MiniCPM5-2B小模型展现强大能力

在Artificial Analysis Intelligence Index v4.1.

1基准测试中，MiniCPM5-2B得分23，在40亿参数以下开源模型中排名第一。

Ok this small local model is sooo good MiniCPM5-2B has only 2B parameters (!!) and can run agents on any laptop or even your phone fully offline. This 100% open source model can perform coding/agentic/tool use tasks and can run on just 2GB RAM! And it's genuinely good even in Hermes agent! I asked it to: - Go to Hugging Face - Find the Models section - Evaluate models across multiple criteria - Create a CSV with the top 15 It did it! In the Artificial Analysis Intelligence Index v4.1.1 results cited in the official release, MiniCPM5-2B scores 23 and ranks #1 among open-source models under 4B parameters. So it's not about the size of the model anymore but way more the density of intelligence: Researchers from Tsinghua University and ModelBest proposed the “Densing Law”: the maximum capability density of open-source pretrained base models roughly doubled every 3.5 months over the period studied! And what's also interesting is that OpenBMB's open-source approach goes beyond just releasing model weights with - Selected training methods - Agent-related data - Data refinement resources Also being opened up, including the RL stack with Meshy + JustRL II. This model even outperforms some models around 6x larger on selected evaluations such as GDPval-AA v2!

本条情报归属 AITOP「模型」核心栏目，重点聚焦中国 AI 产业与国产大模型生态。在跨区域产业观察坐标中，该动态直接关联「AI 开发者工具链、Coding Agent 与工程化实践」「中美大模型技术代差与商业化对照」研究主线，反映出当前技术演进与商业落地的最新风向。涉及核心实体与技术议题包括：MiniCPM5-2B、开源模型、Tsinghua University、ModelBest，读者可通过下方标签进入对应专题页查阅历史脉络与关联对比。

信源核验说明：本文原始线索采编自「Paul Couvert」（@itsPaulAi），经 AITOP 多维评分管线结构化提炼。