diff --git a/litellm/tests/test_function_calling.py b/litellm/tests/test_function_calling.py
index ffef8f6594..0d2aad59bc 100644
--- a/litellm/tests/test_function_calling.py
+++ b/litellm/tests/test_function_calling.py
@@ -219,3 +219,95 @@ def test_parallel_function_call_stream():
 
 
 # test_parallel_function_call_stream()
+
+
+def test_groq_parallel_function_call():
+    litellm.set_verbose = True
+    try:
+        # Step 1: send the conversation and available functions to the model
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a function calling LLM that uses the data extracted from get_current_weather to answer questions about the weather in San Francisco.",
+            },
+            {
+                "role": "user",
+                "content": "What's the weather like in San Francisco?",
+            },
+        ]
+        tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": "get_current_weather",
+                    "description": "Get the current weather in a given location",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {
+                                "type": "string",
+                                "description": "The city and state, e.g. San Francisco, CA",
+                            },
+                            "unit": {
+                                "type": "string",
+                                "enum": ["celsius", "fahrenheit"],
+                            },
+                        },
+                        "required": ["location"],
+                    },
+                },
+            }
+        ]
+        response = litellm.completion(
+            model="groq/llama2-70b-4096",
+            messages=messages,
+            tools=tools,
+            tool_choice="auto",  # auto is default, but we'll be explicit
+        )
+        print("Response\n", response)
+        response_message = response.choices[0].message
+        tool_calls = response_message.tool_calls
+
+        assert isinstance(response.choices[0].message.tool_calls[0].function.name, str)
+        assert isinstance(
+            response.choices[0].message.tool_calls[0].function.arguments, str
+        )
+
+        print("length of tool calls", len(tool_calls))
+        print("Expecting there to be 3 tool calls")
+
+        # Step 2: check if the model wanted to call a function
+        if tool_calls:
+            # Step 3: call the function
+            # Note: the JSON response may not always be valid; be sure to handle errors
+            available_functions = {
+                "get_current_weather": get_current_weather,
+            }  # only one function in this example, but you can have multiple
+            messages.append(
+                response_message
+            )  # extend conversation with assistant's reply
+            print("Response message\n", response_message)
+            # Step 4: send the info for each function call and function response to the model
+            for tool_call in tool_calls:
+                function_name = tool_call.function.name
+                function_to_call = available_functions[function_name]
+                function_args = json.loads(tool_call.function.arguments)
+                function_response = function_to_call(
+                    location=function_args.get("location"),
+                    unit=function_args.get("unit"),
+                )
+                messages.append(
+                    {
+                        "tool_call_id": tool_call.id,
+                        "role": "tool",
+                        "name": function_name,
+                        "content": function_response,
+                    }
+                )  # extend conversation with function response
+            print(f"messages: {messages}")
+            second_response = litellm.completion(
+                model="groq/llama2-70b-4096", messages=messages
+            )  # get a new response from the model where it can see the function response
+            print("second response\n", second_response)
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")