轻量级多模态模型Megrez-3B-Omni，支持设备端图文音理解
Megrez-Omni Technical Report
- 软硬协同设计，实现快速推理与小体积部署
- 单模型在三类模态上均达当前最佳性能
- 适合边缘设备部署，兼顾精度与效率
本文提出Megrez系列模型，包括语言模型Megrez-3B-Instruct和多模态模型Megrez-3B-Omni。通过软硬件协同设计，实现快速推理、模型紧凑与边缘智能的高效结合。Megrez-3B-Instruct具备高准确率、高速度和易用性，应用广泛。在此基础上构建的Megrez-3B-Omni是支持图像、文本、音频分析的设备端多模态大模型，在三类模态上均达到当前最优性能，展现出强泛化能力与鲁棒性，为多模态AI在边缘侧落地树立新标杆。
原文摘要 · Abstract (English)
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.
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