Cohere近日发布North Mini Code,一款30B总参数(3B活跃参数)的开放权重编码模型,采用Apache 2.0开源协议。该模型在Artificial Analysis Intelligence Index上得分27.6,高于gpt-oss-20B (high)的24.5,略低于Mistral Small 4(119B参数,6.5B活跃)的27.8。在Coding Index(Terminal-Bench Hard和SciCode加权平均)上得分33.4,显著高于GLM-4.7-Flash的25.9,低于Qwen3.6 35B A3B的35.2。非编码智能体任务表现较弱:GDPval-AA 14%、τ²-Bench Telecom 37%。在Cohere API上推理速度约199 output tokens/s,快于同类模型。距Cohere上次发布Command A+不到一个月。
Cohere just released North Mini Code, a small 30B parameter (3B active) open weights coding model that scores 27.6 on the Artificial Analysis Intelligence Index
Less than a month since @cohere's last model release, Command A+, has launched another open weights model that is optimized for coding, and much smaller at 30B total parameters and 3B active parameters.
Key Takeaways:
➤ Achieves 27.6 on the Artificial Analysis Intelligence Index, above gpt-oss-20B (high) at 24.5 and just below Mistral Small 4 (119B parameters, 6.5B active) at 27.8
➤ Scores competitively on the Artificial Analysis Coding Index (weighted average of Terminal-Bench Hard and SciCode) against open weights models in its size class, scoring 33.4, significantly above GLM-4.7-Flash at 25.9, and below Qwen3.6 35B A3B at 35.2. However, it underperforms on non-coding agentic tasks, scoring 14% on GDPval-AA and 37% on τ2-Bench Telecom
➤ On Cohere's API, North Mini Code is faster than several comparable open weights models of its intelligence and size class (~199 output tokens per second)
➤ North Mini Code is a text-only 30B total parameter and 3B active parameter model, and is open-sourced under the Apache 2.0 license