MUN-lang (5-Shot): leaderboard
Metric: Win rate (%; share of MUN-lang items where a GPT-4o judge, AlpacaEval-style, prefers the model's explanation (explain how an ordinary-looking image leads to an unusual outcome) over the human-written, GPT-4o-refined reference; five randomly chosen in-context examples). Source: arxiv.org. Saturation forecast: Estimated already saturated. 7 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Phi-4 Multimodal Instruct | 65.1 |
| 2 | Gemma 3 4B (IT) | 49.8 |
| 3 | Qwen 2.5 VL 7B Instruct | 41 |
| 4 | Qwen 2 VL 7B Instruct | 36.5 |
Interactive version: theaggregate.ai/benchmark?slug=mun-lang-5-shot · How It Works · Data refreshed daily, snapshot 2026-09-26.