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  • Beats Opus 4.5 on reasoning you say?

    Prompt: If A goes to B who then goes to C, can A send something to C?

    Response:

    We need to interpret best. The phrase "If A goes to B who then goes to C, can A send something to C?" could be a puzzle about the concept of sending something (like passing a ball) and the relationships.

    Scenario: A gives something to B, and B passes it on to C. Question: Can A also give the same thing to C? Answer: Only if A can obtain a second copy (e.g., the thing was duplicated). Otherwise, after handing it to B, A no longer holds it and cannot “send” it unless a copy exists.

    [Lots of other unnecessary commentary and "scenarios" that make even lesser sense]

    by achrono
  • I tried generating the classic pelican svg, but it failed horribly just showing me a rectangle and a black circle...
    by aero2146
  • Having some success while testing this model out as a replacement for GPT-5 nano in source code security review. Running on RTX 3090 (24 GB VRAM) via vLLM. It's not great on structured output (as noted in the model card) but I'm working around that in my harness.
    by noperator
  • The interesting thing about models this small is they should be able to be put on a single Taalas chip (the HC1 already runs a Llama 3.1 8B model). We're already at the point where half-decent reasoning could be run on an ASIC (and at mind-boggling speeds).
    by NotSuspicious
  • Note that these are Python-only results, the model will not do as well with other languages.

    I'm glad to see more domain-focused SLMs, we need more of them! A programming focused MoE should work well across many languages.

    by gslepak
  • Looks like we are seeing small but mighty model breakthroughs, outpacing the pure capital firepower of SOTA providers. I love rooting for the little guy, but is it too soon to call it? To play devils advocate, could it just be the benchmarks are not efficient enough to capture success of real developer workflows?
    by rbbydotdev
  • There is some base level of intelligence any model needs to be useful, even in narrow tasks.

    Could you teach a 5 year old to drive a car? A 10 year old? A 12 year old? To drive a car requires being able to read, to have judgement about ice or rainy conditions, to anticipate a child running after a ball. By the time a human in in their mid teens they have acquired the base knowledge...

    Small models need to have enough base knowledge to be able to be good enough -- even in a seemingly narrow regime. Where is that? Obviously they don't need all the obscure knowledge of a frontier model but there is some base level which is probably more than it would first seem.

    by deftio
  • Am I right in thinking this is a tiny model which has been trained well to reason, and that's it? Makes me think of a smart person who doesn't know anything about a given topic, but with the right tools will go and research the heck out of it. I really like the sound of this... why have models train on learning anything when you can just train them how to learn and let them get on with it from something as small as a Pi Zero and an internet connection.
    by secretslol

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