Cohere's North Mini Code Beats 120B Models With Just 3B Active Parameters

Cohere just made a move that enterprise AI vendors rarely do: they shipped a genuinely useful open-source model aimed squarely at developers, not their usual enterprise buyers. North Mini Code is a 30-billion-parameter Mixture-of-Experts (MoE) coding model with only 3 billion parameters active at any given time, released under the Apache 2.0 license with no usage restrictions.

North Mini Code is the first model in Cohere's new family of models, specifically designed and trained for agentic software engineering tasks. Cohere's prior models, Command R and Aya, were not coding-focused, and the company had not previously shipped an open-weight coding model. This is a meaningful pivot.

One H100. Free. No strings.

North Mini Code landed with a straightforward pitch: a 30 billion parameter agentic coding agent, Apache 2.0 licensed, that fits on a single NVIDIA H100. MoE (Mixture-of-Experts) is an architecture where the model is split into many specialized sub-networks called "experts," and only a small subset of them activate for each token. North Mini Code routes each query to a small subset of specialized expert networks within the larger model, keeping inference costs dramatically lower than a dense 30B model would require.

The model ships under an Apache 2.0 license, with full commercial permissibility including fine-tuning, redistribution, and commercial deployment. Weights are on Hugging Face in both BF16 and an FP8-quantized variant, and the model is also reachable through the Cohere API, Cohere Model Vault, OpenRouter, and OpenCode. Pricing on Cohere's API is currently $0.00 per million tokens for both input and output.

What it can actually do

North Mini Code is optimized for complex software engineering workflows, terminal-based agentic tasks, and high-quality code generation. On the Artificial Analysis Coding Index, it scores 33.4, which puts it ahead of models several times its size. Specifically, it outperforms Nemotron 3 Super (120B), Mistral Small 4 (119B), and Devstral 2 (123B) on coding tasks, despite having a fraction of their active parameters.