Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Instruction Following | IFBench | IFBench Score50.67 | 56 | |
| Machine Translation | WMT General 2025 | XCOMET-XXL Score63.86 | 31 | |
| Machine Translation | Mandarin ⇔ Minority (General) | XCOMET-XXL Score62.44 | 30 | |
| Machine Translation | DomainMTBench | XCOMET (Finance)97.08 | 30 | |
| Machine Translation | WildMTBench | XCOMET90.28 | 30 | |
| Machine Translation | FLORES-200 ZH ⇔ XX | XCOMET-XXL89.83 | 30 | |
| Machine Translation | FLORES-200 XX ⇔ XX | XCOMET-XXL Score87.47 | 30 | |
| Translation instruction-following | IFMTBench | Simple Score90.2 | 18 | |
| Instruction Following | IFEval | IFEval Score89.8 | 18 | |
| Multi-turn Instruction Following | Multi-IF | Turn 1 Score90.1 | 18 |