LongVQUBench - Open-Ended Relevance: leaderboard
Metric: Relevance score (%; how directly the answer addresses the question; GPT-5 judge score of each free-form answer against the expert reference answer, rated 0 to 1 and averaged over the local, cross-event and global levels, reported in percent; open-ended questions of the 60% held-out test split, same frame budgets as the multiple-choice runs). Source: arxiv.org. Saturation forecast: Around December 2026. 10 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-5 | 88.9 |
| 2 | Qwen 3 VL 8B Instruct | 79.3 |
Interactive version: theaggregate.ai/benchmark?slug=longvqubench-open-ended-relevance · How It Works · Data refreshed daily, snapshot 2026-09-29.