diff --git a/test/test_utils.py b/test/test_utils.py
index 0e77388f13..3d316accc4 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -342,6 +342,91 @@ def fake_linear(func, types, args, kwargs):
             counter["calls"], 2, "Expected fake_linear to be called via aten.t.default"
         )
 
+    def test_subclassing(self):
+        class Parent(TorchAOBaseTensor):
+            tensor_data_names = ["qdata"]
+            tensor_attribute_names = ["attr"]
+
+        Parent._ATEN_OP_TABLE[Parent]["op_parent"] = "parent_impl"
+        Parent._TORCH_FN_TABLE[Parent]["fn_parent"] = "parent_fn_impl"
+
+        class Child(Parent):
+            tensor_data_names = ["qdata"]
+            tensor_attribute_names = ["attr"]
+
+        # ensure child has copied parent ops
+        self.assertEqual(Child._ATEN_OP_TABLE[Child]["op_parent"], "parent_impl")
+        self.assertEqual(Child._TORCH_FN_TABLE[Child]["fn_parent"], "parent_fn_impl")
+
+        # ensure the top-level dicts are distinct (not inherited)
+        self.assertIsNot(Parent._ATEN_OP_TABLE, Child._ATEN_OP_TABLE)
+        self.assertIsNot(Parent._TORCH_FN_TABLE, Child._TORCH_FN_TABLE)
+
+        # change the parent's op after subclass creation — should not leak
+        Parent._ATEN_OP_TABLE[Parent]["new_op"] = "added_later"
+        self.assertNotIn("new_op", Child._ATEN_OP_TABLE[Child])
+
+    def test_subclassing_with_real_op(self):
+        counter = {"calls": 0}
+
+        class Parent(TorchAOBaseTensor):
+            tensor_data_names = ["qdata"]
+            tensor_attribute_names = ["attr"]
+
+            def __new__(cls, qdata, attr):
+                r = torch.Tensor._make_wrapper_subclass(cls, qdata.shape)
+                r.qdata = qdata
+                r.attr = attr
+                return r
+
+            def __init__(self, qdata, attr):
+                pass
+
+        # Real op implementation
+        @Parent.implements([torch.ops.aten.cat.default])
+        def _cat_op(func, types, args, kwargs):
+            counter["calls"] += 1
+
+        class Child(Parent):
+            tensor_data_names = ["qdata"]
+            tensor_attribute_names = ["attr"]
+
+        # Table checks
+        self.assertIn(torch.ops.aten.cat.default, Parent._ATEN_OP_TABLE[Parent])
+        self.assertIn(torch.ops.aten.cat.default, Child._ATEN_OP_TABLE[Child])
+
+        # Ensure child table is distinct
+        self.assertIsNot(Parent._ATEN_OP_TABLE, Child._ATEN_OP_TABLE)
+
+        # calling the op through the child tensor
+        t1 = torch.randn(2, 3)
+        t2 = torch.randn(2, 3)
+        child_tensor1 = Child(t1, "a")
+        child_tensor2 = Child(t2, "b")
+
+        torch.ops.aten.cat.default([child_tensor1, child_tensor2], 0)
+
+        self.assertEqual(counter["calls"], 1)
+
+    def test_multiple_inheritance(self):
+        class A(TorchAOBaseTensor):
+            tensor_data_names = ["a"]
+            tensor_attribute_names = ["b"]
+
+        class B(TorchAOBaseTensor):
+            tensor_data_names = ["a"]
+            tensor_attribute_names = ["b"]
+
+        A._ATEN_OP_TABLE[A]["shared"] = "from_a"
+        B._ATEN_OP_TABLE[B]["shared"] = "from_b"
+
+        class C(A, B):
+            tensor_data_names = ["a"]
+            tensor_attribute_names = ["b"]
+
+        # C(A, B) should inherit from A then B, so B wins
+        self.assertEqual(C._ATEN_OP_TABLE[C]["shared"], "from_b")
+
 
 if __name__ == "__main__":
     unittest.main()
diff --git a/torchao/utils.py b/torchao/utils.py
index 875383a064..38dd0f2949 100644
--- a/torchao/utils.py
+++ b/torchao/utils.py
@@ -828,9 +828,9 @@ def __init__(
 
     @classmethod
     def __init_subclass__(cls, **kwargs):
-        if not hasattr(cls, "_ATEN_OP_TABLE"):
+        if "_ATEN_OP_TABLE" not in cls.__dict__:
             cls._ATEN_OP_TABLE = {}
-        if not hasattr(cls, "_TORCH_FN_TABLE"):
+        if "_TORCH_FN_TABLE" not in cls.__dict__:
             cls._TORCH_FN_TABLE = {}
         if cls not in cls._ATEN_OP_TABLE:
             cls._ATEN_OP_TABLE[cls] = {}
@@ -846,10 +846,14 @@ def __init_subclass__(cls, **kwargs):
         # inherit the torch function and dispatch implementations from direct parent classes
         # e.g. for `class C(B, A)`, C.__bases__ == (B, A)
         for parent in cls.__bases__:
-            if hasattr(cls, "_ATEN_OP_TABLE") and parent in cls._ATEN_OP_TABLE:
-                cls._ATEN_OP_TABLE[cls].update(cls._ATEN_OP_TABLE[parent])
-            if hasattr(cls, "_TORCH_FN_TABLE") and parent in cls._TORCH_FN_TABLE:
-                cls._TORCH_FN_TABLE[cls].update(cls._TORCH_FN_TABLE[parent])
+            parent_aten_table = getattr(parent, "_ATEN_OP_TABLE", None)
+            if parent_aten_table and parent in parent_aten_table:
+                # shallow-copy parent's per-class op mapping into child's per-class mapping
+                cls._ATEN_OP_TABLE[cls].update(parent_aten_table[parent])
+
+            parent_torch_table = getattr(parent, "_TORCH_FN_TABLE", None)
+            if parent_torch_table and parent in parent_torch_table:
+                cls._TORCH_FN_TABLE[cls].update(parent_torch_table[parent])
 
     implements = classmethod(_implements)
     implements_torch_function = classmethod(_implements_torch_function)