Haha I'm on an Mac Studio with an M1 Ultra, 64gb ram. I bought it when it first came out, it just happens to be good for local LLMs. I have to use a smaller quant of Laguna S though (I think 4-bit? Not at my machine to check), as 8-bit and full size definitely don't fit in the 64gb I have.
brb, going to see if 2nd hand mac studios are available!
Yeah, a good rule of thumb is that the weights take up ~100% of the size of the model, so 100B bytes (8-bit quant) would be, well, 100GB and a 4-bit quant would be half that.
I don't know if that's, well, a rule of thumb, it might be, well, straight multiplication.
Oh, that is a useful rule to know! Thanks!
That's not exactly the math. Theres also vram needed for context. I operate several 72-128 GB machines and the larger the context the slower they go.
And the context takes space +kv cache. KV cache drives usefulness as your context grows, it needs to pull the kv cache.
Simplified, the context has to be run on every turn, so the KV cache supplies the processed tokens, so it just needs the new inpute.