Cohere North Mini Code

The most substantive user discussion comes from HackerNews (highly upvoted threads). Technically, users identify North Mini Code as a 30B-A3B (30B total, ~3B activated) Mixture-of-Experts model trained from scratch by Cohere. One user actually ran it locally: downloaded a 4-bit quantized GGUF, used llama.cpp, and pointed OpenCode at it on an 8-core Gen1 Ryzen 7 with 32GB DDR4 — confirming that the low activated-parameter count makes system-RAM offloading 'quite feasible,' consistent with what r/locallama users do with Qwen 3.6 35A3B. On benchmark performance, sentiment is blunt: 'this is certainly not benchmaxxed.' Multiple users note it trails Qwen 3.6 35B-A3B, with one saying it's 'not the best look to stretch and say it's competitive.' One commenter observes there's 'not much else that's useful or novel' beyond being an alternative for organizations that disallow China-trained models (i.e., Qwen). A separate, dominant thread of comments attacks Cohere at the company level: allegations of Canadian government cronyism, 'painfully low' actual API usage, weak leadership, and investors 'preparing their slides' for them. Some balance exists: 'I'm glad they're releasing open weights and I wish them luck catching up.' NOTE: Product Hunt comments appear to describe a completely different 'Cohere' product (a user-onboarding/support tool with Figma-like cursors), and Lemmy comments discuss Half-Life game design — both are data contamination irrelevant to this LLM.

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