
     response_object: Final = {
         "id": "chatcmpl-123",
@@ -5206,7 +5214,7 @@ def test_null_role_response():
 
     openai_client = openai.OpenAI()
     with patch.object(
-        openai_client.chat.completions, "create", side_effect=_openai_mock_response
+        openai_client, "post", side_effect=_openai_mock_response
     ) as mock_response:
         response = litellm.completion(
             model="gpt-3.5-turbo",
@@ -5296,7 +5304,7 @@ def test_completion_perplexity_api():
         pydantic_obj = ChatCompletion(**response_object)
 
         def _return_pydantic_obj(*args, **kwargs):
-            new_response = MagicMock()
+            new_response = MagicMock(spec=LegacyAPIResponse)
             new_response.headers = {"hello": "world"}
 
             new_response.parse.return_value = pydantic_obj
@@ -5305,8 +5313,7 @@ def test_completion_perplexity_api():
         openai_client = OpenAI()
 
         with patch.object(
-            openai_client.chat.completions.with_raw_response,
-            "create",
+            openai_client, "post",
             side_effect=_return_pydantic_obj,
         ) as mock_client:
             # litellm.set_verbose= True
@@ -5350,7 +5357,7 @@ async def test_openai_compatible_custom_api_base(provider):
     openai_client = OpenAI(api_key="fake-key")
 
     with patch.object(
-        openai_client.chat.completions, "create", new=MagicMock()
+        openai_client, "post", new=MagicMock()
     ) as mock_call:
         try:
             completion(
@@ -5368,7 +5375,7 @@ async def test_openai_compatible_custom_api_base(provider):
 
         print("Call KWARGS - {}".format(mock_call.call_args.kwargs))
 
-        assert "hello" in mock_call.call_args.kwargs["extra_body"]
+        assert "hello" in mock_call.call_args.kwargs["options"]["extra_json"]
 
 
 @pytest.mark.parametrize(
@@ -5401,7 +5408,7 @@ async def test_openai_compatible_custom_api_video(provider):
     openai_client = OpenAI(api_key="fake-key")
 
     with patch.object(
-        openai_client.chat.completions, "create", new=MagicMock()
+        openai_client, "post", new=MagicMock()
     ) as mock_call:
         try:
             completion(
@@ -7264,7 +7271,7 @@ def _openai_hallucinated_tool_call_mock_response(
     *args: object,
     **kwargs: object,
 ) -> MagicMock:
-    new_response: Final = MagicMock()
+    new_response: Final = MagicMock(spec=LegacyAPIResponse)
     new_response.headers = {"hello": "world"}
     response_object: Final = {
         "id": "chatcmpl-123",
@@ -7322,8 +7329,8 @@ def test_openai_hallucinated_tool_call():
 
     openai_client = openai.OpenAI()
     with patch.object(
-        openai_client.chat.completions,
-        "create",
+        openai_client,
+        "post",
         side_effect=_openai_hallucinated_tool_call_mock_response,
     ) as mock_response:
         response = litellm.completion(
@@ -7445,7 +7452,7 @@ def test_completion_novita_ai():
     openai_client = OpenAI(api_key="fake-key")
 
     with patch.object(
-        openai_client.chat.completions.with_raw_response, "create"
+        openai_client, "post", return_value=MagicMock(spec=LegacyAPIResponse)
     ) as mock_call:
         mock_call.return_value.headers = {}
         mock_call.return_value.parse.return_value = litellm.ModelResponse(
@@ -7464,11 +7471,11 @@ def test_completion_novita_ai():
 
             # Verify model is passed correctly
             assert (
-                mock_call.call_args.kwargs["model"]
+                mock_call.call_args.kwargs["body"]["model"]
                 == "meta-llama/llama-3.3-70b-instruct"
             )
             # Verify messages are passed correctly
-            assert mock_call.call_args.kwargs["messages"] == messages
+            assert mock_call.call_args.kwargs["body"]["messages"] == messages
 
         except Exception as e:
             pytest.fail(f"Error occurred: {e}")
@@ -7491,8 +7498,8 @@ def test_completion_novita_ai_dynamic_params(api_key):
         openai_client = OpenAI(api_key="fake-key")
 
         with patch.object(
-            openai_client.chat.completions,
-            "create",
+            openai_client,
+            "post",
             side_effect=Exception("Invalid API key"),
         ) as mock_call:
             with pytest.raises(Exception, match="Invalid API key") as exc_info:
@@ -7524,7 +7531,7 @@ def test_completion_openai_metadata(monkeypatch, enable_preview_features):
 
     monkeypatch.setattr(litellm, "enable_preview_features", enable_preview_features)
     with patch.object(
-        client.chat.completions.with_raw_response, "create", return_value=MagicMock()
+        client, "post", return_value=MagicMock()
     ) as mock_completion:
         try:
             resp = litellm.completion(
@@ -7538,11 +7545,11 @@ def test_completion_openai_metadata(monkeypatch, enable_preview_features):
 
         mock_completion.assert_called_once()
         if enable_preview_features:
-            assert mock_completion.call_args.kwargs["metadata"] == {
+            assert mock_completion.call_args.kwargs["body"]["metadata"] == {
                 "my-test-key": "my-test-value"
             }
         else:
-            assert "metadata" not in mock_completion.call_args.kwargs
+            assert "metadata" not in mock_completion.call_args.kwargs["body"]
 
 
 AZURE_TTS_BASE: Final = "https://tts.example.azure.com"