diff --git a/functioncalling_finetuning/evals/evaluation_script.py b/functioncalling_finetuning/evals/evaluation_script.py
index c5c4813..4257d51 100644
--- a/functioncalling_finetuning/evals/evaluation_script.py
+++ b/functioncalling_finetuning/evals/evaluation_script.py
@@ -171,14 +171,10 @@ def load_hermes_dataset(max_samples=500):
     return samples
 
 
-async def get_model_response_async(model, system_prompt, user_query, semaphore):
+async def get_model_response_async(model, system_prompt, user_query, semaphore, client):
     """Get OpenAI model response asynchronously with rate limiting."""
     
     async with semaphore:
-        client = AsyncOpenAI(
-            api_key=API_KEY,
-            base_url=BASE_URL,  # Adjust if using a different endpoint
-        )
         messages = []
         if system_prompt:
             messages.append({"role": "system", "content": system_prompt})
@@ -346,12 +342,12 @@ def print_model_summary(model, results):
     print(f"Format Valid: {format_valid:.3f}")
 
 
-async def process_single_sample(sample: Dict[str, Any], model: str, semaphore: asyncio.Semaphore) -> Dict[str, Any]:
+async def process_single_sample(sample: Dict[str, Any], model: str, semaphore: asyncio.Semaphore, client) -> Dict[str, Any]:
     """Process a single sample asynchronously."""
     
     # Get model response
     response = await get_model_response_async(
-        model, sample["system_prompt"], sample["user_query"], semaphore
+        model, sample["system_prompt"], sample["user_query"], semaphore, client
     )
     
     # print(f"Sample {sample['id']} response: {response}")
@@ -386,6 +382,12 @@ async def run_benchmark_async(eval_samples: List[Dict[str, Any]], models: List[s
     
     all_results = []
     
+    # Create shared client for all requests
+    client = AsyncOpenAI(
+        api_key=API_KEY,
+        base_url=BASE_URL
+    )
+    
     for model in models:
         print(f"\nEvaluating {model}...")
         start_time = time.time()
@@ -397,7 +399,7 @@ async def run_benchmark_async(eval_samples: List[Dict[str, Any]], models: List[s
         tasks = []
         for sample in eval_samples:
             task = asyncio.create_task(
-                process_single_sample(sample, model, semaphore)
+                process_single_sample(sample, model, semaphore, client)
             )
             tasks.append(task)