AICA-Bench - Emotion Reasoning: leaderboard
Metric: Emotion reasoning score on a percent scale: the model explains why an image evokes its labeled emotion, scored by the AICA-Bench scoring model (Qwen2.5-VL-7B fine-tuned on human 1-5 ratings) on emotion alignment and descriptiveness and causal soundness, ratings rescaled as s/5 x 100 (20-100), over AICA-Bench (8,086 affective images from nine public emotion datasets with GPT-4o-generated instructions; closed-source models through their APIs at standard settings, open models on A100 GPUs); higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 23 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Gemini 2.5 Pro | 79.08 |
| 2 | GPT-4o | 77.81 |
| 3 | Gemini 2.5 Flash | 76.55 |
| 4 | GPT-4o Mini | 76.45 |
| 5 | Qwen 2.5 VL 7B Instruct | 74.5 |
| 6 | Gemini 2.0 Flash | 71.05 |
| 7 | MiniCPM-V-2.6 | 65.77 |
| 8 | Qwen 2 VL 7B Instruct | 65.23 |
Interactive version: theaggregate.ai/benchmark?slug=aica-bench-emotion-reasoning · How It Works · Data refreshed daily, snapshot 2026-10-07.