diff --git a/litellm/llms/vertex_httpx.py b/litellm/llms/vertex_httpx.py
index 26f3b814b..b433301ef 100644
--- a/litellm/llms/vertex_httpx.py
+++ b/litellm/llms/vertex_httpx.py
@@ -123,6 +123,67 @@ class VertexAIConfig:
             and v is not None
         }
 
+    def get_supported_openai_params(self):
+        return [
+            "temperature",
+            "top_p",
+            "max_tokens",
+            "stream",
+            "tools",
+            "tool_choice",
+            "response_format",
+            "n",
+            "stop",
+            "extra_headers",
+        ]
+
+    def map_openai_params(self, non_default_params: dict, optional_params: dict):
+        for param, value in non_default_params.items():
+            if param == "temperature":
+                optional_params["temperature"] = value
+            if param == "top_p":
+                optional_params["top_p"] = value
+            if (
+                param == "stream" and value == True
+            ):  # sending stream = False, can cause it to get passed unchecked and raise issues
+                optional_params["stream"] = value
+            if param == "n":
+                optional_params["candidate_count"] = value
+            if param == "stop":
+                if isinstance(value, str):
+                    optional_params["stop_sequences"] = [value]
+                elif isinstance(value, list):
+                    optional_params["stop_sequences"] = value
+            if param == "max_tokens":
+                optional_params["max_output_tokens"] = value
+            if param == "response_format" and value["type"] == "json_object":
+                optional_params["response_mime_type"] = "application/json"
+            if param == "frequency_penalty":
+                optional_params["frequency_penalty"] = value
+            if param == "presence_penalty":
+                optional_params["presence_penalty"] = value
+            if param == "tools" and isinstance(value, list):
+                from vertexai.preview import generative_models
+
+                gtool_func_declarations = []
+                for tool in value:
+                    gtool_func_declaration = generative_models.FunctionDeclaration(
+                        name=tool["function"]["name"],
+                        description=tool["function"].get("description", ""),
+                        parameters=tool["function"].get("parameters", {}),
+                    )
+                    gtool_func_declarations.append(gtool_func_declaration)
+                optional_params["tools"] = [
+                    generative_models.Tool(
+                        function_declarations=gtool_func_declarations
+                    )
+                ]
+            if param == "tool_choice" and (
+                isinstance(value, str) or isinstance(value, dict)
+            ):
+                pass
+        return optional_params
+
     def get_mapped_special_auth_params(self) -> dict:
         """
         Common auth params across bedrock/vertex_ai/azure/watsonx
diff --git a/litellm/utils.py b/litellm/utils.py
index 1f0aa4c71..0f52df63c 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -4216,7 +4216,7 @@ def get_supported_openai_params(
             if model.startswith("meta/"):
                 return litellm.VertexAILlama3Config().get_supported_openai_params()
 
-            return litellm.VertexAIConfig().get_supported_openai_params()
+            return litellm.VertexGeminiConfig().get_supported_openai_params()
         elif request_type == "embeddings":
             return litellm.VertexAITextEmbeddingConfig().get_supported_openai_params()
     elif custom_llm_provider == "vertex_ai_beta":