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Megrez-Omni Technical Report
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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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Cited by 2 Pith papers
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Megrez2 Technical Report
A 3B-parameter Mixture-of-Experts model with experts shared across layers matches or approaches larger models on several benchmarks at much lower storage cost.
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Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models
A survey organizes multimodal reasoning research into a staged roadmap and proposes native large multimodal reasoning models that unify perception, generation, and agentic planning.
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