MAVERIX
MAVERIX (Multimodal Audio-Visual Evaluation Reasoning Index) evaluates multimodal models on tasks that demand tight integration of video and audio information. It features challenges like situational awareness and social sentiment analysis where the answer cannot be reliably determined from a single modality, rigorously testing joint audio-visual understanding.
Nova 2 Omni from Amazon currently leads the MAVERIX leaderboard with a score of 0.666 across 1 evaluated AI models.
What MAVERIX measures
MAVERIX is a multimodal benchmark that evaluates large language models on video, vision, multimodal, reasoning, and audio tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.7, with the leader reaching 0.7.
Compare leaders on the best AI for video, best AI for vision, best AI for multimodal, best AI for reasoning and best AI for audio leaderboards.
Publication
- Paper
- MAVERIX: Multimodal Audio-Visual Evaluation and Recognition IndeX
- Authors
- Liuyue Xie, Avik Kuthiala, George Z. Wei, Ce Zheng, and 11 others
- Published
- arXiv
- 2503.21699
Abstract
We introduce MAVERIX (Multimodal audiovisual Evaluation and Recognition IndeX), a unified benchmark to probe the video understanding in multimodal LLMs, encompassing video, audio, text inputs with human performance baselines. Although recent advancements in models with vision and audio understanding capabilities have shown substantial progress, the field lacks a standardized evaluation framework to thoroughly assess their cross-modality comprehension performance. MAVERIX curates 2,556 questions from 700 videos, in the form of both multiple-choice and open-ended formats, explicitly designed to evaluate multimodal models through questions that necessitate tight integration of video and audio information, spanning a broad spectrum of agentic scenarios. MAVERIX uniquely provides models with audiovisual questions, closely mimicking the multimodal perceptual experiences available to humans during inference and decision-making processes. To our knowledge, MAVERIX is the first benchmark aimed explicitly at assessing comprehensive audiovisual integration in such granularity. Experiments with state-of-the-art models, including Qwen 2.5 Omni and Gemini 2.5 Flash-Lite, show performance around 64% accuracy, while human experts reach near-ceiling performance of 92.8%, exposing a substantial gap to human-level comprehension. With standardized evaluation protocols, a rigorously annotated pipeline, and a public toolkit, MAVERIX establishes a challenging testbed for advancing audiovisual multimodal intelligence.
Nova 2 Omni leads with 66.6%.
Progress Over Time
Interactive timeline showing model performance evolution on MAVERIX
MAVERIX Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Amazon | — | — | — |
FAQ
Common questions about MAVERIX.
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