Do you host your own ML / AI / LLM? What do you use, and what do you use it for?

  • robber@lemmy.ml
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    1 day ago

    Given the 27b is a dense model, I think the numbers are quite ok. Curious about the quant tho.

    The cool thing about the strix is its large unified memory, but it lacks memory bandwith for compute intensive workloads. Something like Qwen3.5-122b MoE with only like 12b active parameters might run at twice the speed if it fits the configuration.

    • Domi@lemmy.secnd.me
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      22 hours ago

      Curious about the quant tho.

      Q8 from unsloth.

      Something like Qwen3.5-122b

      My go to model for knowledge. Definitely much faster at Q5 but it lacks the tool calling quality of the Qwen3.6 models. Really hoping we see a Qwen3.6-122b soon…

      • robber@lemmy.ml
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        8 hours ago

        In case you missed the Ornith 1.0 release (Qwen and Gemma RL finetunes for agentic / coding workloads), they look interesting to bridge the gap until we see larger 3.6 models or a 3.7 release. I didn’t test them yet but according to benchmarks, the 35b MoE seems to be more or less on par with Qwen3.6 27b dense, while ofc a lot faster.

    • SuspiciousCarrot78@aussie.zoneOP
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      1 day ago

      Yeah. Though I think theres a new strix out soon (Medusa? Gorgon? Something like that).

      Its a bit like my P40. On paper, it has 24GB. But that 24gb is capped at 400GB/s and the ai compute is what…Pascal era?

      AI = Good, fast, cheap - pick 2

      • robber@lemmy.ml
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        8 hours ago

        Well compared to the strix, 400GB/s is not that bad, I think with fast system RAM and expert offloading you could squeeze quite something out of it when running stuff in the 100b-a10b regions.

        Your bigger problem is going to be future software support.