K9-Bench - Cause-Effect Analysis: leaderboard

K9-Bench tests video understanding of domestic dogs: five-option questions about canine posture, action order, scene context, cause and effect, and interaction with people and other dogs, built from real-world web videos with an expert-grounded behaviour ontology. This board covers the questions about what caused a behaviour and what followed from it. Models answer in free form and an answer counts as correct when its embedding is closest to the gold option.

Metric: MCQ accuracy (%; the Cause-Effect Analysis category of K9-Bench, 4,744 five-option questions on 907 real-world dog videos; the free-form CoT answer counts as correct when its Qwen3-Embedding-8B similarity to the gold option exceeds 0.5 and no wrong option is closer; 32 uniformly sampled frames for GPT-4o and the open models, the full video at 1 FPS for Gemini 2.5 Pro and Qwen3-VL-235B-A22B). Source: arxiv.org. Saturation forecast: Around February 2027. 11 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro44.7#266
2Qwen 3 VL 235B A22B Instruct39.9#522
3GPT-4o (2024-08-06)33.9#740
4Qwen 3 VL 32B (Thinking)32.8#559
5Qwen 3 VL 32B Instruct31.1#585
6Qwen 3 VL 4B Instruct28.2#1279
7Qwen 3 VL 8B Instruct27.6#981
8Qwen 3 VL 8B (Thinking)24.9#887
9Qwen 3 VL 4B (Thinking)23.1#1296

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=k9-bench-cause-effect-analysis · How It Works · Data refreshed daily, snapshot 2026-11-13.