I would advise getting as much RAM as you possibly can. You can't upgrade later, so get as much as you can afford.

Mine is 64GB, and my memory pressure goes into the red when running a quantized 70B model with a dozen Chrome tabs open.

I use several LLM models locally for chat UIs and IDE autocompletions like copilot (continue.dev).

Between Teams, Chrome, VS Code, Outlook, and now LLMs my RAM usage sits around 20-22GB. 16GB will be a bottleneck to utility.

I've run LLMs and some of the various image models on my M1 Studio 32GB without issue. Not as fast as my old 3080 card, but considering the Mac all in has about a 5th the power draw, it's a lot closer than I expected. I'm not sure of the exact details but there is clearly some secret sauce that allows it to leverage the onboard NN hardware.

Mistral is _very_ small when quantized.

I’d still go with 16gbs

Looks super cool, though it seems to be missing a good chunk of features, like the ability to change the prompt format. (Just installed it myself to check out all the options.) All the other missing stuff I can see though is stuff that LM Studio doesn't have either (such as a notebook mode). If it has a good chat mode then that's good enough for most!