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  • If I'm reading this right, they didn't actually use the Decisions API, they used GPT-6 Luna. Wouldn't call this a good comparison.
    by itg
  • > In Hard-Decisions, our benchmark of decision models on multi-step logic

      "model": "gpt-6-luna",
      "reasoning_effort": "none",
    
    This article seems to be missing important points regarding how these models are intended to be used. It is my understanding that the Decisions API is designed for quick, single-step logic. We already have a proper Death Star for dispatching the more complex problems.

    I am currently using the Responses API with my clients, which is mandatory to get at non-zero reasoning effort in the latest models. Luna without reasoning turned on might as well be a model from early 2025. This is not how anyone is using this. Responses with 5.6-luna+ and high+ reasoning level feels pretty close to the Star Trek computer experience for me.

    Attempting to recreate the OAI reasoning model capabilities at home seems like a pointless quest now. You will never get the access into the base models that the frontier companies have internally. You will also never have access to an engineering team with that kind of capacity. You must submit to the black box if you want the advertised performance figures.

  • Alan is young, round, and kind, but that doesn't mean he isn't also rough and cold at times, as well. … Young round people who are green are usually blue. … Kind people with rough skin are usually red because it's wind burn. If someone shows that they are red, then they are also showing that they are green. …

    Statement: Alan is not blue.

    A log-probability of −0.00182 is a probability of 99.82%. We asked for five alternatives and got none: Luna put essentially nothing on "true" or "false". And it's wrong. Alan is kind with rough skin, so he's red; red means green; young, round and green means blue. "Alan is not blue" is false, three steps in.

    —————-

    Can someone explain this I got unknown as well. The problem statement includes the word “usually” a few times.

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