[formalsystem]

So this should be referring to w8a8 (weights and activations in 8 bit)

So this is gonna be 8 bit weights, 8 bit activations, group size of 256, symmetric quantization. Not sure how to map this to the GGUF variants because they don't mention how they don't do activation quantization

[imjonse]

Were there comparisons made to AWS, Smoothquant, GPTQ or other non-vanilla PTQ methods? Thanks.

[formalsystem]

Not that I know of for this study, at least for the specific scope torchao we want to make it easier for researchers to create new quantization algorithms in python and have those algorithms run fast and you can see a lot of those algorithms here https://github.com/pytorch/ao/tree/main/torchao/prototype

So for example for AWQ and GPTQ we can accelerate them by using a fast int4 kernel called tinygemm