The internal order of operations will most likely be different and e.g. a simple sum can also yield these floating point precision errors:
filters = torch.randn((1, 2, 2, 2))
res1 = filters.sum()
res2 = filters.sum(0).sum(0).sum(0).sum(0)
print(res1 - res2)
> tensor(2.3842e-07)