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BenchLM

VideoMMMU

A video extension of MMMU-style multimodal reasoning over expert questions grounded in temporal media.

Data verified 24 confirmed releases in the last 30 daysStart free brief

Benchmark score on VideoMMMU — August 22, 2026

We mirror the published score view for VideoMMMU. Qwen3.8 Max leads the public snapshot at 88.7%, followed by Gemini 3 Pro (87.6%) and dots3-note Preview (86.8%). We do not use these results to rank models overall.

1Open

Qwen3.8 Max

Alibaba

88.7%
Overall 78.95Context 1M
2Closed

Gemini 3 Pro

Google

87.6%
Overall 67.17Context 2M
3Open

dots3-note Preview

Dots Studio

86.8%
Overall 68.81Context 512K
11 modelsMultimodal & GroundedCurrentDisplay onlyUpdated August 22, 2026

Benchmark score table (11 models)

Score
1
Qwen3.8 MaxAlibaba · Open weight
88.7%
2
Gemini 3 ProGoogle · Closed
87.6%
3
dots3-note PreviewDots Studio · Open weight
86.8%
4
Kimi K2.5Moonshot AI · Open weight
86.6%
5
Qwen3.7 PlusAlibaba · Closed
85.4%
6
Qwen3.5 397BAlibaba · Open weight
84.7%
7
MiniMax M3MiniMax · Open weight
84.6%
8
Claude Opus 4.5Anthropic · Closed
84.4%
9
Qwen3.6-27BAlibaba · Open weight
84.4%
10
Qwen3.6 PlusAlibaba · Closed
84.0%
11
Qwen3.6-35B-A3BAlibaba · Open weight
83.7%

The published VideoMMMU snapshot places Qwen3.8 Max first at 88.7%. The third row is 1.9 points behind. The broader top-10 range is 4.7 points, so many of the published results sit in a relatively narrow band.

11 models have been evaluated on VideoMMMU. The benchmark falls in the Multimodal & Grounded category. This category carries a 12% weight in BenchLM.ai's overall scoring system. VideoMMMU is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.

About VideoMMMU

Year

2026

Tasks

Video-grounded expert reasoning

Format

Video + text reasoning

Difficulty

Frontier multimodal video reasoning

VideoMMMU tests whether multimodal reasoning skills extend from static images into temporal video understanding. It is useful for evaluating long-form visual reasoning rather than static scene recognition.

Qwen3.6 launch benchmarks

BenchLM freshness & provenance

Version

VideoMMMU 2026

Refresh cadence

Quarterly

Staleness state

Current

Question availability

Public benchmark set

CurrentDisplay only

BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.

FAQ

What does VideoMMMU measure?

A video extension of MMMU-style multimodal reasoning over expert questions grounded in temporal media.

Which model scores highest on VideoMMMU?

Qwen3.8 Max by Alibaba currently leads with a score of 88.7% on VideoMMMU.

How many models are evaluated on VideoMMMU?

11 AI models have been evaluated on VideoMMMU on BenchLM.

Compare Top Models on VideoMMMU

Qwen3.8 Max vs Gemini 3 ProGemini 3 Pro vs dots3-note Previewdots3-note Preview vs Kimi K2.5Kimi K2.5 vs Qwen3.7 Plus
Last updated: August 22, 2026 · BenchLM version VideoMMMU 2026

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