MUN-vis (Zero-Shot): leaderboard
Metric: Win rate (%; share of MUN-vis items where a GPT-4o judge, AlpacaEval-style, prefers the model's explanation (explain why a visually odd image leads to an ordinary outcome) over the human-written, GPT-4o-refined reference; zero-shot). Source: arxiv.org. Saturation forecast: Estimated already saturated. 7 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Phi-4 Multimodal Instruct | 41 |
| 2 | Qwen 2.5 VL 7B Instruct | 36.4 |
| 3 | Gemma 3 4B (IT) | 33.5 |
| 4 | Qwen 2 VL 7B Instruct | 22.5 |
Interactive version: theaggregate.ai/benchmark?slug=mun-vis-zero-shot · How It Works · Data refreshed daily, snapshot 2026-09-26.