OpenVLM SEEDBench IMG - Text Understanding: leaderboard
SEED-Bench image Text Understanding accuracy from the OpenCompass OpenVLM Leaderboard (VLMEvalKit): four-option multiple-choice questions on reading and interpreting text in the image, one of the nine evaluation dimensions of the SEED-Bench image set. Accuracy in percent, higher is better.
Metric: Accuracy (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 226 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen 2 VL 72B | 79.8 | #450 |
| 2 | Qwen 2.5 VL 7B | 77.4 | #641 |
| 3 | InternVL3-78B | 75 | #361 |
| 4 | InternVL2-8B | 75 | #813 |
| 5 | Qwen 2 VL 7B | 75 | #743 |
| 6 | InternVL3-8B | 73.8 | #624 |
| 7 | Llama 3.2 90B Vision Instruct | 72.6 | #621 |
| 8 | Llama 3.2 11B Instruct | 71.4 | #1108 |
| 9 | GPT-4.1 Mini | 70.2 | #363 |
| 10 | InternVL3-38B | 70.2 | #413 |
| 11 | GPT-4.1 (2025-04-14) | 70.2 | #257 |
| 12 | InternVL3-14B | 69 | #506 |
| 13 | Grok 2 (1212) | 63.1 | #502 |
| 14 | Moonshot v1 8K | 61.9 | #622 |
| 15 | GPT-4.1 Nano | 60.7 | #730 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=openvlm-seedbench-img-text-understanding · How It Works · Data refreshed daily, snapshot 2026-11-05.