Comment by CuriouslyC
2 days ago
We're not gonna see significant model shrinkage until the money tap dries up. Between now and then, we'll see new benchmarks/evals that push the holes in model capabilities in cycles as they saturate each new round.
2 days ago
We're not gonna see significant model shrinkage until the money tap dries up. Between now and then, we'll see new benchmarks/evals that push the holes in model capabilities in cycles as they saturate each new round.
isn't gemini 3 flash already model shrinkage that does well in coding?
Xiaomi, Nvidia Nemotron, Minimax, lots of other smaller ones too. There are massive economic incentives to shrink models because they can be provided faster and at lower cost.
I think even with the money going in, there has to be some revenue supporting that development somewhere. And users are now looking at the cost. I have been using Anthropic Max for most of this year after checking out some of these other models, it is clearly overpriced (I would also say their moat of Claude Code has been breached). And Anthropic's API pricing is completely crazy when you use some of the paradigms that they suggest (agents/commands/etc) i.e. token usage is going up so efficient models are driving growth.
Smaller open-weights models are also improving noticeably (like Qwen3 Coder 30B), the improvements are happening at all sizes.
Devstral Small 24b looks promising as something I want to try fine tuning on DSLs, etc. and then embedding in tooling.
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How much billion parameter model is gemini 3 flash, I can't seem to find info about it online.
> We're not gonna see significant model shrinkage until the money tap dries up.
I'm not sure about that. Microsoft has been doing great work on "1-bit" LLMs, and dropping the memory requirements would significantly cut down on operating costs for the frontier players.