diff --git a/litellm/tests/test_split_test.py b/litellm/tests/test_split_test.py
index 35ff007be..e26079642 100644
--- a/litellm/tests/test_split_test.py
+++ b/litellm/tests/test_split_test.py
@@ -11,8 +11,8 @@ import litellm
 from litellm import completion_with_split_tests
 litellm.set_verbose = True
 split_per_model = {
-	"gpt-4": 0.7, 
-	"claude-instant-1.2": 0.3
+	"gpt-3.5-turbo": 0.8, 
+	"claude-instant-1.2": 0.1
 }
 
 messages = [{ "content": "Hello, how are you?","role": "user"}]
@@ -21,4 +21,4 @@ messages = [{ "content": "Hello, how are you?","role": "user"}]
 
 # test with client 
 
-print(completion_with_split_tests(models=split_per_model, messages=messages, use_client=True, id=1234))
\ No newline at end of file
+print(completion_with_split_tests(models=split_per_model, messages=messages, use_client=True, id="ishaan_1@berri.ai"))
\ No newline at end of file
diff --git a/litellm/utils.py b/litellm/utils.py
index 12260de02..9fda83790 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -1934,9 +1934,10 @@ def get_model_split_test(models, completion_call_id):
         data = response.json()
         # update model list
         split_test_models = data["split_test_models"]
+        model_configs = data.get("model_configs", {})
         # update environment - if required
         threading.Thread(target=get_all_keys, args=()).start()
-        return split_test_models
+        return split_test_models, model_configs
     except:
         print_verbose(
             f"[Non-Blocking Error] get_all_keys error - {traceback.format_exc()}"
@@ -1959,13 +1960,28 @@ def completion_with_split_tests(models={}, messages=[], use_client=False, overri
         if "id" not in kwargs or kwargs["id"] is None:
             raise ValueError("Please tag this completion call, if you'd like to update it's split test values through the UI. - eg. `completion_with_split_tests(.., id=1234)`.")
         # get the most recent model split list from server 
-        models = get_model_split_test(models=models, completion_call_id=kwargs["id"])
+        models, model_configs = get_model_split_test(models=models, completion_call_id=kwargs["id"])
 
     try:
         selected_llm = random.choices(list(models.keys()), weights=list(models.values()))[0]
     except:
         traceback.print_exc()
         raise ValueError("""models does not follow the required format - {'model_name': 'split_percentage'}, e.g. {'gpt-4': 0.7, 'huggingface/wizard-coder': 0.3}""")
+    
+    # use dynamic model configs if users set 
+    if model_configs!={}:
+        selected_model_configs = model_configs.get(selected_llm, {})
+        if "prompt" in selected_model_configs: # special case, add this to messages as system prompt
+            messages.append({"role": "system", "content": selected_model_configs["prompt"]})
+            selected_model_configs.pop("prompt")
+        for param_name in selected_model_configs:
+            if param_name == "temperature":
+                kwargs[param_name] = float(selected_model_configs[param_name])
+            elif param_name == "max_tokens":
+                kwargs[param_name] = int(selected_model_configs[param_name])
+            else:
+                kwargs[param_name] = selected_model_configs[param_name]
+
     return litellm.completion(model=selected_llm, messages=messages, use_client=use_client, **kwargs)
 
 def completion_with_fallbacks(**kwargs):