OpenRSI Index
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.
- Released
- September 2026
- Kind
- AI research tasks
- Level
- Research frontier
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- All public
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 522 launch posts from 52 labs, and none of them list this benchmark.
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