this post was submitted on 02 Apr 2025
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Consumer GPUs to run LLMs (lemmy.dbzer0.com)
submitted 3 weeks ago* (last edited 3 weeks ago) by marauding_gibberish142@lemmy.dbzer0.com to c/selfhosted@lemmy.world
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Not sure if this is the right place, if not please let me know.

GPU prices in the US have been a horrific bloodbath with the scalpers recently. So for this discussion, let's keep it to MSRP and the lucky people who actually managed to afford those insane MSRPs + managed to actually find the GPU they wanted.

Which GPU are you using to run what LLMs? How is the performance of the LLMs you have selected? On an average, what size of LLMs are you able to run smoothly on your GPU (7B, 14B, 20-24B etc).

What GPU do you recommend for decent amount of VRAM vs price (MSRP)? If you're using the TOTL RX 7900XTX/4090/5090 with 24+ GB of RAM, comment below with some performance estimations too.

My use-case: code assistants for Terraform + general shell and YAML, plain chat, some image generation. And to be able to still pay rent after spending all my savings on a GPU with a pathetic amount of VRAM (LOOKING AT BOTH OF YOU, BUT ESPECIALLY YOU NVIDIA YOU JERK). I would prefer to have GPUs for under $600 if possible, but I want to also run models like Mistral small so I suppose I don't have a choice but spend a huge sum of money.

Thanks

You can probably tell that I'm not very happy with the current PC consumer market but I decided to post in case we find any gems in the wild.

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[–] umami_wasbi@lemmy.ml 9 points 3 weeks ago* (last edited 3 weeks ago) (1 children)

Using 7900XTX with LMS. Speed are everwhere, driver dependent. With QwQ-32B-Q4_K_M, I got about 20 tok/s, with all VRAM filled. Phi-4 runs at about 30-40 tok/s. I can give more numbers if you can wait for a bit.

If you don't enjoy finding which driver works best, I strongly aginst running AMD for AI workload.

[–] marauding_gibberish142@lemmy.dbzer0.com 4 points 3 weeks ago

I didn't know that. I thought just one ROCM binary to install, run Ollama and that's it. Thanks for the explanation