Autor: Jakub Rusinowski · Ostatnia aktualizacja: 11 września 2026
Cohere's first model aimed at developers rather than enterprises, and the opening entry in their North family of code agents. A 30B sparse MoE activating ~3B per token, Apache 2.0, 256K context and 64K maximum generation — small enough to run locally while posting a Coding Index of 33.4, ahead of several open models many times its size.
| Licence | What it permits | Applies to |
|---|---|---|
Apache-2.0 | Commercial use permitted Commercial use permitted. No usage restrictions beyond attribution. | North Mini Code 1.0 30B-A3B |
| North Mini Code 1.0 30B-A3B | Min 19 GB VRAM · Q4_K_M · 256,000 ctx · |
The cheapest GPU that runs North Mini Code locally (min 19 GB VRAM) is the AMD Radeon RX 7900 XT (20 GB).
Install Ollama then run: ollama run
Minimum VRAM: 19 GB. For best results use Q4_K_M quantization.
North Mini Code needs about 19 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: North Mini Code 1.0 30B-A3B (19 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — North Mini Code runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
Q4_K_M is the best balance of quality and VRAM for North Mini Code in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
Install Ollama, then run: ollama run . This downloads North Mini Code and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.