Causal-Plan-Bench - Physical Feasibility: leaderboard

A four-choice task of Causal-Plan-Bench (2026) on why an observed action is physically executable at that moment, 100 held-out video items scored by accuracy (%). Items come from egocentric and robot video and every model sees the same instruction and evidence; higher is better.

Metric: Accuracy (%) on the physical feasibility (why the action is executable now) task (four-choice accuracy (%) after answer normalization); 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 Astra50#6
2Qwen 3 VL 8B Instruct43#981
3GPT-5.6 Sol42#30
4Seed 2.1 Pro42#135
5Gemini 3.1 Pro (Preview)39#94
6GPT-4o37#741
7Kimi K2.534#256

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-physical-feasibility · How It Works · Data refreshed daily, snapshot 2026-11-13.