> had better results with the 20b model, over the 120b model

The difference of quality and accuracy of the responses between the two is vastly different though, if tok/s isn't your biggest priority, especially when using reasoning_effort "high". 20B works great for small-ish text summarization and title generation, but for even moderately difficult programming tasks, 20B fails repeatedly while 120B gets it right on the first try.

But the 120b model has just as bad if not worse formatting issues, compared to the 20b one. For simple refactorings, or chatting about possible solutions i actually feel teh 20b halucinates less than the 120b, even if it is less competent. Migth also be because of 120b not liking being in q8, or not being properly deployed.

> But the 120b model has just as bad if not worse formatting issues, compared to the 20b one

What runtime/tools are you using? Haven't been my experience at all, but I've also mostly used it via llama.cpp and my own "coding agent". It was slightly tricky to get the Harmony parsing in place and working correct, but once that's in place, I haven't seen any formatting issues at all?

The 20B is definitely worse than 120B for me in every case and scenario, but it is a lot faster. Are you running the "native" MXFP4 weights or something else? That would have a drastic impact on the quality of responses you get.

Edit:

> Migth also be because of 120b not liking being in q8

Yeah, that's definitely the issue, I wouldn't use either without letting them be MXFP4.