AffectSim (Reference View): leaderboard

AffectSim (2026) tests emotion recognition from body movement in simulated homes: emotion-labelled full-body motions are replayed in Habitat indoor scenes and a frozen vision-language model classifies each of 3,941 test episodes as angry, fearful, happy, neutral or sad. The observation is an informative camera trajectory chosen by a privileged reference observer from body pose and scene geometry. Score is macro-F1 in percent; higher is better.

Metric: Macro-F1 (%; P-Ref: an informative camera trajectory chosen by a privileged reference observer from body pose and scene geometry; five-class emotion recognition (angry, fearful, happy, neutral, sad) on the 3,941 test episodes of AffectSim, full-body affective motions replayed in Habitat indoor scenes; frozen recognizer, eight uniformly sampled frames for most open models, full video or eight frames for closed models). Source: arxiv.org. Saturation forecast: Around July 2028. 24 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 535.68#22
2GPT-5.6 Sol31.48#30
3Gemini 3 Pro30.21#137
4InternVL2.5-78B30.02#1014
5Gemini 3 Flash28.33#164
6GPT-5.228.2#176
7Qwen 3 VL 8B Instruct15.54#981
8Qwen2.5-Omni-7B12.09#1789
9Qwen 3 VL 8B (Thinking)11.15#887
10MiniCPM-V-2.69.89#3063
11Qwen 2.5 VL 72B Instruct7.57#846
12Qwen 2.5 VL 7B Instruct6.12#1833

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

Interactive version: theaggregate.ai/benchmark?slug=affectsim-reference-view · How It Works · Data refreshed daily, snapshot 2026-11-13.