OpenVLM MMBench V1.0 EN: leaderboard
MMBench v1.0 English test set from the OpenCompass OpenVLM Leaderboard (VLMEvalKit): multiple-choice questions across perception and reasoning abilities. This is the original question set, separate from the MMBench V1.1 boards. Accuracy in percent, higher is better.
Metric: Accuracy (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 231 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | InternVL3-78B | 88.8 | #361 |
| 2 | InternVL2.5-78B | 88.2 | #434 |
| 3 | InternVL3-38B | 87.7 | #413 |
| 4 | GPT-4.1 Mini | 86.9 | #363 |
| 5 | GPT-4.1 (2025-04-14) | 86.9 | #257 |
| 6 | Qwen 2 VL 72B | 86.9 | #450 |
| 7 | InternVL3-14B | 85.7 | #506 |
| 8 | Grok 2 (1212) | 85.3 | #502 |
| 9 | InternVL3-8B | 83.6 | #624 |
| 10 | Qwen 2.5 VL 7B | 83.2 | #641 |
| 11 | Qwen 2 VL 7B | 82.8 | #743 |
| 12 | Claude 3.5 Sonnet (20241022) | 82.6 | #302 |
| 13 | Gemma 3 27B | 82.3 | #606 |
| 14 | InternVL2-8B | 82 | #813 |
| 15 | MiniCPM-V-2.6 | 81.5 | #827 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=openvlm-mmbench-v1-0-en · How It Works · Data refreshed daily, snapshot 2026-11-05.