MVPBench - Weather Condition Evaluation: leaderboard
Metric: MVPBench normalized proficiency score (accuracy minus chance, divided by one minus chance, times 100, so 0 is chance level and 100 is perfect) on its 45 multi-video questions choosing the most severe weather among three clips; chance is 1/3; answers extracted by rules and GPT-4-turbo; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 15 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemini 2.5 Flash | 18.79 | #237 |
| 2 | GPT-4o | 12.51 | #333 |
| 3 | InternVL3-78B | -3.33 | #345 |
| 4 | Qwen 2.5 VL 72B Instruct | -8.32 | #364 |
| 5 | InternVL3-8B | -9.99 | #606 |
| 6 | InternVL3-38B | -16.66 | #395 |
| 7 | Qwen 2.5 VL 7B Instruct | -16.66 | #643 |
No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.
Interactive version: theaggregate.ai/benchmark?slug=mvpbench-weather-condition-evaluation · How It Works · Data refreshed daily, snapshot 2026-10-11.