diff --git a/src/transformers/models/pixtral/image_processing_pixtral.py b/src/transformers/models/pixtral/image_processing_pixtral.py
index 9f8a5ede3..69eb7c28e 100644
--- a/src/transformers/models/pixtral/image_processing_pixtral.py
+++ b/src/transformers/models/pixtral/image_processing_pixtral.py
@@ -67,7 +67,7 @@ class BatchMixFeature(BatchFeature):
         def _recursive_to(obj, device, *args, **kwargs):
             # Lists can be nested, so keep digging until we hit tensors
             if isinstance(obj, list):
-                return [_recursive_to(o, *args, **kwargs) for o in obj]
+                return [_recursive_to(o, device, *args, **kwargs) for o in obj]
             # We cast only floating point tensors to avoid issues with tokenizers casting `LongTensor` to `FloatTensor`
             elif isinstance(obj, torch.Tensor) and torch.is_floating_point(obj):
                 # cast and send to device
diff --git a/src/transformers/models/pixtral/processing_pixtral.py b/src/transformers/models/pixtral/processing_pixtral.py
index 4c5bfa844..218c290ae 100644
--- a/src/transformers/models/pixtral/processing_pixtral.py
+++ b/src/transformers/models/pixtral/processing_pixtral.py
@@ -70,7 +70,7 @@ class BatchMixFeature(BatchFeature):
         def _recursive_to(obj, device, *args, **kwargs):
             # Lists can be nested, so keep digging until we hit tensors
             if isinstance(obj, list):
-                return [_recursive_to(o, *args, **kwargs) for o in obj]
+                return [_recursive_to(o, device, *args, **kwargs) for o in obj]
             # We cast only floating point tensors to avoid issues with tokenizers casting `LongTensor` to `FloatTensor`
             elif isinstance(obj, torch.Tensor) and torch.is_floating_point(obj):
                 # cast and send to device