Cohere's First Model for Developers

Cohere launched North Mini Code, an open-source mixture-of-experts model with 30B total parameters and 3B active, optimized for agentic coding tasks. Released under Apache 2.0, it aims to provide developers with sovereign AI capabilities for code generation and software engineering, achieving competitive benchmark scores and up to 2.8x higher throughput than comparable models.

Today we're launching North Mini Code open-source. A mixture-of-experts MoE model, North Mini Code is Cohere's first agentic coding model, and the inaugural member of our next generation of powerful models. At 30B total parameters with just 3B active, North Mini Code delivers strong software development performance without demanding extensive hardware to match. Efficient by design, it's built to run where you need it. Freely available under an Apache 2.0 https://www.apache.org/licenses/LICENSE-2.0? gl=1 gri8sk gcl au MjU0OTU5MzQwLjE3Nzk4MDczMTc. license, North Mini Code advances Cohere’s mission to make sovereign AI a practical reality, giving developers direct access to agentic coding capabilities. We're building in the open, because the future of AI should be shaped by the people running, testing, and improving it. Download the weights on Hugging Face https://huggingface.co/CohereLabs/North-Mini-Code-1.0 , or deploy in a dedicated, managed inference environment on Model Vault https://dashboard.cohere.com/welcome/login . Alternatively, try it for free in your harness of choice on OpenCode https://opencode.ai/ or with a Cohere API key https://dashboard.cohere.com/ . Share what you build and tag @ Cohere on X https://x.com/cohere or Discord https://discord.com/invite/co-mmunity , or engage with us on Reddit https://www.reddit.com/r/LocalLLaMA/comments/1tylzy2/coheres unreleased coding model early access for/ . Snapshot | Model | North-Mini-Code-1.0 | |---|---| | License | Apache 2.0 | | Model size | 30B total; 3B active | | Context length | 256K total context; 64K max generation | | Optimized for | Code generation, agentic software engineering, and terminal tasks | | Availability | Hugging Face Weights , Cohere API, Cohere Model Vault, OpenRouter | | Hardware minimum | 1× H100 @ FP8 | Agentic coding capabilities North Mini Code achieves competitive scores across benchmarks against models of this size class, demonstrating strong performance in real-world software engineering tasks. North Mini Code’s benchmark scores translate to a 33.4 on the Artificial Analysis Coding Index https://artificialanalysis.ai/models/north-mini-code , a competitive position among similarly sized models. The speed advantage for developer tasks North Mini Code is designed for speed and efficiency, with a strong focus on minimizing total cost of ownership as we continue to refine and scale the model. In our testing, North Mini Code achieved up to 2.8x higher output throughput than Devstral Small 2 under identical concurrency levels and hardware configurations. In practical terms, that translates to nearly three times the work rate, enabling faster iteration while reducing computational overhead. North Mini Code also demonstrated a 30% advantage in inter-token latency, a metric that reflects the consistency and pacing of token generation. Time-to-first-token TTFT performance was more closely matched between the two models, with Devstral Small 2 maintaining a slight edge across the tested conditions. Sovereign open models for developers North Mini Code is our first open-source model for developers. As coding agents transform software engineering, developers need control and flexibility over their agentic coding infrastructure. North Mini Code represents a step forward in small agentic coding models that can accomplish tasks that matter to developers. Specifically, it is built for agentic workflows, including understanding and orchestrating sub-agents, mapping systems architecture, and running code reviews. Deploy on-prem or locally, on your own terms. Community feedback will directly shape our roadmap as we expand the ecosystem toward more open and sovereign developer models. Try North Mini Code when you need freedom from vendor constraints, and help us build what's next. What’s next? North Mini Code launches as the first—but certainly not the last—of Cohere's new generation of powerful models, designed for a more sovereign open-source ecosystem. We're committed to increasing our capabilities, with community input informing what comes next. Getting started Help us build a complete sovereign AI ecosystem for software development by trying North Mini Code. North Mini Code is available for free on Hugging Face https://huggingface.co/CohereLabs/North-Mini-Code-1.0 and Model Vault https://dashboard.cohere.com/welcome/login? gl=1 uxjn5q gcl au MjA0ODIxMjk3My4xNzgwOTUxMzc0 ga NzE2NDY3MTkyLjE3ODA5NTEzNzQ. ga CRGS116RZS czE3ODA5NTEzNzMkbzEkZzAkdDE3ODA5NTEzNzQkajU5JGwwJGgw —our fully managed inference platform. We've specifically trained it for compatibility with OpenCode https://opencode.ai/ , but it works with most coding agents. Share what you build and tag @ Cohere on X https://x.com/cohere or Discord https://discord.com/invite/co-mmunity , or engage with us on Reddit https://www.reddit.com/r/LocalLLaMA/comments/1tylzy2/coheres unreleased coding model early access for/ to help shape the future of sovereign models. Visit our documentation https://docs.cohere.com/docs/north-mini-code-1.0 for detailed model specs, deployment guides, and cookbooks to get started. 1 We used publicly reported scores for competitor models either from original reports or Artificial Analysis Intelligence Index where available. Additionally, Gemma 4’s scores for agentic coding tasks were reported by Qwen team https://qwen.ai/blog?id=qwen3.6-35b-a3b . For the benchmark results that any public report is missing denoted by in Image 1, we run internally with recommended model configuration. 2 We evaluated North Mini Code using “SWE-agent” harness for SWE-Bench Verified and SWE-Bench Pro, and a simple ReAct harness employing a single terminal-use tool for Terminal Bench v2. For Terminal Bench Hard, we used Terminus-2 harness for both North Mini Code and the other models that are evaluated internally.