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We're NOT business users, we just want to run our own LLM at home.

Given the size of LLMs, this should be possible with just a little bit of extra VRAM.




Exactly, we're just below that sweet spot right now.

For example on 24GB, Llama 30B runs only in 4bit mode and very slowly, but I can imagine a RLHF finetuned 30B or 65B version running in at least 8bit would be actually useful, and you could run it on your own computer easily.


Do you know where the cutoff is? Does 32GB VRAM give us 30B int8 with/without a RLHF layer? I don't think 5090 is going to go straight to 48GB, I'm thinking either 32 or 40GB (if not 24GB).


> For example on 24GB, Llama 30B runs only in 4bit mode and very slowly

why do you think adding vram, but not cores will make it run faster?..


I've been told the 4 bit quantization slows it down, but don't quote me on this since I was unable to benchmark at 8 bit locally

In any case, you're right it might not be as significant, however, the quality of the output increases with 8/16bit, and running 65B is completely impossible on 24GB


It's not impossible, there are several projects which load model layer by layer for execution from the disk or ram, but it will be much slower.


I don't think you understand though, they don't WANT you. They WANT the version of you who makes $150k+ a year and will splurge $5k on a Quadro.

If they had trouble selling stock we would see this niche market get catered to.


That IS me. $5K is not enough to run an LLM at home (beyond the non-functional reduced quantization smaller models).


Ahh yes, looks like I was too generous with my numbers, the new Quadro with 48GB VRAM is $7k, so you probably would need $14k and a Threadripper/Xeon/EPYC workstation because you won't have enough PCIE lanes/RAM/Memory Bandwidth otherwise.

So maybe more accurate is $200k+ a year and $20-30k on a workstation.

I grew up on $20k a year, the numbers in tech. are baffling!




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