diff --git a/apps/rmbg/service.py b/apps/rmbg/service.py
index 9ba22eb..0363b47 100644
--- a/apps/rmbg/service.py
+++ b/apps/rmbg/service.py
@@ -454,6 +454,60 @@ class RmbgService:
         batch_size = settings.batch_size
         loop = asyncio.get_event_loop()
         
+        # 性能统计变量
+        download_time = 0.0
+        gpu_inference_time = 0.0
+        save_time = 0.0
+        batch_count = 0
+        batch_sizes = []
+        stats_printed = False
+        
+        def print_stats():
+            """输出性能统计信息"""
+            nonlocal stats_printed
+            if stats_printed:
+                return
+            stats_printed = True
+            
+            total_time = time.time() - batch_start_time
+            other_time = total_time - download_time - gpu_inference_time - save_time
+            
+            logger.info("=" * 60)
+            logger.info("📊 批处理性能统计")
+            logger.info("=" * 60)
+            logger.info(f"图片总数: {total}")
+            logger.info(f"成功数量: {success_count}")
+            logger.info(f"失败数量: {error_count}")
+            logger.info(f"批处理次数: {batch_count}")
+            logger.info(f"每批图片数: {batch_sizes}")
+            logger.info("-" * 60)
+            logger.info("⏱️  各阶段耗时:")
+            
+            if total_time > 0:
+                download_pct = (download_time / total_time) * 100
+                gpu_pct = (gpu_inference_time / total_time) * 100
+                save_pct = (save_time / total_time) * 100
+                other_pct = (other_time / total_time) * 100
+                
+                logger.info(f"  1. 下载图片:     {download_time:.3f}s ({download_pct:.1f}%)")
+                logger.info(f"  2. GPU推理:      {gpu_inference_time:.3f}s ({gpu_pct:.1f}%)")
+                logger.info(f"  3. 保存图片:     {save_time:.3f}s ({save_pct:.1f}%)")
+                logger.info(f"  4. 其他开销:     {other_time:.3f}s ({other_pct:.1f}%)")
+            else:
+                logger.info(f"  1. 下载图片:     {download_time:.3f}s")
+                logger.info(f"  2. GPU推理:      {gpu_inference_time:.3f}s")
+                logger.info(f"  3. 保存图片:     {save_time:.3f}s")
+                logger.info(f"  4. 其他开销:     {other_time:.3f}s")
+            
+            logger.info("-" * 60)
+            logger.info(f"📈 总耗时:        {total_time:.3f}s")
+            if total > 0:
+                avg_per_image = (total_time / total) * 1000
+                logger.info(f"📈 平均每张:      {avg_per_image:.1f}ms")
+            if batch_count > 0:
+                avg_batch_time = gpu_inference_time / batch_count
+                logger.info(f"📈 每批平均耗时:  {avg_batch_time:.3f}s")
+        
         async def download_image_async(index, url):
             """异步下载图片"""
             url_str = str(url)
@@ -472,8 +526,11 @@ class RmbgService:
             except Exception as e:
                 return (None, None, index, url_str, str(e))
         
+        # 记录下载开始时间
+        download_start_time = time.time()
         download_tasks = [download_image_async(i, url) for i, url in enumerate(urls, 1)]
         downloaded_images = await asyncio.gather(*download_tasks)
+        download_time = time.time() - download_start_time
         
         valid_images = []
         failed_results = {}
@@ -511,7 +568,13 @@ class RmbgService:
         if use_single_batch:
             try:
                 images_with_info = [(img, size, idx) for img, size, idx, _ in valid_images]
+                
+                # 记录GPU推理开始时间
+                gpu_start_time = time.time()
                 batch_results = await self.process_batch_images(images_with_info)
+                gpu_inference_time += time.time() - gpu_start_time
+                batch_count += 1
+                batch_sizes.append(len(images_with_info))
                 
                 # 并行保存所有图片
                 save_tasks = []
@@ -526,7 +589,10 @@ class RmbgService:
                     )
                     save_tasks.append((index, save_task))
                 
+                # 记录保存开始时间
+                save_start_time = time.time()
                 save_results = await asyncio.gather(*[task for _, task in save_tasks], return_exceptions=True)
+                save_time += time.time() - save_start_time
                 
                 for (index, _), image_url in zip(save_tasks, save_results):
                     if isinstance(image_url, Exception):
@@ -591,6 +657,7 @@ class RmbgService:
                             "batch_elapsed": round(time.time() - batch_start_time, 2)
                         }
                         yield result
+                    print_stats()
                     return
             except Exception as e:
                 # 其他异常，直接返回错误
@@ -611,6 +678,7 @@ class RmbgService:
                         "batch_elapsed": round(time.time() - batch_start_time, 2)
                     }
                     yield result
+                print_stats()
                 return
         
         # 如果一次性处理失败（显存不足）或图片数量太多，使用分批处理
@@ -622,7 +690,13 @@ class RmbgService:
                 
                 try:
                     images_with_info = [(img, size, idx) for img, size, idx, _ in batch_images]
+                    
+                    # 记录GPU推理开始时间
+                    gpu_start_time = time.time()
                     batch_results = await self.process_batch_images(images_with_info)
+                    gpu_inference_time += time.time() - gpu_start_time
+                    batch_count += 1
+                    batch_sizes.append(len(images_with_info))
                     
                     # 并行保存所有图片
                     save_tasks = []
@@ -637,8 +711,11 @@ class RmbgService:
                         )
                         save_tasks.append((index, save_task))
                     
+                    # 记录保存开始时间
+                    save_start_time = time.time()
                     # 并行执行所有保存任务
                     save_results = await asyncio.gather(*[task for _, task in save_tasks], return_exceptions=True)
+                    save_time += time.time() - save_start_time
                     
                     # 按顺序返回结果
                     for (index, _), image_url in zip(save_tasks, save_results):
@@ -693,6 +770,9 @@ class RmbgService:
                             "batch_elapsed": round(time.time() - batch_start_time, 2)
                         }
                         yield result
+        
+        # 输出性能统计信息
+        print_stats()
 
     def is_valid_url(self, url):
         """验证URL是否有效"""