The outputs differ in the used print precision and you will see the same output values using:
a = torch.tensor([1.1])
print(a.item())
> 
1.100000023841858
print(a)
> tensor([1.1000])

torch.set_printoptions(precision=15)
print(a)
> tensor([1.100000023841858])

so it’s unrelated to mixed-precision training.
I think the comparison using the tensor should yield True, as the right-hand side would be transformed to a tensor first and would thus be equal to the left-hand side.
The second comparison uses Python directly, so I guess it might be using float64 values (or even a higher precision?) and might be able to represent the 1.1 value in a different way, such that the comparison fails.