diff --git a/berkeley-function-call-leaderboard/bfcl/model_handler/proprietary_model/claude.py b/berkeley-function-call-leaderboard/bfcl/model_handler/proprietary_model/claude.py
index 8d81ecfbc..30fa6dc17 100644
--- a/berkeley-function-call-leaderboard/bfcl/model_handler/proprietary_model/claude.py
+++ b/berkeley-function-call-leaderboard/bfcl/model_handler/proprietary_model/claude.py
@@ -3,6 +3,8 @@
 
 from anthropic import Anthropic
 from anthropic.types import TextBlock, ToolUseBlock
+from anthropic.types.beta.message_create_params import MessageCreateParamsNonStreaming
+from anthropic.types.beta.messages.batch_create_params import Request
 from bfcl.model_handler.base_handler import BaseHandler
 from bfcl.model_handler.constant import DEFAULT_SYSTEM_PROMPT, GORILLA_TO_OPENAPI
 from bfcl.model_handler.model_style import ModelStyle
@@ -66,23 +68,43 @@ def decode_execute(self, result):
         else:
             function_call = convert_to_function_call(result)
             return function_call
+        
+    # Helper function to process the batch response and return results
+    def _process_batch_response(self, batch_response):
+        results = []
+        for result in batch_response:
+            if result.result.type == "succeeded":
+                results.append(result.result.message.content)
+            elif result.result.type == "errored":
+                print(f"Error: {result.result.error}")
+    
+        return results
 
     #### FC methods ####
 
     def _query_FC(self, inference_data: dict):
-        inference_data["inference_input_log"] = {
-            "message": repr(inference_data["message"]),
-            "tools": inference_data["tools"],
-        }
+        # Initialize batch request list
+        batch_requests = []
+
+        # For each message in the inference data, add to the batch request
+        for message in inference_data["message"]:
+            batch_requests.append(
+                Request(
+                    custom_id=f"fc-{message['content'][:20]}",  # Custom ID for each request
+                    params=MessageCreateParamsNonStreaming(
+                        model=self.model_name.strip("-FC"),
+                        max_tokens=8192 if "claude-3-5-sonnet-20240620" in self.model_name else 4096,
+                        tools=inference_data["tools"],
+                        messages=[message],
+                    )
+                )
+            )
+    
+        # Send the batch request
+        batch_response = self.client.beta.messages.batches.create(requests=batch_requests)
 
-        return self.client.messages.create(
-            model=self.model_name.strip("-FC"),
-            max_tokens=(
-                8192 if "claude-3-5-sonnet-20240620" in self.model_name else 4096
-            ),  # 3.5 Sonnet has a higher max token limit
-            tools=inference_data["tools"],
-            messages=inference_data["message"],
-        )
+        # Process the batch response
+        return self._process_batch_response(batch_response)
 
     def _pre_query_processing_FC(self, inference_data: dict, test_entry: dict) -> dict:
         for round_idx in range(len(test_entry["question"])):
@@ -183,22 +205,29 @@ def _add_execution_results_FC(
     #### Prompting methods ####
 
     def _query_prompting(self, inference_data: dict):
-        inference_data["inference_input_log"] = {
-            "message": repr(inference_data["message"]),
-            "system_prompt": inference_data["system_prompt"],
-        }
-
-        api_response =  self.client.messages.create(
-            model=self.model_name,
-            max_tokens=(
-                8192 if "claude-3-5-sonnet-20240620" in self.model_name else 4096
-            ),  # 3.5 Sonnet has a higher max token limit
-            temperature=self.temperature,
-            system=inference_data["system_prompt"],
-            messages=inference_data["message"],
-        )
-        
-        return api_response
+        # Initialize batch request list
+        batch_requests = []
+
+        # Add all the messages to the batch
+        for message in inference_data["message"]:
+            batch_requests.append(
+                Request(
+                    custom_id=f"prompt-{message['content'][:20]}",
+                    params=MessageCreateParamsNonStreaming(
+                        model=self.model_name,
+                        max_tokens=8192 if "claude-3-5-sonnet-20240620" in self.model_name else 4096,
+                        temperature=self.temperature,
+                        messages=[message],
+                        system=inference_data["system_prompt"],
+                    )
+                )
+            )
+    
+        # Send the batch request
+        batch_response = self.client.beta.messages.batches.create(requests=batch_requests)
+    
+        # Process the batch response
+        return self._process_batch_response(batch_response)
 
     def _pre_query_processing_prompting(self, test_entry: dict) -> dict:
         functions: list = test_entry["function"]
@@ -261,4 +290,4 @@ def _add_execution_results_prompting(
             {"role": "user", "content": formatted_results_message}
         )
 
-        return inference_data
+        return inference_data
\ No newline at end of file