CiteVQA - Multi-Doc (1-Gold): leaderboard
Metric: Strict attributed accuracy (%): share of questions with answer score at least 4 and either relevance at least 4 or evidence recall at least 0.6, on the multi-document questions with one gold document (25.7 percent of the set), the model answers from the document pages and cites element-level bounding boxes, unified prompt, temperature 1.0, at most 4,096 output tokens, Qwen3-VL-235B-A22B judge; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 20 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Gemini 3.1 Pro (Preview) (High) | 79.7 |
| 2 | Gemini 3 Flash (Preview) (High) | 61.8 |
| 3 | GPT-5.4 (xHigh) | 56.9 |
| 4 | GPT-5.2 (xHigh) | 38.8 |
| 5 | Seed 2.0 Pro | 33.5 |
| 6 | Gemma 4 31B | 29.8 |
| 7 | Qwen 3.5 27B | 22.6 |
| 8 | Qwen 3.5 397B A17B | 22.2 |
| 9 | Qwen 3 VL 235B A22B Instruct | 21.6 |
| 10 | Kimi K2.5 | 18.9 |
| 11 | Qwen 3.6 Plus | 18.5 |
| 12 | Qwen 3.5 9B | 17.7 |
| 13 | Qwen 3.5 122B A10B | 17 |
| 14 | Qwen 3 VL 32B Instruct | 16.2 |
| 15 | Qwen 3.5 35B A3B | 15.6 |
Interactive version: theaggregate.ai/benchmark?slug=citevqa-multi-doc-1-gold · How It Works · Data refreshed daily, snapshot 2026-10-07.