Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild

Mao Zheng; Zheng Li; Tao Chen; Bo Lv; Mingrui Sun; Mingyang Song; Jinlong Song; Hong Huang; Decheng Wu; Hai Wang; Yifan Song; Yanfeng Chen; Guanwei Zhang

arXiv · 2605.22064

Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild

Mao Zheng·Zheng Li·Tao Chen·Bo Lv·Mingrui Sun·Mingyang Song·Jinlong Song·Hong Huang·Decheng Wu·Hai Wang·Yifan Song·Yanfeng Chen·Guanwei Zhang

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Abstract

Hy-MT2 is a family of fast-thinking multilingual translation models designed for complex real-world scenarios. It includes three model sizes: 1.8B, 7B, and 30B-A3B (MoE), all of which support translation among 33 languages and effectively follow translation instructions in multiple languages. Multi-dimensional evaluations show that Hy-MT2 delivers outstanding performance across general, real-world business, domain-specific, and instruction-following translation tasks. The 7B and 30B models outperform open-source models such as DeepSeek-V4-Pro and Kimi K2.6 in fast-thinking mode, while the lightweight 1.8B model also surpasses mainstream commercial APIs from providers such as Microsoft and Doubao overall. Moreover, when paired with AngelSlim's 1.25-bit extreme quantization for on-device deployment, the lightweight 1.8B model requires only 440 MB of storage and achieves a 1.5x inference speedup.

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Mao Zheng, Zheng Li, Tao Chen, Bo Lv, Mingrui Sun, Mingyang Song, Jinlong Song, Hong Huang, Decheng Wu, Hai Wang, Yifan Song, Yanfeng Chen, Guanwei Zhang. 2026-05-21. Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild. https://arxiv.org/abs/2605.22064

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