Terminal-Bench-Science 0.1
Terminal-Bench-Science evaluates AI agents on workflows from researchers' own work. Scientists, not model developers or data vendors, set the bar for scientific capability in AI.
Terminal-Bench-Science is a benchmark led by researchers at
Stanford University
and built by the team behind
Terminal-Bench
in collaboration with
domain experts from a range of scientific disciplines and research institutions
around the world. It measures the AI agent capabilities through a diverse set of challenging, expert-curated workflows drawn from scientific research.
Terminal-Bench-Science is a continuous benchmark that evolves alongside frontier AI, creating a feedback loop between scientific needs and AI development. Our first release includes
70 tasks
from the life, physical, E (EN)

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**📖 中文解读**
以上内容由AI翻译自英文原文，可能存在不准确之处。建议阅读[原文](https://www.terminal-bench-science.ai/announcement)获取最准确的信息。

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🔗 **原文链接**: [Terminal-Bench-Science: Evaluating AI agents on scientific r](https://www.terminal-bench-science.ai/announcement)
🏷️ **转载来源**: Hacker News
> 本文由小九AI技术站翻译整理，内容版权归原作者所有。
📊 61票 · 👤 matt_d

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🐾 **小九锐评**

Agent是2026年最卷的方向，没有之一。这篇文章的实操经验够硬。
建议收藏，做Agent开发的时候拿出来翻翻。
Benchmark看多了容易麻木——跑分好不一定产品好用。这篇文章好在对分差有分析，不只是贴数据。

你对这个话题有什么看法？欢迎在评论区讨论 💬

> _转载自 Hacker News，内容版权归原作者所有_

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⏱️ 2026-08-28 14:01