diff --git a/litellm/llms/vertex_ai/common_utils.py b/litellm/llms/vertex_ai/common_utils.py
index 51e104d0a94..f298d6f4a12 100644
--- a/litellm/llms/vertex_ai/common_utils.py
+++ b/litellm/llms/vertex_ai/common_utils.py
@@ -699,7 +699,7 @@ def _build_vertex_schema(parameters: dict, add_property_ordering: bool = False):
 
 
 def _convert_consts_to_enums(
-    schema: dict[str, object],  # mutable-ok: response schema is normalized in place
+    schema: dict[str, object],  # mutable-ok: Gemini schema is normalized in place
     depth: int = 0,
 ) -> None:
     """
diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
index 69fe5678de9..5d3db82f94b 100644
--- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
+++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
@@ -86,6 +86,7 @@ from ..common_utils import (
     VertexAIError,
     _build_json_schema,
     _build_vertex_schema,
+    _convert_consts_to_enums,
     supports_response_json_schema,
 )
 from ..vertex_llm_base import VertexBase
@@ -594,16 +595,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
         for tool in value:
             openai_function_object: ChatCompletionToolParamFunctionChunk | None = None
             if "function" in tool:  # tools list
-                _openai_function_object = ChatCompletionToolParamFunctionChunk(**tool["function"])
-
-                if (
-                    "parameters" in _openai_function_object
-                    and _openai_function_object["parameters"] is not None
-                    and isinstance(_openai_function_object["parameters"], dict)
-                ):  # OPENAI accepts JSON Schema, Google accepts OpenAPI schema.
-                    _openai_function_object["parameters"] = _build_vertex_schema(_openai_function_object["parameters"])
-
-                openai_function_object = _openai_function_object
+                openai_function_object = ChatCompletionToolParamFunctionChunk(**tool["function"])
 
             elif "name" in tool:  # functions list
                 openai_function_object = ChatCompletionToolParamFunctionChunk(**tool)
@@ -663,13 +655,14 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
                 )
                 _description = openai_function_object.get("description", None)
                 _parameters = openai_function_object.get("parameters", None)
-                if isinstance(_parameters, str) and len(_parameters) == 0:
-                    _parameters = {
-                        "type": "object",
-                    }
                 if _description is not None:
                     gtool_func_declaration["description"] = _description
-                if _parameters is not None:
+                if isinstance(_parameters, dict):
+                    _convert_consts_to_enums(_parameters)
+                    gtool_func_declaration["parameters"] = _build_vertex_schema(_parameters)
+                elif isinstance(_parameters, str) and len(_parameters) == 0:
+                    gtool_func_declaration["parameters"] = {"type": "object"}
+                elif _parameters is not None:
                     gtool_func_declaration["parameters"] = _parameters
                 gtool_func_declarations.append(gtool_func_declaration)
             else:
diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
index d2788408e09..359e6de539a 100644
--- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
+++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
@@ -2,7 +2,7 @@ import asyncio
 import json
 import re
 from copy import deepcopy
-from typing import Final, List, cast
+from typing import Final, List, Literal, cast
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -1219,6 +1219,34 @@ def test_vertex_ai_map_tools():
     assert tools == new_tools
 
 
+@pytest.mark.parametrize("legacy_functions", [False, True])
+def test_gemini_map_tool_converts_pydantic_consts_to_enums(legacy_functions: bool):
+    class Operation(BaseModel):
+        kind: Literal["create"]
+        resource_name: str
+
+    class ToolInput(BaseModel):
+        status: Literal["pending"]
+        operation: Operation
+
+    function = {
+        "name": "perform_action",
+        "description": "Perform an action",
+        "parameters": ToolInput.model_json_schema(),
+    }
+    tools_input = [function] if legacy_functions else [{"type": "function", "function": function}]
+
+    tools = VertexGeminiConfig()._map_function(value=tools_input, optional_params={})
+    parameters = tools[0]["function_declarations"][0]["parameters"]
+
+    assert parameters["properties"]["status"]["enum"] == ["pending"]
+    assert parameters["properties"]["operation"]["properties"]["kind"]["enum"] == ["create"]
+    assert parameters["properties"]["operation"]["properties"]["resource_name"]["type"] == "string"
+    assert parameters["properties"]["operation"]["required"] == ["kind", "resource_name"]
+    assert "const" not in json.dumps(parameters)
+    assert "$ref" not in json.dumps(parameters)
+
+
 def test_vertex_ai_map_tool_with_anyof():
     """
     Related issue: https://github.com/BerriAI/litellm/issues/11164