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looks like it's just qwen 3.6 coder.
its worse at code compared to qwen 3.6 coder.
How can it be worse than something that doesn't exist?
I'm excited to see more OSS models
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.

Wasn't aware that Cohere was still around but this release doesn't exactly instill confidence.
Really? Why not. From the benchmarks at least it's a pretty decent small model.
>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.

Aren't they focused on embeddings and strong there?
> Hardware (minimum): 1× H100 @ FP8

Cool to see this but seems like it would be pretty expensive to run

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)?
Well, this is certainly not benchmaxxed, I'll give it that. And props for being honest about how far behind Qwen 3.6 MoE is this model.

But yeah, it's not the best look to have to stretch and say it's "competitive" with other models in it's weight class, when it offers not much else that's useful or novel.