Causal-Plan-Bench - Failure Recovery: leaderboard

An open-ended task of Causal-Plan-Bench (2026): models propose a recovery strategy that re-establishes the conditions a failed step needs, over 100 held-out video items; a GPT-5.6-sol rubric judge scores each answer against a human-verified reference on a 0-100 scale. Items come from egocentric and robot video and every model sees the same instruction and evidence; higher is better.

Metric: Open-ended failure recovery (a strategy to re-establish the conditions after a failure) task, rubric score (0-100): a blind GPT-5.6-sol judge scores each open-ended answer against a human-verified reference from 0 to 1, times 100; 100 held-out expert-reviewed items per task drawn from egocentric and robot video (EPIC-KITCHENS, Ego4D, HoloAssist and others), the same instruction, visual evidence and answer format for every model, temperature 0.2, mean of three regenerated runs; higher is better. Source: arxiv.org. Saturation forecast: Around 2032. 14 models tracked.

Top models

#ModelScoreOverall rank
1GPT-6 Astra46.4#6
2Gemini 3.1 Pro (Preview)42.2#94
3Seed 2.1 Pro40.2#135
4GPT-5.6 Sol39.5#30
5Kimi K2.539.4#256
6GPT-4o38.2#741
7Qwen 3 VL 8B Instruct35.5#981

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=causal-plan-bench-failure-recovery · How It Works · Data refreshed daily, snapshot 2026-11-13.