Since I like having more than one local LLM to switch between when analysing tricky development issues I decided to try out this new MoE model today. It's a 30B A3B which means it's basically a drop-in replacement for Qwen 3.6 35B A3B with suitable llama.cpp parameters the same. On their own published benchmark metrics it's supposed to be slightly worse than Qwen, but so far it's not something I've noticed. It's tuned to work well in Opencode which is how I'm running it as well. Try it out, see how it works for you. I know that there are those who would rather use a Canadian than Chinese model in today's political climate and it does seem to perform better than Gemma 4 at least for me. Just don't forget to use the PR linked from unsloth's description until it has been merged into main.

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[–] 1 point 3 months ago

I finally got around to trying this model today. My initial impression is that it's ok conversationally and decently fast (even at Q8), but unfortunately it repeatedly fails when I ask it to do tasks that require using multiple tools in sequence -- like listing files and then reading through them to explore a codebase. (Qwen3.6 and Gemma4 both manage that fine usually.) In some of the failures, I was seeing it get stuck in loops with bad thinking tags.

I haven't pushed it hard on non-tool tasks yet though. If it turns out to be particular good at that I might try using it as a fast code generator driven by another model maybe...

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