MMBench-V1.1

Version 1.1 of MMBench, an improved bilingual benchmark for assessing multi-modal capabilities of vision-language models through multiple-choice questions in both English and Chinese, providing systematic evaluation across diverse vision-language tasks.

Qwen3.6-35B-A3B from Alibaba Cloud / Qwen Team currently leads the MMBench-V1.1 leaderboard with a score of 0.928 across 18 evaluated AI models.

Paper

Alibaba Cloud / Qwen TeamQwen3.6-35B-A3B leads with 92.8%, followed by Alibaba Cloud / Qwen TeamQwen3.5-122B-A10B at 92.8% and Alibaba Cloud / Qwen TeamQwen3.5-27B at 92.6%.

Progress Over Time

Interactive timeline showing model performance evolution on MMBench-V1.1

State-of-the-art frontier
Open
Proprietary

MMBench-V1.1 Leaderboard

18 models
ContextCostLicense
1
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
35B
1
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
122B262K$0.40 / $3.20
3
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
27B262K$0.30 / $2.40
4
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
28B262K$0.60 / $3.60
5
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
35B262K$0.25 / $2.00
6
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
33B
7
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
236B262K$0.45 / $3.49
8
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
236B262K$0.30 / $1.49
9
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
31B262K$0.20 / $1.00
10
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
9B262K$0.18 / $2.09
11
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
31B262K$0.20 / $0.70
12
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
4B262K$0.10 / $1.00
13
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
4B262K$0.10 / $0.60
14
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
9B262K$0.08 / $0.50
15
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
7B
1616B
17
DeepSeek
DeepSeek
27B
183B
Notice missing or incorrect data?

FAQ

Common questions about MMBench-V1.1.

What is the MMBench-V1.1 benchmark?

Version 1.1 of MMBench, an improved bilingual benchmark for assessing multi-modal capabilities of vision-language models through multiple-choice questions in both English and Chinese, providing systematic evaluation across diverse vision-language tasks.

What is the MMBench-V1.1 leaderboard?

The MMBench-V1.1 leaderboard ranks 18 AI models based on their performance on this benchmark. Currently, Qwen3.6-35B-A3B by Alibaba Cloud / Qwen Team leads with a score of 0.928. The average score across all models is 0.868.

What is the highest MMBench-V1.1 score?

The highest MMBench-V1.1 score is 0.928, achieved by Qwen3.6-35B-A3B from Alibaba Cloud / Qwen Team.

How many models are evaluated on MMBench-V1.1?

18 models have been evaluated on the MMBench-V1.1 benchmark, with 0 verified results and 18 self-reported results.

Where can I find the MMBench-V1.1 paper?

The MMBench-V1.1 paper is available at https://arxiv.org/abs/2307.06281. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does MMBench-V1.1 cover?

MMBench-V1.1 is categorized under multimodal, reasoning, and vision. The benchmark evaluates multimodal models with multilingual support.

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