diff --git a/libs/vertexai/langchain_google_vertexai/llms.py b/libs/vertexai/langchain_google_vertexai/llms.py
index 59fb147b..ca16de4a 100644
--- a/libs/vertexai/langchain_google_vertexai/llms.py
+++ b/libs/vertexai/langchain_google_vertexai/llms.py
@@ -217,7 +217,7 @@ def _default_params(self) -> Dict[str, Any]:
             default_value = default_params.get(param_name)
             if param_value or default_value:
                 updated_params[param_name] = (
-                    param_value if param_value else default_value
+                    param_value if param_value is not None else default_value
                 )
         return updated_params
 
diff --git a/libs/vertexai/tests/unit_tests/test_llm.py b/libs/vertexai/tests/unit_tests/test_llm.py
new file mode 100644
index 00000000..8d65221e
--- /dev/null
+++ b/libs/vertexai/tests/unit_tests/test_llm.py
@@ -0,0 +1,49 @@
+from typing import Any, Dict
+from unittest import TestCase
+from unittest.mock import MagicMock, patch
+
+from langchain_google_vertexai.llms import VertexAI
+
+
+def test_vertexai_args_passed() -> None:
+    response_text = "Goodbye"
+    user_prompt = "Hello"
+    prompt_params: Dict[str, Any] = {
+        "max_output_tokens": 1,
+        "temperature": 0,
+        "top_k": 10,
+        "top_p": 0.5,
+    }
+
+    # Mock the library to ensure the args are passed correctly
+    with patch("langchain_google_vertexai.llms.GenerativeModel") as model:
+        with patch("langchain_google_vertexai.llms.get_generation_info") as gen_info:
+            gen_info.return_value = {}
+            mock_response = MagicMock()
+            candidate = MagicMock()
+            candidate.text = response_text
+            mock_response.candidates = [candidate]
+            model_instance = MagicMock()
+            model_instance.generate_content.return_value = mock_response
+            model.return_value = model_instance
+
+            llm = VertexAI(model_name="gemini-pro", **prompt_params)
+            response = llm.invoke("Hello")
+            assert response == response_text
+            model_instance.generate_content.assert_called_once
+
+            assert model_instance.generate_content.call_args.args[0] == [user_prompt]
+            TestCase().assertCountEqual(
+                model_instance.generate_content.call_args.kwargs,
+                {
+                    "stream": False,
+                    "safety_settings": None,
+                    "generation_config": {
+                        "max_output_tokens": 1,
+                        "temperature": 0,
+                        "top_k": 10,
+                        "top_p": 0.5,
+                        "stop_sequences": None,
+                    },
+                },
+            )