diff --git a/torchao/prototype/mx_formats/mx_ops.py b/torchao/prototype/mx_formats/mx_ops.py
index 1779b0e278..d870698601 100644
--- a/torchao/prototype/mx_formats/mx_ops.py
+++ b/torchao/prototype/mx_formats/mx_ops.py
@@ -311,49 +311,6 @@ def mx_copy_(func, types, args, kwargs):
     )
 
 
-@implements([aten._to_copy.default])
-def autocast_to_copy(func, types, args, kwargs):
-    """Autocast + device movement"""
-    assert isinstance(args[0], MXTensor)
-
-    # Handle dtype parameter
-    dtype = kwargs.pop("dtype", None)
-    if dtype is not None:
-        assert dtype in {
-            torch.float16,
-            torch.bfloat16,
-        }, "Only support floating point conversion for autocast w/ MXTensor"
-
-    # Handle device parameter
-    device = kwargs.pop("device", None)
-    if device is not None:
-        # Apply device change using _apply_fn_to_data
-        tensor = args[0]._apply_fn_to_data(lambda x: func(x, device=device))
-        tensor = return_and_correct_aliasing(func, args, {}, tensor)
-    else:
-        tensor = args[0]
-
-    # Verify no other kwargs remain
-    assert len(kwargs) == 0, "Only support dtype and device kwargs for autocast"
-
-    # If dtype is specified, create a new MXTensor with the requested dtype
-    if dtype is not None:
-        res = MXTensor(
-            tensor.qdata,
-            tensor._scale_e8m0,
-            tensor._elem_dtype,
-            tensor._block_size,
-            dtype,
-            tensor._gemm_kernel_choice,
-            tensor._pack_fp6,
-            tensor.act_quant_kwargs,
-        )
-        return res
-
-    # If only device was changed, return the device-changed tensor
-    return tensor
-
-
 @implements([aten.clone.default])
 def mx_clone(func, types, args, kwargs):
     self = args[0]