Causal-Plan-Bench - Effects: leaderboard
Metric: Effects score: mean four-choice accuracy (%) after answer normalization over the affordance visual semantics, spatial postcondition and affordance postcondition 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 2036. 14 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-6 | 39.67 |
| 2 | Seed 2.1 Pro | 37.33 |
| 3 | Gemini 3.1 Pro (Preview) | 36 |
| 4 | GPT-5.6 Sol | 36 |
| 5 | Kimi K2.5 | 33.33 |
| 6 | Qwen 3 VL 8B Instruct | 33 |
| 7 | InternVL3.5-8B | 31.67 |
| 8 | GPT-4o | 30.33 |
Interactive version: theaggregate.ai/benchmark?slug=causal-plan-bench-effects · How It Works · Data refreshed daily, snapshot 2026-09-29.