# Cohere发布North Mini Code：30B总参数（3B活跃）开源编码模型

- 来源：Artificial Analysis (@ArtificialAnlys)
- 发布时间：2026-06-10 00:03
- AIHOT 分数：70
- AIHOT 链接：https://aihot.virxact.com/items/cmq6uj83n0by6sl5iik6xa6r1
- 原文链接：https://x.com/ArtificialAnlys/status/2064377790875455938

## AI 摘要

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。

## 正文

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