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

• URL: http://arxiv.org/abs/2605.22064v2
• Date: Mon, 25 May 2026 03:05:16 GMT
• Title: Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild
• Abstract summary: Hy-MT2 delivers outstanding performance across general, real-world business, domain-specific, and instruction-following translation tasks.<n>The 7B and 30B models outperform open-source models such as DeepSeek-V4-Pro and Kimi K2.6 in fast-thinking mode.<n>The lightweight 1.8B model requires only 440 MB of storage and achieves a 1.5x inference speedup.
• Score: 28.747270164782673
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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