Causal-Plan-Bench - Robustness: leaderboard
The robustness dimension of Causal-Plan-Bench (2026), the mean of three tasks on robust planning: plan diagnosis and repair, counterfactual outcomes and failure recovery, as open-ended answers scored 0-100 by a GPT-5.6-sol rubric judge. Items come from egocentric and robot video and every model sees the same instruction and evidence; higher is better.
Metric: Robustness score: mean 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, over the plan diagnosis and repair, counterfactual outcome and failure recovery tasks; 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
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-6 Astra | 44.17 | #6 |
| 2 | Gemini 3.1 Pro (Preview) | 38.9 | #94 |
| 3 | GPT-5.6 Sol | 38.57 | #30 |
| 4 | Seed 2.1 Pro | 37.6 | #135 |
| 5 | Kimi K2.5 | 35.93 | #256 |
| 6 | Qwen 3 VL 8B Instruct | 33.13 | #981 |
| 7 | GPT-4o | 32.07 | #741 |
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-robustness · How It Works · Data refreshed daily, snapshot 2026-11-13.