>>3027238Not that anon, but here's my understanding:
That being said GPU layers are for performance, it's basically how many decisions can happen at once. Turning it down would impact the response time a lot, but shouldn't impact the end quality of the output much. If you're willing to wait you could turn them down to give more VRAM for other things.
Context matters most for the AI remembering things, so again depending on what you're doing you could turn it down if you don't need the AI to remember things that happened in previous messages. A workaround for context is to periodically summarize messages so the summary is in context even if the original messages are forgotten. Like if the AI is only remembering 2048 characters that's basically a max length 4chan post, every time you passed that limit it would start forgetting previous things but you can tell it to summarize what it remembers or give it a condensed summary yourself and it'll know that.
Since the Quant impacts the actual neural network of the model that's probably the most important for actual quality responses. When you go down to lower quants you're basically making the model dumber. Even if you got fast responses with lots of gpu agents and the AI remembered everything with a huge context size if it's giving you dumbed down responses it may still not be what you want.
tl:dr; I'd say most important is the model/Quant, you want as big a one as possible. Then context size next, then GPU agents. But depending on your patience and such you could balance out gpu agents and context size (speed and memory basically) for whatever you like best.
Hope that helps!
