OpenRSI Index
Not in model cards
Agents run autoresearch on real open-source model development projects with their original code, data and checkpoints, for 60 or more hours. Fixed verifiers score the result against the human recipe they started from.
Signature tasks, such as Qwen-122B RL and a Marin scaling-ladder optimizer, use 256 H100s and up to about 20,000 H100-hours per run. Public tasks need 1 to 8 H100s. Repo has 289 stars.
Made by OpenRSI Foundation (UW-led, academic and industry partners) Released Sep 2026 AI research tasks All tasks public
- Level
- Research frontier Researchers, on open problems or tasks that take days
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
No scores here yet
No lab, leaderboard or Epoch AI run has reported a score for OpenRSI Index yet.
No lab model card reports it yet
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.
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