diff -ruN paddlex_/inference/models/doc_vlm/predictor.py paddlex/inference/models/doc_vlm/predictor.py
--- paddlex_/inference/models/doc_vlm/predictor.py	2026-02-24 20:08:06.590533120 +0800
+++ paddlex/inference/models/doc_vlm/predictor.py	2026-02-24 20:12:07.842533120 +0800
@@ -490,7 +490,7 @@
                         }
                     ],
                     return_future=True,
-                    timeout=600,
+                    timeout=3600,
                     **kwargs,
                 )
                 return future
diff -ruN paddlex_/inference/models/object_detection/predictor.py paddlex/inference/models/object_detection/predictor.py
--- paddlex_/inference/models/object_detection/predictor.py	2026-02-24 20:08:06.622533120 +0800
+++ paddlex/inference/models/object_detection/predictor.py	2026-02-24 20:11:42.570533120 +0800
@@ -34,6 +34,9 @@
 from .result import DetResult
 from .utils import STATIC_SHAPE_MODEL_LIST
 
+import os
+from ais_bench.infer.interface import InferSession
+
 
 class DetPredictor(BasePredictor):
 
@@ -111,6 +114,9 @@
         self.layout_merge_bboxes_mode = layout_merge_bboxes_mode
         self.pre_ops, self.infer, self.post_op = self._build()
 
+        om_path = os.path.join(self.model_dir, f"inference_linux_aarch64.om")
+        self.om_sess = InferSession(0, om_path)
+
     def _build_batch_sampler(self):
         return ImageBatchSampler()
 
@@ -140,7 +146,8 @@
             pre_ops.insert(1, self.build_resize(self.img_size, False, 2))
 
         # build infer
-        infer = self.create_static_infer()
+        # infer = self.create_static_infer()
+        infer = None
 
         # build postprocess op
         post_op = self.build_postprocess()
@@ -231,7 +238,8 @@
         batch_inputs = self.pre_ops[-1](datas)
 
         # do infer
-        batch_preds = self.infer(batch_inputs)
+        # batch_preds = self.infer(batch_inputs)
+        batch_preds = self.om_sess.infer(batch_inputs, mode='dymshape', custom_sizes=100000000)
 
         # process a batch of predictions into a list of single image result
         preds_list = self._format_output(batch_preds)