MMAU Sound
A subset of the MMAU benchmark focused specifically on environmental sound understanding and reasoning tasks. Part of a comprehensive multimodal audio understanding benchmark that evaluates models on expert-level knowledge and complex reasoning across environmental sound clips.
Progress Over Time
Interactive timeline showing model performance evolution on MMAU Sound
State-of-the-art frontier
Open
Proprietary
MMAU Sound Leaderboard
1 models
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | 7B | — | — |
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FAQ
Common questions about MMAU Sound
A subset of the MMAU benchmark focused specifically on environmental sound understanding and reasoning tasks. Part of a comprehensive multimodal audio understanding benchmark that evaluates models on expert-level knowledge and complex reasoning across environmental sound clips.
The MMAU Sound paper is available at https://arxiv.org/abs/2410.19168. This paper provides detailed information about the benchmark methodology, dataset creation, and evaluation criteria.
The MMAU Sound leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Qwen2.5-Omni-7B by Alibaba Cloud / Qwen Team leads with a score of 0.679. The average score across all models is 0.679.
The highest MMAU Sound score is 0.679, achieved by Qwen2.5-Omni-7B from Alibaba Cloud / Qwen Team.
1 models have been evaluated on the MMAU Sound benchmark, with 0 verified results and 1 self-reported results.
MMAU Sound is categorized under audio, multimodal, and reasoning. The benchmark evaluates multimodal models.