I cannot reproduce the issue in a recent master build and am able to save a tensor of e.g. 16GB using:
>>> import torch
>>> x = torch.randn(int(4*1024**3), device='cuda')
>>> print(torch.cuda.memory_allocated()/1024**3)
16.0
>>> torch.save(x, 'tmp.pt')
>>> y = torch.load('tmp.pt')
>>> print(y.shape)
torch.Size([4294967296])