Causal-Plan-Bench - Executability: leaderboard
The executability dimension of Causal-Plan-Bench (2026), the mean of three tasks on whether an action is executable: spatial and affordance preconditions and physical feasibility, as four-choice accuracy (%). Items come from egocentric and robot video and every model sees the same instruction and evidence; higher is better.
Metric: Executability score: mean four-choice accuracy (%) after answer normalization over the spatial precondition, affordance precondition and physical feasibility 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 | 46.33 | #6 |
| 2 | Seed 2.1 Pro | 42 | #135 |
| 3 | Gemini 3.1 Pro (Preview) | 40.67 | #94 |
| 4 | GPT-5.6 Sol | 39.67 | #30 |
| 5 | Qwen 3 VL 8B Instruct | 38.67 | #981 |
| 6 | GPT-4o | 35.33 | #741 |
| 7 | Kimi K2.5 | 33.67 | #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-executability · How It Works · Data refreshed daily, snapshot 2026-11-13.