diff --git a/python/sglang/srt/managers/schedule_batch.py b/python/sglang/srt/managers/schedule_batch.py
index 1abd67424..4d67ce6ff 100644
--- a/python/sglang/srt/managers/schedule_batch.py
+++ b/python/sglang/srt/managers/schedule_batch.py
@@ -133,6 +133,7 @@ class ImageInputs:
     aspect_ratio_mask: Optional[List[torch.Tensor]] = None
     # QWen2-VL related
     image_grid_thws: List[Tuple[int, int, int]] = None
+    mrope_position_delta: Optional[torch.Tensor] = None
 
     @staticmethod
     def from_dict(obj, vocab_size):
@@ -251,9 +252,6 @@ class Req:
         # The number of cached tokens, that were already cached in the KV cache
         self.cached_tokens = 0
 
-        # For Qwen2-VL
-        self.mrope_position_delta = []  # use mutable object
-
     # whether request reached finished condition
     def finished(self) -> bool:
         return self.finished_reason is not None
@@ -983,8 +981,6 @@ class ScheduleBatch:
         global bid
         bid += 1
 
-        mrope_positions_delta = [req.mrope_position_delta for req in self.reqs]
-
         return ModelWorkerBatch(
             bid=bid,
             forward_mode=self.forward_mode,
@@ -1007,7 +1003,6 @@ class ScheduleBatch:
             encoder_out_cache_loc=self.encoder_out_cache_loc,
             lora_paths=[req.lora_path for req in self.reqs],
             sampling_info=self.sampling_info,
-            mrope_positions_delta=mrope_positions_delta,
         )
 
     def copy(self):
@@ -1074,9 +1069,6 @@ class ModelWorkerBatch:
     # Sampling info
     sampling_info: SamplingBatchInfo
 
-    # For Qwen2-VL
-    mrope_positions_delta: List[List[int]]
-
     def copy(self):
         return dataclasses.replace(self, sampling_info=self.sampling_info.copy())
 
diff --git a/python/sglang/srt/model_executor/forward_batch_info.py b/python/sglang/srt/model_executor/forward_batch_info.py
index d314af944..8bd5f197a 100644
--- a/python/sglang/srt/model_executor/forward_batch_info.py
+++ b/python/sglang/srt/model_executor/forward_batch_info.py
@@ -136,8 +136,13 @@ class ForwardBatch:
         mrope_positions_list = [None] * self.seq_lens.shape[0]
         if self.forward_mode.is_decode():
             for i, _ in enumerate(mrope_positions_list):
+                mrope_position_delta = (
+                    0
+                    if batch.image_inputs[i] is None
+                    else batch.image_inputs[i].mrope_position_delta
+                )
                 mrope_positions_list[i] = MRotaryEmbedding.get_next_input_positions(
-                    batch.mrope_positions_delta[i][0],
+                    mrope_position_delta,
                     int(self.seq_lens[i]) - 1,
                     int(self.seq_lens[i]),
                 )
@@ -159,7 +164,6 @@ class ForwardBatch:
                             )
                         ]
                     ] * 3
-                    mrope_position_delta = 0
                 else:
                     # TODO: current qwen2-vl do not support radix cache since mrope position calculation
                     mrope_positions, mrope_position_delta = (
@@ -173,8 +177,8 @@ class ForwardBatch:
                             context_len=0,
                         )
                     )
+                    batch.image_inputs[i].mrope_position_delta = mrope_position_delta
                 mrope_positions_list[i] = mrope_positions
-                batch.mrope_positions_delta[i].append(mrope_position_delta)
 
         self.mrope_positions = torch.concat(
             [torch.tensor(pos, device=device) for pos in mrope_positions_list],
diff --git a/python/sglang/srt/models/qwen2_vl.py b/python/sglang/srt/models/qwen2_vl.py
index 4e4fef3dc..cedaa8e5c 100644
--- a/python/sglang/srt/models/qwen2_vl.py
+++ b/python/sglang/srt/models/qwen2_vl.py
@@ -649,8 +649,6 @@ class Qwen2VLForConditionalGeneration(nn.Module):
                     ]
                     image_embeds_offset += num_image_tokens
 
-            input_ids = None
-
         hidden_states = self.model(
             input_ids=input_ids,
             positions=positions,