斯坦福开源了新agent模型，基于Qwen-3在7个基准上平均44.8%，小模型也能打，值得一试。
Stanford AI Lab发布OpenThoughts-Agent-v2和OpenThinkerAgent-32B，两者均基于Qwen-3开源数据。在计算控制比较中，该模型在全部训练规模下领先，并在7个agent基准测试上平均得分44.8%。模型在终端使用和编码任务上表现突出，且泛化能力强。
Most open agentic datasets target one benchmark. In compute-controlled comparisons, OpenThoughts-Age...
Most open agentic datasets target one benchmark. In compute-controlled comparisons, OpenThoughts-Agent-v2 leads at every training set size, and generalizes across seven agentic benchmarks. Check it out! Richard Zhuang @RichardZ412 How can we train small agentic models that are highly capable of terminal use and coding? Announcing OpenThoughts-Agent + OpenThinkerAgent-32B, the strongest Qwen-3 based open-data agentic model: 44.8% avg across 7 agentic benchmarks! (1/n) 🔗 View Quoted Tweet 💬 1 🔄 2 ❤️ 15 👀 1605 📊 3 ⚡