When you use .data, you get a new Tensor with requires_grad=False, so cloning it won’t involve autograd. So both are equivalent, but there might be a (small) speed difference, I am not sure about that.
Another use case could is when you want to clone/copy a non-parameter Tensor without autograd. You should use .detach() (and not data 125) before cloning:
>>> t = torch.rand(1, requires_grad=True)
>>> t.detach().clone()
tensor([0.4847])