Today, we are releasing North Mini Code, a 30B-parameter Mixture-of-Experts model with 3B active parameters with powerful agentic coding capabilities, available on Hugging Face under the Apache 2.0 license.

North Mini Code is the first model in Cohere’s new family of models, and is specifically designed and trained for agentic software engineering tasks.

Figure 1: North Mini Code’s performance in agentic coding tasks and complex code generation benchmarks, compared to leading open-source models of similar size. See here for the details of our benchmarking methodology.

North Mini Code is optimized for complex software engineering workflows, terminal-based agentic tasks, and high-quality code generation. On Artificial Analysis’ Coding Index, North Mini Code achieves a score of 33.4, outperforming Qwen3.5 (35B-A3B), Gemma 4 (26B-A4B), Devstral Small 2 (24B Dense), and even substantially larger models such as Nemotron 3 Super (120B-A12B), Mistral Small 4 (119B-A6B), and Devstral 2 (123B).1 It ranks among the strongest open-source coding models in its size class.

Real-world code agents depend on model quality and robustness across agent harnesses. We trained North Mini Code using multiple scaffolds rather than optimizing for a single one. This approach enables North Mini Code to serve as a reliable foundation for coding agents such as OpenCode.

Figure 2: North Mini Code is a Mixture-of-Experts Transformer decoder with interleaved sliding-window self-attention and full self-attention.