Introduction
Tencent’s Hunyuan group has launched Hunyuan-MT-7B (a translation mannequin) and Hunyuan-MT-Chimera-7B (an ensemble mannequin). Each fashions are designed particularly for multilingual machine translation and had been launched at the side of Tencent’s participation within the WMT2025 Normal Machine Translation shared process, the place Hunyuan-MT-7B ranked first in 30 out of 31 language pairs.
Mannequin Overview
Hunyuan-MT-7B
- A 7B parameter translation mannequin.
- Helps mutual translation throughout 33 languages, together with Chinese language ethnic minority languages corresponding to Tibetan, Mongolian, Uyghur, and Kazakh.
- Optimized for each high-resource and low-resource translation duties, reaching state-of-the-art outcomes amongst fashions of comparable dimension.
Hunyuan-MT-Chimera-7B
- An built-in weak-to-strong fusion mannequin.
- Combines a number of translation outputs at inference time and produces a refined translation utilizing reinforcement studying and aggregation strategies.
- Represents the first open-source translation mannequin of this kind, enhancing translation high quality past single-system outputs.
Coaching Framework
The fashions had been educated utilizing a five-stage framework designed for translation duties:
- Normal Pre-training
- 1.3 trillion tokens masking 112 languages and dialects.
- Multilingual corpora assessed for data worth, authenticity, and writing model.
- Variety maintained by way of disciplinary, business, and thematic tagging techniques.
- MT-Oriented Pre-training
- Monolingual corpora from mC4 and OSCAR, filtered utilizing fastText (language ID), minLSH (deduplication), and KenLM (perplexity filtering).
- Parallel corpora from OPUS and ParaCrawl, filtered with CometKiwi.
- Replay of normal pre-training knowledge (20%) to keep away from catastrophic forgetting.
- Supervised Effective-Tuning (SFT)
- Stage I: ~3M parallel pairs (Flores-200, WMT take a look at units, curated Mandarin–minority knowledge, artificial pairs, instruction-tuning knowledge).
- Stage II: ~268k high-quality pairs chosen by way of automated scoring (CometKiwi, GEMBA) and guide verification.
- Reinforcement Studying (RL)
- Algorithm: GRPO.
- Reward features:
- XCOMET-XXL and DeepSeek-V3-0324 scoring for high quality.
- Terminology-aware rewards (TAT-R1).
- Repetition penalties to keep away from degenerate outputs.
- Weak-to-Robust RL
- A number of candidate outputs generated and aggregated by way of reward-based output
- Utilized in Hunyuan-MT-Chimera-7B, enhancing translation robustness and decreasing repetitive errors.
Benchmark Outcomes
Computerized Analysis
- WMT24pp (English⇔XX): Hunyuan-MT-7B achieved 0.8585 (XCOMET-XXL), surpassing bigger fashions like Gemini-2.5-Professional (0.8250) and Claude-Sonnet-4 (0.8120).
- FLORES-200 (33 languages, 1056 pairs): Hunyuan-MT-7B scored 0.8758 (XCOMET-XXL), outperforming open-source baselines together with Qwen3-32B (0.7933).
- Mandarin⇔Minority Languages: Scored 0.6082 (XCOMET-XXL), increased than Gemini-2.5-Professional (0.5811), exhibiting important enhancements in low-resource settings.
Comparative Outcomes
- Outperforms Google Translator by 15–65% throughout analysis classes.
- Outperforms specialised translation fashions corresponding to Tower-Plus-9B and Seed-X-PPO-7B regardless of having fewer parameters.
- Chimera-7B provides ~2.3% enchancment on FLORES-200, significantly in Chinese language⇔Different and non-English⇔non-Chinese language translations.
Human Analysis
A customized analysis set (masking social, medical, authorized, and web domains) in contrast Hunyuan-MT-7B with state-of-the-art fashions:
- Hunyuan-MT-7B: Avg. 3.189
- Gemini-2.5-Professional: Avg. 3.223
- DeepSeek-V3: Avg. 3.219
- Google Translate: Avg. 2.344
This reveals that Hunyuan-MT-7B, regardless of being smaller at 7B parameters, approaches the standard of a lot bigger proprietary fashions.
Case Research
The report highlights a number of real-world instances:
- Cultural References: Accurately interprets “小红薯” because the platform “REDnote,” not like Google Translate’s “candy potatoes.”
- Idioms: Interprets “You’re killing me” as “你真要把我笑死了” (expressing amusement), avoiding literal misinterpretation.
- Medical Phrases: Interprets “uric acid kidney stones” exactly, whereas baselines generate malformed outputs.
- Minority Languages: For Kazakh and Tibetan, Hunyuan-MT-7B produces coherent translations, the place baselines fail or output nonsensical textual content.
- Chimera Enhancements: Provides enhancements in gaming jargon, intensifiers, and sports activities terminology.
Conclusion
Tencent’s launch of Hunyuan-MT-7B and Hunyuan-MT-Chimera-7B establishes a brand new normal for open-source translation. By combining a fastidiously designed coaching framework with specialised give attention to low-resource and minority language translation, the fashions obtain high quality on par with or exceeding bigger closed-source techniques. The launch of those 2 fashions supplies the AI analysis group with accessible, high-performance instruments for multilingual translation analysis and deployment.
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