AI benchmarks and leaderboards are different things
Learn the difference between a benchmark, an evaluation run and a leaderboard, and use each to answer the right question.
LLM Stats
MMT-Bench
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.
Evaluation context and evidence
- Source
- LLM Stats
- Publisher
- Not recorded
- Benchmark release
- Not recorded
- Collected
- 2026-08-17
- Modality
- multimodal
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Original sources
Reported results 4
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| Qwen2.5 VL 7B Instruct | 0.636 | Not recorded | Not recorded | 2025-01-26 · model_announcement | LLM Stats |
| DeepSeek VL2 | 0.636 | Not recorded | Not recorded | 2024-12-13 · model_announcement | LLM Stats |
| DeepSeek VL2 Small | 0.629 | Not recorded | Not recorded | 2024-12-13 · model_announcement | LLM Stats |
| DeepSeek VL2 Tiny | 0.532 | Not recorded | Not recorded | 2024-12-13 · model_announcement | LLM Stats |