this post was submitted on 17 Oct 2026
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Does anyone run their own AI service?

If so,

Which one?

What hardware?

Do you have a way to access it from outside or from a phone?

And, if you're open to sharing, what do you do with it?

I know AI-enabling hardware is insanely expensive right now, but some of the smaller (<32GB) more efficient models (think deepseek- or qwen-based) don't absolutely need specialized hardware to run and perform well enough for many purposes.

I am so aware of the absolutely abysmal privacy practices of basically all AI companies that I'm not comfortable using them to help me with web searches and the such, because there's no way that all this information won't be going into a profile. This makes me want to have my own "helper" service.

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[–] kensand@sopuli.xyz 24 points 1 day ago

Running Qwen 3.8 27B dense on some R9700s, and Qwen 3.8 flash next on dgx sparks. I use it for code gen outside work, including an automated Dev pipeline that rubs on its own. When I did the math comparing to token API pricing of Opus 4.8, it covered its own costs in a few months. With the sparks I get about 40tg/s, 1500pp/s, but can get concurrency up to 5 stably. With the R9700s, I get ~100tg/s, 3000pp/s and can also get up to 5 concurrency.

I access it over wireguard to the network that it is on, and use termux to ssh into a build machine for dev over CLI using https://pi.dev/

I also started building https://fcli.dev/ to make integrations easier; the idea being that LLMs should just implement simple reusable functions instead of repeatedly making complex curl requests to integrate with a service.

I also use LLMs heavily for work; Qwen 3.8 seems almost on par to Opus 4.8 IMO. I also don't have to worry about token costs, and it often responds faster than Claude would because there usually isn't a queue on my machines. At this point, I wouldn't complain if my work provided me 2x B6000 instead of a Claude subscription; I'd still be able to get all my work done.