Sure, but 16-bit float is pretty primitive compression, as it does not exploit any redundancy in the input. zfp groups numbers together in chunks, which means t

Sure, but 16-bit float is pretty primitive compression, as it does not exploit any redundancy in the input. zfp groups numbers together in chunks, which means that correlated numbers can be represented more precisely. Its algorithm is described here: https://zfp.readthedocs.io/en/release1.0.0/algorithm.html#lossy-compression https://zfp.readthedocs.io/en/release1.0.0/algorithm.html#lo... I would like to see if the zfp can be applied to something like Stable Diffusion (or other ML models) and give better results than regular floats at the same size.