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Comment by andai | Hacker News Reader

Hard to find info but I think the -chat versions of 5.1 and 5.2 (gpt-5.2-chat) are what you're looking for. They might just be an alias for the same model with very low reasoning though. I've seen other providers do the same thing, where they offer a reasoning and non reasoning endpoint. Seems to work well enough.

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They’re not the same, there are (at least) two different tunes per 5.x

For each you can use it as “instant” supposedly without thinking (though these are all exclusively reasoning models) or specify a reasoning amount (low, medium, high, and now xhigh - though if you do g specify it defaults to none) OR you can use the -chat version which is also “no thinking” but in practice performs markedly differently from the regular version with thinking off (not more or less intelligent but has a different style and answering method).

It's weird they don't document this stuff. Like understanding things like tool call latency and time to first token is extremely important in application development.

Humans often answer with fluff like "That's a good question, thanks for asking that, [fluff, fluff, fluff]" to give themselves more breathing room until the first 'token' of their real answer. I wonder if any LLM are doing stuff like that for latency hiding?

I don't think the models are doing this, time to first token is more of a hardware thing. But people writing agents are definitely doing this, particularly in voice it's worth it to use a smaller local llm to handle the acknowledgment before handing it off.

Do humans really do that often?

Coming up with all that fluff would keep my brain busy, meaning there's actually no additional breathing room for thinking about an answer.

People who professionally answer questions do that, yes. Eg politicians or press secretaries for companies, or even just your professor taking questions after a talk.

> Coming up with all that fluff would keep my brain busy, meaning there's actually no additional breathing room for thinking about an answer.

It gets a lot easier with practice: your brain caches a few of the typical fluff routines.

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