RoboProcessBench - Current Primitive Recognition: leaderboard
RoboProcessBench (2026) asks vision-language models multiple-choice questions about how a robot manipulation is unfolding, using frames and short clips from held-out recordings of four robot datasets. This task asks which low-level primitive is being executed, from a short clip, with 4 options; accuracy in percent, higher is better.
Metric: Accuracy (%) on 359 questions asking which low-level primitive is being executed, from a short clip (4 options, chance 25.0); zero-shot multiple-choice VQA on held-out robot manipulation recordings from GM-100, RH20T, REASSEMBLE and AIST-Bimanual (ProcessData-Eval), temperature 0.01; higher is better. Source: arxiv.org. 14 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GLM-4.6V | 34 | #701 |
| 2 | Qwen 2.5 VL 7B Instruct | 33.1 | #1833 |
| 3 | GPT-5.4 Mini | 32.1 | #389 |
| 4 | GPT-4o | 32 | #741 |
| 5 | InternVL3-8B | 31.2 | #1688 |
| 6 | Claude Sonnet 4.6 | 27.3 | #161 |
| 7 | InternVL3-38B | 26.2 | #903 |
| 8 | Claude Haiku 4.5 | 23.4 | #568 |
Interactive version: theaggregate.ai/benchmark?slug=roboprocessbench-current-primitive-recognition · How It Works · Data refreshed daily, snapshot 2026-11-13.