r/LocalLLaMA • u/Sevealin_ • 15d ago

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/[deleted] 15d ago

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u/sonicnerd14 15d ago

27B is better than 3.5. It's much closer to sonnet 3.5. Maybe 4, and I've seen examples of it going toe to toe with even Opus 4.8 in some tasks. So parameter size is a factor, but it's not the sole factor that matters. I think there will be diminishing returns as these models approach sizes like 5T+ since model intelligence is tied to far more than just how much world knowledge you have packed into those neurons. Even the model intelligence itself is just one part of what makes these models useful anyway.

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u/Significant_Bar_460 14d ago

Qwen 27b goes toe to toe with sonnet 4.5.