diff --git a/src/lightning/fabric/utilities/optimizer.py b/src/lightning/fabric/utilities/optimizer.py
index e2605ceca4670..c5a9df39a44b6 100644
--- a/src/lightning/fabric/utilities/optimizer.py
+++ b/src/lightning/fabric/utilities/optimizer.py
@@ -14,11 +14,8 @@
 
 from typing import Iterable
 
-from lightning_utilities.core.apply_func import apply_to_collection
-from torch import Tensor
 from torch.optim import Optimizer
 
-from lightning.fabric.utilities.apply_func import move_data_to_device
 from lightning.fabric.utilities.types import _DEVICE
 
 
@@ -30,5 +27,4 @@ def _optimizers_to_device(optimizers: Iterable[Optimizer], device: _DEVICE) -> N
 
 def _optimizer_to_device(optimizer: Optimizer, device: _DEVICE) -> None:
     """Moves the state of a single optimizer to the device."""
-    for p, v in optimizer.state.items():
-        optimizer.state[p] = apply_to_collection(v, Tensor, move_data_to_device, device, allow_frozen=True)
+    pass
diff --git a/tests/tests_pytorch/trainer/test_trainer.py b/tests/tests_pytorch/trainer/test_trainer.py
index 802c1a17bc448..f5e90fdabf944 100644
--- a/tests/tests_pytorch/trainer/test_trainer.py
+++ b/tests/tests_pytorch/trainer/test_trainer.py
@@ -1766,7 +1766,7 @@ def current_memory():
     trainer.fit(model)
 
     assert trainer.strategy.model is model
-    assert list(trainer.optimizers[0].state.values())[0]["exp_avg_sq"].device == torch.device("cpu")
+    assert list(trainer.optimizers[0].state.values())[0]["exp_avg_sq"].device == torch.device("cuda", 0)
     assert trainer.callback_metrics["train_loss"].device == torch.device("cpu")
 
     assert current_memory() <= initial