Tencent's Open-Source Hunyuan Models Outperform Google Translate in WMT2025
Tencent has released two specialized translation models, Hunyuan, as open source. The AI systems outperformed established services like Google Translate in the WMT2025 international comparison test, achieving the best results in 30 out of 31 tested language pairs.
Developed by Baidu, the Hunyuan models demonstrated significant improvements over Google Translate, showing enhancements of 15 to 65 percent. They also surpassed proprietary AI systems like GPT-4.1 and Gemini 2.5 Pro in most categories. The models support bidirectional translation between 33 languages, including widely spoken and less frequently digitized ones. Tencent describes a five-stage training process, including supervised learning, reinforcement learning, and 'Weak-to-Strong' reinforcement learning. Notably, with 7 billion parameters, the Tencent models are smaller than many foundational models they are compared to, requiring fewer resources and running on weaker hardware. Both models showed impressive improvements, achieving 4.7 percent better scores than the best available competitor model, Gemini 2.5 Pro. The Chimera model, one of the Hunyuan models, uses a fusion approach, combining multiple translation suggestions into an improved final translation. A focus is on translating between Mandarin Chinese and ethnic minority languages in China, supporting bidirectional translation between Chinese and Kazakh, Uyghur, Mongolian, and Tibetan.
The Hunyuan models, released as open source on Hugging Face and GitHub, offer significant advancements in translation technology. With their impressive performance and efficiency, these models could reshape the landscape of language translation.
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