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It will also help with local inference, making AI without big players possible.

It's already possible. Post-training is vastly more important than model size. (There's bigtime diminishing returns with increasing model size.)

Is there a size cutoff you would say where diminishing returns really kick in?

My experience doesn't disagree, at least. I've been using Qwen for coding locally a bit. It is much better than I thought it would be. But also still falls short in some obvious ways compared to the frontiers.

> Is there a size cutoff you would say where diminishing returns really kick in?

No idea yet. But also it's obvious that making LLMs without MoE is stupid.

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