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Hi! So I'm considering...maybe having an NPU or something similar to be hooked to my proxmox server, which runs in a mini PC. It's a EliteDesk 800 micro form factor. It has a Core i5 8500 CPU, which at the moment of purchase was good enough for live encoding HEVC video on Jellyfin...that was my main concern back then. But I'd like to consider the possibility of hooking maybe some docker instances or other containers to some local-only AI acceleration. Is there any NPU or cheap GPU I could hook on USB to this proxmox server to run? Has it been done before?

Thanks!

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[–] yellowbadbeast@lemmy.blahaj.zone 3 points 1 week ago* (last edited 1 week ago) (2 children)

Any NPU/TPU you can buy is going to be essentially useless for either image diffusion or LLMs. The onboard RAM is both far too small and far too slow (LLM text generation speed relies on RAM speed first and foremost, and both LLMs and image models tend to be, you know, big), and USB isn't nearly fast enough to help with that, not to mention that software support is pretty much nonexistent. You'd be better off upgrading the GPU to a 3060ti 12gb or something.

P.S. A word of advice, consider using something other than Ollama. Llama.cpp in router mode or llama-swap support pretty much all of the functionality that Ollama does without being crap. Ik_llama.cpp is also nice if you have a CPU/Nvidia setup.

If you wanna make the most out of what you've got now, the LFM2.5 series of LLMs are quite good for the small size and fast inference speeds with sizes ranging from 0.2 billion to 8 billion parameters, though their low parameter count means that you'll probably wanna hook them up to some sort of web search or similar since they won't have a ton of general knowledge.

If you have at least 32GB of RAM, Qwen3.6 35B is quite a good general-purpose model that runs faster than its parameter count would suggest.

[–] xSikes@feddit.online 1 points 5 days ago (1 children)

Not sure half of what you said due to I’m just getting started; but you explained that real well that I can follow. I wish I knew what you know. Thanks for sharing.

Happy to help! c:

[–] dan@upvote.au 2 points 1 week ago

I wish more modern TPUs were available for purchase. Google's TPU v8i is very powerful, but you can only rent it via Google Cloud. (that and they're most useful in big clusters, and the pricing for such a cluster is definitely out of reach for anyone that's not running their own data center)