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Shapelearn Qwen 3.8 27B (13.1 GB VRAM)

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  1. npodbielski · · focus · HN ↗
    Well I tested it on 7900XTX with the same prompts and their draft model gave me about 30t/s. Their own snippet of code with regular MTP model gave me 60t/s.

    Also model with their draft answered incorrectly. With MTP it answered correctly.

    Question was: "Does MikroTik CRS312-4C+8XG-RM have combo ports?". The answer is Yes.

    1. nvme0n1p1 · · focus · HN ↗
      That's not how you're supposed to use LLMs. You shouldn't expect a tiny little local model to know random facts about every obscure consumer product on earth. That's the job of tool calling. At best a model of this size is just giving you a random guess.

      You're basically saying "I tried rolling these dice one time, the green dice rolled a 6 and the blue dice rolled a 1, so green dice are better"

      1. serf · · focus · HN ↗
        agreed. a niche knowledge callout is about the worst benchmark one can give a smaller model.

        smaller models are attempting to distill the useful methodologies, not the license plate number of an obscure extras car on Magnum PI.

        that said I wonder if there is a small 'trivia' model out there. Seems like the kinda thing Google would tackle.

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