diff --git a/thunder/tests/test_tensor_subclass.py b/thunder/tests/test_tensor_subclass.py
index 6459fdec21..de040f5208 100644
--- a/thunder/tests/test_tensor_subclass.py
+++ b/thunder/tests/test_tensor_subclass.py
@@ -4,6 +4,7 @@
 import torch
 
 import thunder
+from thunder.tests.framework import instantiate, NOTHING
 from thunder.tests.make_tensor import make_tensor
 
 if TYPE_CHECKING:
@@ -87,20 +88,35 @@ def maybe_unwrap_and_scale(t: ScaleTensorSubclass | Any):
             return ScaleTensorSubclass(out, scales[0])
 
 
-def test_func_of_subclass_ctor_wrapper():
+@instantiate(
+    dtypes=(thunder.core.dtypes.float32,),
+)
+def test_func_of_subclass_ctor_wrapper(executor, device, _):
 
     def f(x: torch.Tensor, scale: torch.Tensor) -> ScaleTensorSubclass:
-        return ScaleTensorSubclass(x, scale)
+        y = ScaleTensorSubclass(x, scale)
+        return y
+
+    jitted = executor.make_callable(f)
 
-    device = torch.device("cuda")
     dtype = torch.float32
     shape = (2, 2)
     x = make_tensor(shape, device=device, dtype=dtype)
     scale = make_tensor((), device=device, dtype=dtype)
 
-    jitted = thunder.jit(f)
+    expected = f(x, scale)
+    actual = jitted(x, scale)
+    torch.testing.assert_close((expected._x, expected._scale), (actual._x, actual._scale))
+
+    def f(x: torch.Tensor, scale: torch.Tensor):
+        y = ScaleTensorSubclass(x, scale)
+        z = ScaleTensorSubclass(y._x, y._scale)
+        return z
+
+    jitted = executor.make_callable(f)
 
     expected = f(x, scale)
     actual = jitted(x, scale)
-    assert type(expected) is type(actual)
     torch.testing.assert_close((expected._x, expected._scale), (actual._x, actual._scale))
+    print(thunder.last_traces(jitted)[0])
+    print(thunder.last_traces(jitted)[-1])