Video Understanding Benchmark

MMVU

MMVU - multi-modal video understanding benchmark evaluating comprehension across diverse video types.

Category

Video Understanding

Score type

percent

Scale

relative

higher is better

Models tested

7

What is MMVU?

MMVU is a benchmark for understanding videos instead of static images. The official description says: "MMVU - multi-modal video understanding benchmark evaluating comprehension across diverse video types". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

MMVU measures understanding videos instead of static images. In detail, it checks:

  • following events, actions and their order across time
  • answering questions about long videos (with and without subtitles)
  • reasoning about what happened and why, not just single frames
  • integrating audio/subtitle context with the visual stream

How to read the score

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: MMVU - multi-modal video understanding benchmark evaluating comprehension across diverse video types.

Frequently asked questions

What is the MMVU benchmark?

MMVU is a benchmark for understanding videos instead of static images. The official description says: 'MMVU - multi-modal video understanding benchmark evaluating comprehension across diverse video types'. Below we describe in simple words what benchmarks of this type generally examine.

What does MMVU test?

MMVU mainly measures understanding videos instead of static images. Concretely, it checks: following events, actions and their order across time; answering questions about long videos (with and without subtitles); reasoning about what happened and why, not just single frames.

How is the MMVU score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Where do I get MMVU data and scores?

The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/mmvu/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 7 models tested

Reset
# Model Score Date Source Verified
1 Kimi K3
Moonshot AI
82.1%
18.08.2026 Report Verified
2 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
74.7%
01.02.2026 Report Verified
3 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
73.3%
01.02.2026 Report Unverified
4 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
72.3%
01.02.2026 Report Unverified
5 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
71.1%
01.02.2026 Report Unverified
6 Qwen3.5-4B
Qwen
64.9%
01.02.2026 Report Verified
7 LFM3-VL-2B
LiquidAI
52.9%
— Report Verified

What now?

You've seen how models score on MMVU — here's what to do next.