Robo-bench
General agents control a simulated 7-DoF Franka arm and a 29-DoF humanoid through motor commands, sensors and camera images only, across 24 tasks.
The agent gets the robot datasheet and kinematic model but never the MuJoCo simulator itself. Most tasks are held out. Seven models on 2026-10-13, led by GPT-6.1 Sol at 28.33%.
- Level
- Expert Specialists with years of training, often over hours of work
- 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.
GPT-6.1 Sol leads with 28.3%
Best score per model from the benchmark's own leaderboard, read on 2 Nov 2026. Where a model ran with several settings or harnesses, we keep its best.
- 1 GPT-6.1 Sol 28.3%
- 2 GPT-6 Astra 23.3%
- 3 Claude Opus 5.5 14.6%
- 4
Muse Wonder Full 10.4%
- 5 Claude Fable 5.1 5.83%
- 6
Gemini 4 Argon 0.83%
- 7 Grok 4.7 0.21%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-6.1 Sol | 28.3% | Sep 2026 | Official leaderboard | |
| 2 | GPT-6 Astra | 23.3% | Sep 2026 | Official leaderboard | |
| 3 | Claude Opus 5.5 | 14.6% | Sep 2026 | Official leaderboard | |
| 4 | | 10.4% | Oct 2026 | Official leaderboard | |
| 5 | Claude Fable 5.1 | 5.83% | Sep 2026 | Official leaderboard | |
| 6 | | 0.83% | Sep 2026 | Official leaderboard | |
| 7 | Grok 4.7 | 0.21% | Sep 2026 | Official leaderboard |
Number one over time
Lab claims count from the day the card came out, independent runs from the model’s release.
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
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.
More in Robotics
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- Moment finding (Google DeepMind) In use Models find the moment in a robot video when an event happens. Scored by accuracy and mean absolute time distance in seconds.
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- Progress classification (Google DeepMind) In use Models assign each frame of a robot video to one of five task-progress bands from 0 to 100 percent. Scored by accuracy.
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- LIBERO Fading Simulated Franka tabletop tasks in four 10-task suites. Policies fine-tuned on 50 demos per task. Success rate over ~50 trials.
MolmoAct 2 97.2%