Are these models trained from scratch or do they necessarily need distillation from bigger models to be competitive? It's usually the case that they're a small model for a family with a bigger model. In the first case, does anybody know what's the economy of training this 30B-A3B model vs. training a DeepSeek V4 Pro or Flash size of models (1.6T, 200 something B, less activated)?

This is a 30B parameter model with 3B active. It should run performantly on a Mac with > 48GB RAM at 8bit precision.

I was a fan of coheres general purpose LLM. Command A I think? Before they came out with their reasoning model.

More competition is better.

fwiw because of the relatively few activated params offloading to system RAM is quite feasible, you can see the endless amount of people doing this on r/localllama with qwen3.6 35a3b

>Wasn't aware that Cohere was still around but this release doesn't exactly instill confidence.

It's being kept alive because the Canadian government is desperate to have a local frontier lab and is willing to inject funding and force its adoption in government services, but leadership at Cohere is known to be weak in Canadian tech circles, and they pivoting to an enterprise-first market around production RAG rather than anything close to frontier work.

I'm glad they're doing open weight releases but they're not viable in the long-run. It is embarrassing sharing similar spaces with them, but I'll try this release out in OpenCode and re-think afterwards.

Sometimes non-existing is better than existing for unnecessary or harmful things. I know that is not what you mean but I just found it relevant in the age in which making new stuff is so fast and easy due to LLMs. Main enshitification would come, imo, not from bad things but for unnecessary things that nobody asked for.

There is no "coder" version of Qwen 3.6; I think they just mean it's a coding-focused model of similar size and performance (to Qwen 3.6 35B-A3B).

Regular Qwen 3.6 benchmarks slightly better and has much wider software support though, so this is probably of interest only to organizations which disallow models trained in China.

I mean, Qwen 3.6 kicks ass. I don't know who these people are, but if their first outing is "not quite as good as Qwen 3.6", that's not a bad start by any means.

30B vs 35B isn't nothing either.

If it ends up just being some tweaks to someone else's weights, then meh.

It was trained from scratch by Cohere. They're the only Canadian AI lab - I'm glad they're releasing open weights and I wish them luck catching up!