---
dataset_info:
- config_name: vision_bench_0701
  features:
  - name: question_id
    dtype: string
  - name: instruction
    dtype: string
  - name: image
    dtype: image
  - name: language
    dtype: string
  splits:
  - name: test
    num_bytes: 1654009592.0
    num_examples: 500
  download_size: 1653981819
  dataset_size: 1654009592.0
- config_name: vision_bench_0617
  features:
  - name: question_id
    dtype: string
  - name: instruction
    dtype: string
  - name: image
    dtype: image
  - name: language
    dtype: string
  splits:
  - name: test
    num_bytes: 1193682526.0
    num_examples: 500
  download_size: 1193578497
  dataset_size: 1193682526.0
configs:
- config_name: vision_bench_0701
  data_files:
  - split: test
    path: vision_bench_0701/test-*
- config_name: vision_bench_0617
  data_files:
  - split: test
    path: vision_bench_0617/test-*
---

# WildVision-Bench

We have two versions of Wildvision-Bench data
- `vision_bench_0617`: the selected 500 examples that best simulates the vision-arena elo ranking, same data in the paper.
- `vision_bench_0701`: the further filter and selected 500 examples by NSFW and manual selection. Leaderboard are still preparing.

## Evaluation
Please refer to our [Github](https://github.com/WildVision-AI/WildVision-Bench) for evaluation

If you want to evaluate your model, please use the `vision_bench_0617` version to fairly compare the performance with other models in the following leaderboard.

## Leaderboard (`vision_bench_0717`)

|              Model               | Score |    95% CI   | Win Rate | Reward | Much Better | Better |  Tie  | Worse | Much Worse | Avg Tokens |
| :------------------------------: | :---: | :---------: | :------: | :----: | :---------: | :----: | :---: | :---: | :--------: | :--------: |
|              gpt-4o              | 89.15 | (-1.9, 1.5) |  80.6%   |  56.4  |    255.0    | 148.0  |  14.0 |  72.0 |    11.0    |    142     |
|       gpt-4-vision-preview       | 79.78 | (-2.9, 2.2) |  71.8%   |  39.4  |    182.0    | 177.0  |  22.0 |  91.0 |    28.0    |    138     |
|            Reka-Flash            | 64.65 | (-2.6, 2.7) |  58.8%   |  18.9  |    135.0    | 159.0  |  28.0 | 116.0 |    62.0    |    168     |
|      claude-3-opus-20240229      | 62.03 | (-3.7, 2.8) |  53.0%   |  13.5  |    103.0    | 162.0  |  48.0 | 141.0 |    46.0    |    105     |
|            yi-vl-plus            | 55.05 | (-3.4, 2.3) |  52.8%   |  7.2   |     98.0    | 166.0  |  29.0 | 124.0 |    83.0    |    140     |
|    liuhaotian/llava-v1.6-34b     | 51.89 | (-3.4, 3.8) |  49.2%   |  2.5   |     90.0    | 156.0  |  26.0 | 145.0 |    83.0    |    153     |
|     claude-3-sonnet-20240229     |  50.0 |  (0.0, 0.0) |   0.2%   |  0.1   |     0.0     |  1.0   | 499.0 |  0.0  |    0.0     |    114     |
|     claude-3-haiku-20240307      | 37.83 | (-2.6, 2.8) |  30.6%   | -16.5  |     54.0    |  99.0  |  47.0 | 228.0 |    72.0    |     89     |
|        gemini-pro-vision         | 35.57 | (-3.0, 3.2) |  32.6%   | -21.0  |     80.0    |  83.0  |  27.0 | 167.0 |   143.0    |     68     |
| liuhaotian/llava-v1.6-vicuna-13b | 33.87 | (-2.9, 3.3) |  33.8%   | -21.4  |     62.0    | 107.0  |  25.0 | 167.0 |   139.0    |    136     |
| deepseek-ai/deepseek-vl-7b-chat  | 33.61 | (-3.3, 3.0) |  35.6%   | -21.2  |     59.0    | 119.0  |  17.0 | 161.0 |   144.0    |    116     |
|       THUDM/cogvlm-chat-hf       | 32.01 | (-2.2, 3.0) |  30.6%   | -26.4  |     75.0    |  78.0  |  15.0 | 172.0 |   160.0    |     61     |
| liuhaotian/llava-v1.6-vicuna-7b  | 26.41 | (-3.3, 3.1) |  27.0%   | -31.4  |     45.0    |  90.0  |  36.0 | 164.0 |   165.0    |    130     |
|        idefics2-8b-chatty        | 23.96 | (-2.2, 2.4) |  26.4%   | -35.8  |     44.0    |  88.0  |  19.0 | 164.0 |   185.0    |    135     |
|        Qwen/Qwen-VL-Chat         | 18.08 | (-1.9, 2.2) |  19.6%   | -47.9  |     42.0    |  56.0  |  15.0 | 155.0 |   232.0    |     69     |
|         llava-1.5-7b-hf          |  15.5 | (-2.4, 2.4) |  18.0%   | -47.8  |     28.0    |  62.0  |  25.0 | 174.0 |   211.0    |    185     |
|    liuhaotian/llava-v1.5-13b     | 14.43 | (-1.7, 1.6) |  16.8%   | -52.5  |     28.0    |  56.0  |  19.0 | 157.0 |   240.0    |     91     |
|        BAAI/Bunny-v1_0-3B        | 12.98 | (-2.0, 2.1) |  16.6%   | -54.4  |     23.0    |  60.0  |  10.0 | 164.0 |   243.0    |     72     |
|        openbmb/MiniCPM-V         | 11.95 | (-2.4, 2.1) |  13.6%   | -57.5  |     25.0    |  43.0  |  16.0 | 164.0 |   252.0    |     86     |
|     bczhou/tiny-llava-v1-hf      |  8.3  | (-1.6, 1.2) |  11.0%   | -66.2  |     16.0    |  39.0  |  15.0 | 127.0 |   303.0    |     72     |
| unum-cloud/uform-gen2-qwen-500m  |  7.81 | (-1.3, 1.7) |  10.8%   | -68.5  |     16.0    |  38.0  |  11.0 | 115.0 |   320.0    |     92     |


## Citation
```
@article{lu2024wildvision,
  title={WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences},
  author={Lu, Yujie and Jiang, Dongfu and Chen, Wenhu and Wang, William Yang and Choi, Yejin and Lin, Bill Yuchen},
  journal={arXiv preprint arXiv:2406.11069},
  year={2024}
}
```