Probably not too far off, but then you’ll probably still want the frontier model because it will be even better.

Unless we are hitting the maxima of what these things are capable of now of course. But there’s not really much indication that this is happening

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woggy 8 hours ago | parent | next [-]

I was thinking about this the other day. If we did a plot of 'model ability' vs 'computational resources' what kind of relationship would we see? Is the improvement due to algorithmic improvements or just more and more hardware?

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chasd00 8 hours ago | parent | next [-]

i don't think adding more hardware does anything except increase performance scaling. I think most improvement gains are made through specialized training (RL) after the base training is done. I suppose more GPU RAM means a larger model is feasible, so in that case more hardware could mean a better model. I get the feeling all the datacenters being proposed are there to either serve the API or create and train various specialized models from a base general one.

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ryoshu 8 hours ago | parent | prev [-]

I think the harnesses are responsible for a lot of recent gains.

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NitpickLawyer 8 hours ago | parent [-]

Not really. A 100 loc "harness" that is basically a llm in a loop with just a "bash" tool is way better today than the best agentic harness of last year.

Check out mini-swe-agent.

	▲	SOLAR_FIELDS 4 hours ago \| parent [-]
		Everyone is currently discovering independently that “Ralph Wigguming” is a thing

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gherkinnn 8 hours ago | parent | prev | next [-]

Opus 4.5 is at a point where it is genuinely helpful. I've got what I want and the bubble may burst for all I care. 640K of RAM ought to be enough for anybody.

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dust42 8 hours ago | parent | prev [-]

I don't get all this frontier stuff. Up to today the best model for coding was DeepSeek-V3-0324. The newer models are getting worse and worse trying to cater for an ever larger audience. Already the absolute suckage of emoticons sprinkled all over the code in order to please lm-arena users. Honestly, who spends his time on lm-arena? And yet it spoils it for everybody. It is a disease.

Same goes for all these overly verbose answers. They are clogging my context window now with irrelevant crap. And being used to a model is often more important for productivity than SOTA frontier mega giga tera.

I have yet to see any frontier model that is proficient in anything but js and react. And often I get better results with a local 30B model running on llama.cpp. And the reason for that is that I can edit the answers of the model too. I can simply kick out all the extra crap of the context and keep it focused. Impossible with SOTA and frontier.