I have not spent a lot of time running FP16 'full precision' versions of some things, but as the other commenter says, it's not much difference. There's a really wide array of benchmarks and tests from a lot of third parties unrelated to the trainer of the AI models that shows at most a two percent difference in score and capability between BF16 and Q8.

Q8 quant is very minimal fall off in terms of KLD against the lab 16 bit. If you have the memory for BF16 KV-cache (which is usually easier to stomach) then the Q8 is very close. But even Q8 quant model with Q8 KV-cache is very close.

Smaller quants for the model start to fall off but more importantly, smaller KV-cache quants fall off much faster so avoid less than Q8 there.