diff --git a/tensordict/functional.py b/tensordict/functional.py
index 2699f36bb..226e55da1 100644
--- a/tensordict/functional.py
+++ b/tensordict/functional.py
@@ -216,7 +216,7 @@ def pad_sequence(
         try:
             item0 = list_of_dicts[0][key]
             if is_non_tensor(item0):
-                out.set(key, torch.stack([d[key] for d in list_of_dicts]))
+                out.set(key, TensorDict.lazy_stack([d[key] for d in list_of_dicts]))
                 continue
             tensor_shape = item0.shape
             pos_pad_dim = (
diff --git a/test/test_tensordict.py b/test/test_tensordict.py
index a77cb11e7..60ba211a9 100644
--- a/test/test_tensordict.py
+++ b/test/test_tensordict.py
@@ -1920,6 +1920,13 @@ def test_pad_sequence_nontensor(self):
         assert (d["a"] == torch.tensor([[1, 1], [2, 0]])).all()
         assert d["b"] == ["asd", "efg"]
 
+    def test_pad_sequence_single_nontensor(self):
+        d1 = TensorDict({"a": torch.tensor([1, 1]), "b": "asd"})
+        d = pad_sequence([d1])
+        assert (d["a"] == torch.tensor([[1, 1]])).all()
+        assert d["b"] == ["asd"]
+        assert isinstance(d.get("b"), NonTensorStack)
+
     def test_pad_sequence_tensorclass_nontensor(self):
         @tensorclass
         class Sample: