diff --git a/torch/_meta_registrations.py b/torch/_meta_registrations.py
index b3ccc4350eb..5cdc6ea1863 100644
--- a/torch/_meta_registrations.py
+++ b/torch/_meta_registrations.py
@@ -2658,6 +2658,25 @@ if torch._C._has_mkldnn:
             memory_format=memory_format,
         )
 
+    @register_meta(torch.ops.quantized.int4mm_packed_weight_cpu)
+    def meta_int4mm_packed_weight_cpu(x, w, q_group_size, q_scale_and_zeros):
+        torch._check(x.dim() == 2, f"x must be a 2D tensor, got {x.dim()}D")
+        torch._check(w.dim() == 2, f"w must be a 2D tensor, got {w.dim()}D")
+        torch._check(
+            x.dtype in [torch.float32, torch.float16, torch.bfloat16],
+            f"expected x to be f32/f16/bf16, got {x.dtype}",
+        )
+        torch._check(w.dtype == torch.uint8, f"expected w to be uint8, got {w.dtype}")
+        torch._check(
+            q_group_size.dtype == torch.int64,
+            f"q_group_size must be int64, got {q_group_size.dtype}",
+        )
+        torch._check(
+            q_scale_and_zeros.dtype == x.dtype,
+            f"q_scale_and_zeros must have the same dtype as x, got {q_scale_and_zeros.dtype}",
+        )
+        return x.new_empty(x.size(0), w.size(0), dtype=x.dtype)
+
 
 # from check_dim_size() in aten/src/ATen/TensorUtils.cpp.
 def check_dim_size(tensor, dim, dim_size, size):
@@ -3774,26 +3793,6 @@ def meta__weight_int8pack_mm(x, w, q_scales):
     return x.new_empty(x.size(0), w.size(0), dtype=x.dtype)
 
 
-@register_meta([torch.ops.quantized.int4mm_packed_weight_cpu])
-def meta_int4mm_packed_weight_cpu(x, w, q_group_size, q_scale_and_zeros):
-    torch._check(x.dim() == 2, f"x must be a 2D tensor, got {x.dim()}D")
-    torch._check(w.dim() == 2, f"w must be a 2D tensor, got {w.dim()}D")
-    torch._check(
-        x.dtype in [torch.float32, torch.float16, torch.bfloat16],
-        f"expected x to be f32/f16/bf16, got {x.dtype}",
-    )
-    torch._check(w.dtype == torch.uint8, f"expected w to be uint8, got {w.dtype}")
-    torch._check(
-        q_group_size.dtype == torch.int64,
-        f"q_group_size must be int64, got {q_group_size.dtype}",
-    )
-    torch._check(
-        q_scale_and_zeros.dtype == x.dtype,
-        f"q_scale_and_zeros must have the same dtype as x, got {q_scale_and_zeros.dtype}",
-    )
-    return x.new_empty(x.size(0), w.size(0), dtype=x.dtype)
-
-
 @register_meta(aten._cdist_forward.default)
 def meta_cdist_forward(x1, x2, p, compute_mode):
     torch._check(