diff --git a/fastdeploy/engine/common_engine.py b/fastdeploy/engine/common_engine.py
index b70abf8ee1f..9e46a9af92b 100644
--- a/fastdeploy/engine/common_engine.py
+++ b/fastdeploy/engine/common_engine.py
@@ -1097,6 +1097,7 @@ def _fetch_request():
                 if self.engine_worker_queue.exist_tasks():
                     time.sleep(0.001)
                     continue
+
                 if self.cfg.scheduler_config.splitwise_role != "mixed":
                     if not is_fetching:
                         is_fetching = True
@@ -1118,7 +1119,10 @@ def _fetch_request():
                 if hasattr(self.resource_manager, "scheduler_unhandled_request_num"):
                     self.resource_manager.scheduler_unhandled_request_num = self._get_scheduler_unhandled_request_num()
                 # 2. Schedule requests
-                batch_request, error_tasks = self.resource_manager.schedule()
+                if self.cfg.scheduler_config.splitwise_role == "prefill":
+                    batch_request, error_tasks = self.resource_manager.prefill_schedule()
+                else:
+                    batch_request, error_tasks = self.resource_manager.schedule()
 
                 # 3. Send to engine
                 if len(batch_request) > 0:
diff --git a/fastdeploy/engine/sched/resource_manager_v1.py b/fastdeploy/engine/sched/resource_manager_v1.py
index 8bc831844f5..692e210623a 100644
--- a/fastdeploy/engine/sched/resource_manager_v1.py
+++ b/fastdeploy/engine/sched/resource_manager_v1.py
@@ -1248,6 +1248,32 @@ def _allocate_decode_and_extend():
 
             return batch_request, error_reqs
 
+    def prefill_schedule(self):
+        with self.lock:
+            # P instance has no decode — full budget for prefill
+            batch_request = BatchRequest()
+            token_budget = self.config.scheduler_config.max_num_batched_tokens
+
+            assert len(self.waiting) == 0, "Prefill scheduler should not have waiting requests"
+
+            # Prepare prefill tasks for all running requests
+            for request in list(self.running):
+                if self._is_decoding(request):
+                    continue
+
+                num_new_tokens = self._get_num_new_tokens(request, token_budget)
+                if num_new_tokens == 0:
+                    continue
+
+                # Add requests into scheduled batch as blocks were preallocated
+                llm_logger.debug(f"schedule prefill tasks {request.request_id} with {num_new_tokens} tokens")
+                batch_request.add_request(self._prepare_prefill_task(request, num_new_tokens))
+                token_budget -= num_new_tokens
+                request.num_computed_tokens += num_new_tokens
+
+            self.update_metrics()
+            return batch_request, []
+
     def waiting_async_process(self, request: Request) -> None:
         """
         Check if async preprocessing is complete for a request.