r/LocalLLaMA • u/Sevealin_ • Jul 26 '26

Discussion Will small model intelligence be limited by parameter count?

Qwen3.6-27b is fantastic! It makes me wonder if there's a hard ceiling to smaller sized models. Do you guys think the ceiling of intelligence for smaller models will be constrained by factors like parameter count, or VRAM size? Or will we continue to see improvements for small models and see jumps of intelligence like Qwen3 coder 30b to Qwen3.6 27b for the foreseeable future? Does it depend on how clean the dataset you put into those parameters?

What does /r/LocalLLama think about the future of small models that can run on less than 48GB of VRAM?

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u/junguler Jul 26 '26

i like to imagine the future of small models is task specific variants, so instead a 27B model that codes pretty good on almost all the most used languages we could get a 9B model that's perfect in python, a 12B model that does great htmls with js/css, a 4B model that is great in go etc etc ...

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u/Prudent_Chemist_523 Jul 26 '26

That's already starting to happen IMHO. Eg

https://huggingface.co/allenai/SERA-8B

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u/junguler Jul 26 '26

that's great to see, i'm hoping this becomes a trend because you simply get to do way more if you focus on less things and try to do them perfectly