diff --git a/litellm/llms/gemini.py b/litellm/llms/gemini.py
index 126569ecc0c9..21d85a2fcfd2 100644
--- a/litellm/llms/gemini.py
+++ b/litellm/llms/gemini.py
@@ -6,7 +6,8 @@
 from litellm.utils import ModelResponse, get_secret, Choices, Message, Usage
 import litellm
 import sys, httpx
-from .prompt_templates.factory import prompt_factory, custom_prompt
+from .prompt_templates.factory import prompt_factory, custom_prompt, get_system_prompt
+from packaging.version import Version
 
 
 class GeminiError(Exception):
@@ -103,6 +104,13 @@ async def __aiter__(self):
                 break
 
 
+def supports_system_instruction():
+    import google.generativeai as genai
+
+    gemini_pkg_version = Version(genai.__version__)
+    return gemini_pkg_version >= Version("0.5.0")
+
+
 def completion(
     model: str,
     messages: list,
@@ -124,7 +132,7 @@ def completion(
             "Importing google.generativeai failed, please run 'pip install -q google-generativeai"
         )
     genai.configure(api_key=api_key)
-
+    system_prompt = ""
     if model in custom_prompt_dict:
         # check if the model has a registered custom prompt
         model_prompt_details = custom_prompt_dict[model]
@@ -135,6 +143,7 @@ def completion(
             messages=messages,
         )
     else:
+        system_prompt, messages = get_system_prompt(messages=messages)
         prompt = prompt_factory(
             model=model, messages=messages, custom_llm_provider="gemini"
         )
@@ -166,7 +175,11 @@ def completion(
     )
     ## COMPLETION CALL
     try:
-        _model = genai.GenerativeModel(f"models/{model}")
+        _params = {"model_name": "models/{}".format(model)}
+        _system_instruction = supports_system_instruction()
+        if _system_instruction and len(system_prompt) > 0:
+            _params["system_instruction"] = system_prompt
+        _model = genai.GenerativeModel(**_params)
         if stream == True:
             if acompletion == True:
 
@@ -213,11 +226,12 @@ async def async_streaming():
                 encoding=encoding,
             )
         else:
-            response = _model.generate_content(
-                contents=prompt,
-                generation_config=genai.types.GenerationConfig(**inference_params),
-                safety_settings=safety_settings,
-            )
+            params = {
+                "contents": prompt,
+                "generation_config": genai.types.GenerationConfig(**inference_params),
+                "safety_settings": safety_settings,
+            }
+            response = _model.generate_content(**params)
     except Exception as e:
         raise GeminiError(
             message=str(e),
diff --git a/litellm/llms/prompt_templates/factory.py b/litellm/llms/prompt_templates/factory.py
index 5d3d70a5972e..2abb544095d7 100644
--- a/litellm/llms/prompt_templates/factory.py
+++ b/litellm/llms/prompt_templates/factory.py
@@ -959,7 +959,20 @@ def parse_xml_params(xml_content, json_schema: Optional[dict] = None):
     return params
 
 
-###
+### GEMINI HELPER FUNCTIONS ###
+
+
+def get_system_prompt(messages):
+    system_prompt_indices = []
+    system_prompt = ""
+    for idx, message in enumerate(messages):
+        if message["role"] == "system":
+            system_prompt += message["content"]
+            system_prompt_indices.append(idx)
+    if len(system_prompt_indices) > 0:
+        for idx in reversed(system_prompt_indices):
+            messages.pop(idx)
+    return system_prompt, messages
 
 
 def convert_openai_message_to_cohere_tool_result(message):
diff --git a/litellm/llms/vertex_ai.py b/litellm/llms/vertex_ai.py
index a38530f151db..ddfc8e9fb7d4 100644
--- a/litellm/llms/vertex_ai.py
+++ b/litellm/llms/vertex_ai.py
@@ -417,7 +417,7 @@ def completion(
             return async_completion(**data)
 
         if mode == "vision":
-            print_verbose("\nMaking VertexAI Gemini Pro Vision Call")
+            print_verbose("\nMaking VertexAI Gemini Pro / Pro Vision Call")
             print_verbose(f"\nProcessing input messages = {messages}")
             tools = optional_params.pop("tools", None)
             prompt, images = _gemini_vision_convert_messages(messages=messages)