Dense 200 (bbox)
Qwen 3.8 Max 87% In use Model detects and boxes every object in 200 densely annotated images (109 categories, about 91 boxes each). Box F1 at IoU thresholds.
Mistral's 'Dense 200 (bbox)' is assumed to be this Dense200 set. Eval data is bundled with other Rex-Omni eval sets.
Made by IDEA Research (Rex-Omni) Released Oct 2025 Detection and captioning All tasks public Last in a launch post Oct 2026
Last model added Oct 2026
- Level
- Everyday Most adults, without training
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Short answer A number, word or short string matched to a key.
2
Models scored in lab cards
2
Launch posts list it, from 2 labs
Qwen 3.8 Max leads with 87%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Qwen 3.8 Max | 87% | Aug 2026 | Model card | |
| 2 |  Mistral Large 4 | 42% | Oct 2026 | Model card |
The best score passed 85% in Aug 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Reported by the lab in its model card
2 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 6 Oct 2026 | Mistral Large 4 | 42 | Grounding: Dense200 (bbox) |
| 3 Aug 2026 | Qwen 3.8 Max | 87 | Dense200 |
More in Vision
- MMMU In use 11.5K college-level multimodal questions across 30 subjects. Multiple-choice and open accuracy. GPT-5.1 85.4%
- MMMU-Pro In use Harder MMMU: college-level multimodal questions with more options and vision-only inputs to remove text shortcuts. Kimi K3.1 Pro 84.1%
- CharXiv In use Chart understanding on real arXiv figures. Reasoning questions require synthesizing information from complex charts. Claude Fable 5 93.5%
- MATH-Vision (MathVision) In use 3,040 competition math problems with visual context. Answer accuracy. Qwen 3.8 Max 97.7%
- ChartQA In use Models answer human-written and generated questions about chart images that need visual and arithmetic reasoning. Scored by relaxed accuracy with a 5 percent numeric tolerance.
Command A Vision 90.9% - DocVQA In use Models answer 50,000 questions about 12,000 scanned document images by reading their text and layout. Scoring is ANLS, a string similarity to reference answers.
Seed1.5-VL 96.9%