Super-intelligent small models vs. super-efficient large models.

Reddit r/LocalLLaMA News

Summary

The article discusses the debate between small, highly capable local LLMs and large models optimized for efficiency, comparing performance on CPU using MiniCPM5 2B and MoE Qwen3.6 35B.

What do you think is the future of local LLMs? This technology is booming and keeps growing; eventually, models will become both smarter and more optimized. Do you think the future of optimization lies in very small yet highly capable models? Or in optimizing the performance of very large models? I’ve been running several tests lately using only the CPU. I tried MiniCPM5 2B Q8; it runs at about 6 t/s without vision but makes a lot of mistakes... It felt pointless compared to the MoE Qwen3.6 35B Q2_XXS, which runs at 3 t/s but delivers much more impressive results. In my last post, I showed how Qwen3.6 35B is usable even without a GPU: https://www.reddit.com/r/LocalLLaMA/comments/1w655he/qwen36_35b_q2_xxs_being_gpu_poor_in_2026_is_not/
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