Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

Those are very different questions...

If you want to simply run inference or do QLoRA fine tunes of "the best, largest open source models" eg the llama2-70b models, you can do so with 2 x RTX 3090 24GB (~$600 used), so for about $1200 for the GPUs, 48GB of VRAM (set to PL 300W, so 600W while inferencing) - q4 version of llama2-70b take about 38-40GB of memory + kvcache.

If you want 192GB of VRAM, your cheapest realistic option is probably going to be 4 x A6000's (~$16,000) - you will need to have a chassis that will provide adequate power and cooling (1200W for the GPUs). I'd personally suggest that anyone looking to buy that kind of hardware have a fairly good idea of what they're going to use it for beforehand.

I'm not sure what exactly you're asking about with regards to memory, but for workstations, the Xeon W-3400's have 8 channels of DDR5-4800 (the W5-3425 has a $1200 list price) and the upcoming Threadripper Pro 7000s will likely have similar memory support (or you can get an EPYC 9124 for ~$1200 now if you want 12 channels of DDR5).



Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: