Megrez-Omni Technical Report

Li, Boxun, Li, Yadong, Li, Zhiyuan, Liu, Congyi, Liu, Weilin, Niu, Guowei, Tan, Zheyue, Xu, Haiyang, Yao, Zhuyu, Yuan, Tao, Zhou, Dong, Zhuang, Yueqing, Yan, Shengen, Dai, Guohao, Wang, Yu

arXiv.org Artificial Intelligence 

In this work, we present the Megrez models, comprising a language model (Megrez-3B-Instruct) and a multimodal model (Megrez-3B-Omni). These models are designed to deliver fast inference, compactness, and robust edge-side intelligence through a software-hardware co-design approach. Megrez-3B-Instruct offers several advantages, including high accuracy, high speed, ease of use, and a wide range of applications. Building on Megrez-3B-Instruct, Megrez-3B-Omni is an on-device multimodal understanding LLM that supports image, text, and audio analysis. It achieves state-of-the-art accuracy across all three modalities and demonstrates strong versatility and robustness, setting a new benchmark for multimodal AI models.