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Massive Multi-discipline Multimodal Understanding (MMMU)

A broad multimodal reasoning benchmark spanning charts, diagrams, tables, and academic visual question answering.

Data verified

Benchmark score on MMMU — July 23, 2026

BenchLM mirrors the published score view for MMMU. Qwen3.6 Plus leads the public snapshot at 86.0% , followed by Qwen3.5-122B-A10B (83.9%) and Qwen3.6-27B (82.9%). BenchLM does not use these results to rank models overall.

1Closed

Qwen3.6 Plus

Alibaba

qwen3-6-plus

86.0%
Overall 65.2Context 1M
2Open

Qwen3.5-122B-A10B

Alibaba

qwen3-5-122b-a10b

83.9%
Overall 60.56Context 262K
3Open

Qwen3.6-27B

Alibaba

qwen3-6-27b

82.9%
Overall 53.82Context 262K
9 modelsMultimodal & GroundedRefreshingDisplay onlyUpdated July 23, 2026

Benchmark score table (9 models)

Score
1
Qwen3.6 PlusAlibaba · Closed
86.0%
2
Qwen3.5-122B-A10BAlibaba · Open weight
83.9%
3
Qwen3.6-27BAlibaba · Open weight
82.9%
4
Qwen3.5-27BAlibaba · Open weight
82.3%
5
Qwen3.6-35B-A3BAlibaba · Open weight
81.7%
6
Qwen3.5-35B-A3BAlibaba · Open weight
81.4%
7
Command A+Cohere · Open weight
75.1%
8
Nemotron 3 Nano Omni 30B A3BNVIDIA · Open weight
70.8%
9
LFM2.5-VL-450MLiquidAI · Open weight
32.7%

The published MMMU snapshot places Qwen3.6 Plus first at 86.0%. The third row is 3.1 points behind. The broader top-10 range is 53.3 points, so the table still separates the published systems.

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

About MMMU

Year

2024

Tasks

Multimodal academic reasoning

Format

Image + text question answering

Difficulty

Frontier multimodal

MMMU is the base benchmark family behind later MMMU-Pro variants. It measures whether a model can answer expert-style questions that require combining visual understanding with domain knowledge and reasoning.

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

BenchLM freshness & provenance

Version

MMMU 2024

Refresh cadence

Annual

Staleness state

Refreshing

Question availability

Public benchmark set

RefreshingDisplay 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 MMMU measure?

A broad multimodal reasoning benchmark spanning charts, diagrams, tables, and academic visual question answering.

Which model scores highest on MMMU?

Qwen3.6 Plus by Alibaba currently leads with a score of 86.0% on MMMU.

How many models are evaluated on MMMU?

9 AI models have been evaluated on MMMU on BenchLM.

Compare Top Models on MMMU

Qwen3.6 Plus vs Qwen3.5-122B-A10BQwen3.5-122B-A10B vs Qwen3.6-27BQwen3.6-27B vs Qwen3.5-27BQwen3.5-27B vs Qwen3.6-35B-A3B
Last updated: July 23, 2026 · BenchLM version MMMU 2024

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