diff --git a/deepmd/pt/utils/dataloader.py b/deepmd/pt/utils/dataloader.py
index ec1aa68128..1f09f41320 100644
--- a/deepmd/pt/utils/dataloader.py
+++ b/deepmd/pt/utils/dataloader.py
@@ -241,15 +241,67 @@ def __getitem__(self, idx):
                 batch = next(self.iters[idx])
         else:
             try:
+                # For binding datasets, we need to ensure all subsystems load the same frame
+                # We'll get data from the first dataset (e.g. complex) first
+                first_key = self.part_key[0]
                 batch = {}
-                for kk in self.part_key:
-                    batch[kk] = next(self.iters[kk][idx])
+                
+                # Get the complex data first, which maintains its original randomness
+                # The random selection comes from the sampler configured in the DataLoader
+                first_key_data = next(self.iters[first_key][idx])
+                batch[first_key] = first_key_data
+                
+                # Now, ensure other subsystems use the same frame indices
+                if 'fid' in first_key_data:
+                    # Get the frame indices from the complex data
+                    frame_indices = first_key_data['fid']
+                    
+                    # For each other subsystem, get the same frames
+                    for kk in self.part_key[1:]:
+                        sub_batch = []
+                        # Each batch may contain multiple frames
+                        # We need to match each frame individually
+                        for i, frame_idx in enumerate(frame_indices):
+                            # Use the dataset's __getitem__ method to get the exact frame
+                            # This ensures we always get the matching frame
+                            frame = self.systems[kk][idx][frame_idx]
+                            sub_batch.append(frame)
+                        
+                        # Collate the selected frames into a batch
+                        batch[kk] = collate_batch(sub_batch)
+                else:
+                    # Fallback for cases where fid is not available
+                    # Use the original method which may have synchronization issues
+                    log.warning("Frame IDs not available, synchronization between subsystems may be imperfect")
+                    for kk in self.part_key[1:]:
+                        batch[kk] = next(self.iters[kk][idx])
             except StopIteration:
+                # If complex iterator is exhausted, reset all iterators
                 for kk in self.part_key:
                     self.iters[kk][idx] = iter(self.dataloaders[kk][idx])
+                
+                # Try again with reset iterators
+                first_key = self.part_key[0]
                 batch = {}
-                for kk in self.part_key:
-                    batch[kk] = next(self.iters[kk][idx])
+                first_key_data = next(self.iters[first_key][idx])
+                batch[first_key] = first_key_data
+                
+                # Same logic as above for getting matching frames
+                if 'fid' in first_key_data:
+                    frame_indices = first_key_data['fid']
+                    
+                    for kk in self.part_key[1:]:
+                        sub_batch = []
+                        for i, frame_idx in enumerate(frame_indices):
+                            frame = self.systems[kk][idx][frame_idx]
+                            sub_batch.append(frame)
+                        
+                        batch[kk] = collate_batch(sub_batch)
+                else:
+                    log.warning("Frame IDs not available, synchronization between subsystems may be imperfect")
+                    for kk in self.part_key[1:]:
+                        batch[kk] = next(self.iters[kk][idx])
+                
         batch["sid"] = idx
         return batch