Terminal-Bench Science extends the original Terminal-Bench benchmark used by Anthropic, OpenAI, and Google DeepMind into scientific domains and opens for over 100 task contributions by August 17, 2026

I'm very excited about this extension to the celebrated Terminal-Bench to science.

If you're a scientist (life, physical, earth, mathematical science, etc) interested in AI, definitely check this out!

Terminal bench evaluate how good AI models are at controling tools on a computer to achieve a goal (using the command line). T-Bench science now extends that to "AI for Science" and it comes with a call to contribute your own (real scientific world) workflow to the benchmark (until August 2026).

The more workflows and the more diverse they are, the better the next generation of AI models will be at helping you in your daily research work.

Note that this is not a training dataset, it's to evaluate frontier model performances.

Terminal-Bench Science is a direct way to contribute to AI for Science. It's programming agents by task specification. Ask a precise scientific question and watch how AI agents will learn to solve it: Step 1. Package a scientific task or workflow, something that takes a working scientist a week or month to do into an RL environment. Step 2. Write tests that verify if the task has been done correctly (can be done easily if you have already solved the task manually). Step 3. Sit back and let AI agent progress solve it in 6 months.

Science is the frontier of AI. Contribute to this initiative if you can!

Extremely excited for Terminal-Bench Science, which we're proud to support via our Open Benchmarks Grants @SnorkelAI !

"AI for science" benchmarks today mostly test textbook recall. Terminal-Bench Science is a chance for scientists to practice writing that definition. Contribute a real workflow, and you find out exactly where today's best agents break on it. http://tbench.ai/news/tb-science-announcement