Tencent Hunyuan open-sources Hy-MT2 translation models in 1.8B, 7B and 30B-A3B sizes
Tencent Hunyuan has open-sourced the Hy-MT2 family of multilingual translation models on Hugging Face and ModelScope, spanning 1.8B, 7B and 30B-A3B (MoE) sizes, covering 33 languages and emphasizing multilingual translation instruction-following. The team claims the 7B and 30B-A3B models outperform open-source models such as DeepSeek-V4-Pro and Kimi K2.6 in "fast-thinking" mode, while the 1.8B model beats mainstream commercial APIs from providers such as Microsoft and Doubao overall — claims based on its own evaluations and not yet independently verified. The release also open-sources the IFMTBench instruction-following benchmark and a Hy-MT2-Translator Skill, and uses AngelSlim 1.25-bit quantization to shrink the 1.8B model to about 440 MB with a 1.5x inference speedup; Tencent Hy also announced a WMT26 partnership with sponsored awards for teams using Hy-MT models.
Compressing translation models to on-device size while keeping weights open could push more localization and multilingual work toward self-hosted deployments.
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🖥️ Official Website | 💬 GitHub | 🪡 AngelSlim | 📚 Hy-MT2 Report
Model Introduction
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. For on-device deployment, AngelSlim 1.25-bit extreme quantization reduces the storage requirement of the 1.8B model to only 440 MB and improves inference speed by 1.5x. 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-A3B 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.
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