The double-precision number probably best represents the generational improvement.

The 20x 32-bit floating point improvement is probably achieved by comparing doing full FP32 calculations on the previous generation vs doing TF32 calculations on Ampere. This would not be an apple-to-apple comparison as the TF32 result is less precise.

That said, it is probably not terribly important for deep learning at least, given the success of BF16.