Video Understanding Benchmark

MVBench

MVBench - comprehensive multi-modal video understanding benchmark.

Category

Video Understanding

Score type

percent

Scale

100%

higher is better

Models tested

9

What is MVBench?

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

What does it test?

MVBench 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: MVBench - comprehensive multi-modal video understanding benchmark.

Frequently asked questions

What is the MVBench benchmark?

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

What does MVBench test?

MVBench 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 MVBench score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get MVBench 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/mvbench/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 9 models tested

Reset
# Model Score Date Source Verified
1 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
76.6%
01.02.2026 Report Verified
2 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
75.5%
22.04.2026 Qwen Team (official model card) Verified
3 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
75.2%
01.02.2026 Report Unverified
4 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
74.8%
16.04.2026 Qwen Team (official model card - comparison) Unverified
5 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
74.6%
16.04.2026 Qwen Team (official model card) Verified
6 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
74.6%
16.04.2026 Qwen Team (official model card - comparison) Unverified
7 Qwen3.5-4B
Qwen
71.2%
01.02.2026 Report Verified
8 LFM3-VL-2B
LiquidAI
69.4%
— Report Verified
9 LFM3-Omni-2B
LiquidAI
58.03%
— Report Verified

What now?

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