RoboProcessBench - Primitive Chain Restoration: 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 primitive fills a masked slot in the local action chain, with 4 options; accuracy in percent, higher is better.

Metric: Accuracy (%) on 46 questions asking which primitive fills a masked slot in the local action chain (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

#ModelScoreOverall rank
1InternVL3-8B91.3#1688
2GPT-5.4 Mini87#389
3InternVL3-38B82.6#903
4Qwen 2.5 VL 7B Instruct80.4#1833
5GLM-4.6V76.7#701
6GPT-4o76.1#741
7Claude Haiku 4.567.4#568
8Claude Sonnet 4.665.2#161

Interactive version: theaggregate.ai/benchmark?slug=roboprocessbench-primitive-chain-restoration · How It Works · Data refreshed daily, snapshot 2026-11-13.