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.

  • PetteriPano@lemmy.worldEnglish
    0·
    13 days ago

    Yes, were all on c/LocalLLaMa

    I’m running qwen3.8-next-flash on a rx7900xtx plus 128gb of ram. It serves my hermes agent. I direct it through matrix. I also forward an endpoint to my VPS to use for anything. Mostly opencode.

  • LewdLemon@sh.itjust.worksEnglish
    0·
    13 days ago

    I’m self-hosting immich (with ML-based facial recognition, semantic search and OCR) and psiTTSa, an offline text-to-speech engine.

    (Prob not the answer you were looking for, but a reminder that “AI” is more than just LLMs.)

    • N0x0n@lemmy.mlEnglish
      0·
      13 days ago

      Does Immich sell/use/keep your ML-based FR? Or is this totally local a never leaves your instance?

      That was always the question that bordered me… I run Leeche its a very simple and minimal photo album service and I really like it ! But my family want something that’s more like immich but I’m very cautious about what i’m selfhosting and something that collects data points on my behalf is a no-go !

      • LewdLemon@sh.itjust.worksEnglish
        1·
        13 days ago

        Immich is entirely free and open-source software and got a grant from the FUTO Foundation, which is fiercely pro privacy. As such, it does not engage in any data sharing. Development is financed through the grant and purchases of the server licence (I got one; it’s ridiculously good software).

  • hoshikarakitaridia@lemmy.worldEnglish
    0·
    13 days ago
    • Qwen3.6 35b a3b Q4_K_M running on llama.cpp
    • Open-WebUI as a frontend
    • integrations with an embedding model and searxng & crawl4ai
    • doing lots of different stuff with it, asking basic stupid questions, recipes, tech stuff, etc
      • hoshikarakitaridia@lemmy.worldEnglish
        1·
        13 days ago

        1070ti and some hexacore something cpu that’s alright with around 24gb ddr4, I think one of the slower speeds. I also got a faster PC with another llama.cpp instance and I vibe coded a quick and dirty proxy which I can use to switch between the different backends. It’s genuinely useful because I got code editors but also my Open-WebUI using it.

        Sounds elaborate but generally it’s all pretty primitive.

        Also fyi long preloading steps because my vram is obv not good enough to hold the full model and kv cache and stuff, generation at about 15t/s tops.

        My experience is right now we’re at the stage where it’s a good assistant but not great for actually taking over bigger tasks completely.

        Am looking forward to:

        • experimenting with existing non-uniform quants; I believe those quants are the next step to more bang for your buck on those low-grade consumer rigs
        • hoping for new kinds of quants to come out and be more widely adopted
        • maybe a more universal or consistent harness that is less prone to broken tool-calls etc.
        • better models, specifically a new version for 35b a3b.