diff --git a/tests/local_testing/test_completion.py b/tests/local_testing/test_completion.py
index d5da0719e0..080c80e97f 100644
--- a/tests/local_testing/test_completion.py
+++ b/tests/local_testing/test_completion.py
@@ -3292,6 +3292,13 @@ def test_petals():
 ## test deep infra
 @pytest.mark.parametrize("drop_params", [True, False])
 def test_completion_deep_infra(drop_params):
+    """Test that DeepInfra requests are shaped correctly without making real API calls."""
+    from unittest.mock import MagicMock, patch
+    from openai import OpenAI
+    from openai.types.chat import ChatCompletion, ChatCompletionMessage
+    from openai.types.chat.chat_completion import Choice
+    import httpx
+
     litellm.set_verbose = False
     model_name = "deepinfra/meta-llama/Llama-2-70b-chat-hf"
     tools = [
@@ -3320,7 +3327,51 @@ def test_completion_deep_infra(drop_params):
             "content": "What's the weather like in Boston today in Fahrenheit?",
         }
     ]
-    try:
+
+    mock_response = ChatCompletion(
+        id="chatcmpl-mock",
+        choices=[
+            Choice(
+                finish_reason="stop",
+                index=0,
+                message=ChatCompletionMessage(
+                    content="It's sunny.", role="assistant"
+                ),
+            )
+        ],
+        created=1234567890,
+        model="meta-llama/Llama-2-70b-chat-hf",
+        object="chat.completion",
+        usage={"completion_tokens": 5, "prompt_tokens": 20, "total_tokens": 25},
+    )
+
+    mock_raw = MagicMock()
+    mock_raw.parse.return_value = mock_response
+    mock_raw.headers = httpx.Headers({"content-type": "application/json"})
+    mock_raw.status_code = 200
+
+    with patch(
+        "litellm.llms.openai.openai.OpenAIChatCompletion.make_sync_openai_chat_completion_request",
+        return_value=(mock_raw, mock_response),
+    ) as mock_create:
+        if drop_params is False:
+            # DeepInfra doesn't support tool_choice, should raise UnsupportedParamsError
+            with pytest.raises(litellm.exceptions.UnsupportedParamsError):
+                completion(
+                    model=model_name,
+                    messages=messages,
+                    temperature=0,
+                    max_tokens=10,
+                    tools=tools,
+                    tool_choice={
+                        "type": "function",
+                        "function": {"name": "get_current_weather"},
+                    },
+                    drop_params=drop_params,
+                    api_key="fake-api-key",
+                )
+            return
+
         response = completion(
             model=model_name,
             messages=messages,
@@ -3332,33 +3383,75 @@ def test_completion_deep_infra(drop_params):
                 "function": {"name": "get_current_weather"},
             },
             drop_params=drop_params,
+            api_key="fake-api-key",
         )
-        # Add any assertions here to check the response
-        print(response)
-    except Exception as e:
-        if drop_params is True:
-            pytest.fail(f"Error occurred: {e}")
+
+        # Verify the call was made
+        mock_create.assert_called_once()
+        call_kwargs = mock_create.call_args.kwargs
+
+        # Verify request shape
+        data = call_kwargs["data"]
+        assert data["model"] == "meta-llama/Llama-2-70b-chat-hf"
+        assert data["messages"] == messages
+        assert data["temperature"] == 0
+        assert data["max_tokens"] == 10
+        # tool_choice should be dropped for unsupported params
+        assert "tool_choice" not in data
 
 
 # test_completion_deep_infra()
 
 
 def test_completion_deep_infra_mistral():
-    print("deep infra test with temp=0")
+    """Test that DeepInfra Mistral requests are shaped correctly without making real API calls."""
+    from unittest.mock import MagicMock, patch
+    from openai.types.chat import ChatCompletion, ChatCompletionMessage
+    from openai.types.chat.chat_completion import Choice
+    import httpx
+
     model_name = "deepinfra/mistralai/Mistral-7B-Instruct-v0.1"
-    try:
+
+    mock_response = ChatCompletion(
+        id="chatcmpl-mock",
+        choices=[
+            Choice(
+                finish_reason="stop",
+                index=0,
+                message=ChatCompletionMessage(
+                    content="Hello!", role="assistant"
+                ),
+            )
+        ],
+        created=1234567890,
+        model="mistralai/Mistral-7B-Instruct-v0.1",
+        object="chat.completion",
+        usage={"completion_tokens": 5, "prompt_tokens": 20, "total_tokens": 25},
+    )
+
+    mock_raw = MagicMock()
+    mock_raw.parse.return_value = mock_response
+    mock_raw.headers = httpx.Headers({"content-type": "application/json"})
+    mock_raw.status_code = 200
+
+    with patch(
+        "litellm.llms.openai.openai.OpenAIChatCompletion.make_sync_openai_chat_completion_request",
+        return_value=(mock_raw, mock_response),
+    ) as mock_create:
         response = completion(
             model=model_name,
             messages=messages,
-            temperature=0.01,  # mistrail fails with temperature=0
+            temperature=0.01,
             max_tokens=10,
+            api_key="fake-api-key",
         )
-        # Add any assertions here to check the response
-        print(response)
-    except litellm.exceptions.Timeout as e:
-        pass
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
+
+        mock_create.assert_called_once()
+        call_kwargs = mock_create.call_args.kwargs
+        data = call_kwargs["data"]
+        assert data["model"] == "mistralai/Mistral-7B-Instruct-v0.1"
+        assert data["temperature"] == 0.01
+        assert data["max_tokens"] == 10
 
 
 # test_completion_deep_infra_mistral()