Benchmark
MMT-Bench
vision
multimodal
reasoning
general
multimodal
MMT-Bench is a comprehensive multimodal benchmark for evaluating Large Vision-Language Models towards multitask AGI. It comprises 31,325 meticulously curated multi-choice visual questions from various multimodal scenarios such as vehicle driving and embodied navigation, covering 32 core meta-tasks and 162 subtasks in multimodal understanding.
语言EN
满分1
参评模型4
模型排名
| 名次 | 模型 | 机构 | 分数 | 来源 |
|---|---|---|---|---|
| 1 | DeepSeek VL2 | DeepSeek | 63.6 | 来源 ↗ |
| 2 | Qwen2.5 VL 7B Instruct | Alibaba Cloud / Qwen Team | 63.6 | 来源 ↗ |
| 3 | DeepSeek VL2 Small | DeepSeek | 62.9 | 来源 ↗ |
| 4 | DeepSeek VL2 Tiny | DeepSeek | 53.2 | 来源 ↗ |