Causal-Plan-Bench - Spatial Postcondition: leaderboard

A four-choice task of Causal-Plan-Bench (2026) on the spatial result an action causes (position, contact, support), 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 spatial postcondition (spatial result after the action) 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
1Seed 2.1 Pro42#135
2GPT-6 Astra41#6
3Gemini 3.1 Pro (Preview)38#94
4GPT-5.6 Sol38#30
5Kimi K2.535#256
6GPT-4o33#741
7Qwen 3 VL 8B Instruct32#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-spatial-postcondition · How It Works · Data refreshed daily, snapshot 2026-11-13.