The MiniCPM5-2B model, a collaborative open-source initiative by LangChain AI and OpenBMB, has claimed the top spot among open-source foundation models with fewer than 4 billion parameters on the AA leaderboard. Its success is attributed to its streamlined design, featuring a mere 2 billion parameters. Despite its compact size, the model achieved a comprehensive score of 23 points, outperforming several larger models. Notably, its Agentic Index score soared to 20 points, surpassing models with several times more parameters and successfully realizing a prototype of a general-purpose agent for end-user applications. This model also excels in token efficiency, with an intelligence score nearly twice that of its peers when consuming the same number of tokens. Across 34 diverse tasks, it attained an average score of 53.9 points, securing the top position among its competitors. Furthermore, in real-world task evaluations, it scored an impressive 891 points, inching closer to human-level performance.