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Defining what "coding" means now, and how quickly we fall off the capability cliff seems increasingly important.

Today my "coding" sessions often enough begin with real life problems, where I discuss domain or inter-domain things, ranging from business, economics, psychology, etc. Being able to do all of that with one model is something I am willing to pay a premium for.

Of course not having to pay the premium, because the routing is smart or whatever, would be great. I just don't want to have to think about it.

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> Today my "coding" sessions often enough begin with real life problems

intuition is that your sessions consists of 10% of domain related reasoning, and 90% of code plumbing. Those 90% could be moved to cheap and efficient specialized and focused model.

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Qwen was doing something like this with their coder models. But alas, they seem not to be releasing those anymore. Last one was Qwen3-coder-next.
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Its crazy that OpenAI and Anthropic themselves aren't doing that. No attempts at reducing inference cost for code as far as I know from them.
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OpenAI do have codex models, which are half the price. I haven't used them enough to comment on the quality though.

I remember them saying a few years ago that, they didn't think it was worth specializing models for code, because their general purpose models kept beating them. I guess they changed their mind? Since they did start making codex models again.

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They also stopped making them again.
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I use this model. It's pretty good but not Opus 4.8 or Fable levels obviously. I'm really hoping we get more models like it (and better) soon. I run it locally and it's great that way.
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Qwen3-coder-next is very usable. But I don't think it's as good as Qwen3.6-27B (though it does run faster on my hardware). It would be great if we could get a Qwen3.7-coder, but I'm not going to hold my breath.
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