diff --git a/litellm/utils.py b/litellm/utils.py
index b777819e5..5729395d3 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -7107,6 +7107,7 @@ def get_model_info(model: str) -> ModelInfo:
             - output_cost_per_token (float): The cost per token for output.
             - litellm_provider (str): The provider of the model (e.g., "openai").
             - mode (str): The mode of the model (e.g., "chat" or "completion").
+            - supported_openai_params (List[str]): A list of supported OpenAI parameters for the model.
 
     Raises:
         Exception: If the model is not mapped yet.
@@ -7118,9 +7119,11 @@ def get_model_info(model: str) -> ModelInfo:
             "input_cost_per_token": 0.00003,
             "output_cost_per_token": 0.00006,
             "litellm_provider": "openai",
-            "mode": "chat"
+            "mode": "chat",
+            "supported_openai_params": ["temperature", "max_tokens", "top_p", "frequency_penalty", "presence_penalty"]
         }
     """
+    supported_openai_params: Union[List[str], None] = []
 
     def _get_max_position_embeddings(model_name):
         # Construct the URL for the config.json file
@@ -7148,9 +7151,18 @@ def get_model_info(model: str) -> ModelInfo:
         azure_llms = litellm.azure_llms
         if model in azure_llms:
             model = azure_llms[model]
-        if model in litellm.model_cost:
-            return litellm.model_cost[model]
-        model, custom_llm_provider, _, _ = get_llm_provider(model=model)
+        ##########################
+        # Get custom_llm_provider
+        split_model, custom_llm_provider = model, ""
+        try:
+            split_model, custom_llm_provider, _, _ = get_llm_provider(model=model)
+        except:
+            pass
+        #########################
+
+        supported_openai_params = litellm.get_supported_openai_params(
+            model=model, custom_llm_provider=custom_llm_provider
+        )
         if custom_llm_provider == "huggingface":
             max_tokens = _get_max_position_embeddings(model_name=model)
             return {
@@ -7159,15 +7171,26 @@ def get_model_info(model: str) -> ModelInfo:
                 "output_cost_per_token": 0,
                 "litellm_provider": "huggingface",
                 "mode": "chat",
+                "supported_openai_params": supported_openai_params,
             }
         else:
             """
-            Check if model in model cost map
+            Check if:
+            1. 'model' in litellm.model_cost. Checks "groq/llama3-8b-8192" in  litellm.model_cost
+            2. 'split_model' in litellm.model_cost. Checks "llama3-8b-8192" in litellm.model_cost
             """
             if model in litellm.model_cost:
-                return litellm.model_cost[model]
+                _model_info = litellm.model_cost[model]
+                _model_info["supported_openai_params"] = supported_openai_params
+                return _model_info
+            if split_model in litellm.model_cost:
+                _model_info = litellm.model_cost[split_model]
+                _model_info["supported_openai_params"] = supported_openai_params
+                return _model_info
             else:
-                raise Exception()
+                raise ValueError(
+                    "This model isn't mapped yet. Add it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json"
+                )
     except:
         raise Exception(
             "This model isn't mapped yet. Add it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json"