---
title: "TENCENT's Open-Source On-Device Mobile Model Targets Offline Translation Scenarios"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/284547711.md"
description: "Disrupting the landscape of the entire translation sector"
datetime: "2026-04-29T10:35:00.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/284547711.md)
  - [en](https://longbridge.com/en/news/284547711.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/284547711.md)
---

# TENCENT's Open-Source On-Device Mobile Model Targets Offline Translation Scenarios

Author | Huang Yu

TENCENT is accelerating the deployment of large models in real-world scenarios, with translation now taking center stage.

On April 29, TENCENT Hunyuan launched and open-sourced Hy-MT1.5-1.8B-1.25bit, an extremely quantized and compressed version of its translation model. This release compresses the large translation model, which supports 33 languages, down to 440MB. It can run directly on mobile devices locally without an internet connection, requiring only a download.

In addition to open-sourcing the model weights, TENCENT Hunyuan also released a practical "TENCENT Hunyuan Translation Demo," specially adapted for a "background word-selection mode."

Whether checking emails locally or browsing web pages, Hunyuan Translation is available on demand.

After experiencing the TENCENT Hunyuan Translation Demo, Wall Street Insights found that this version requires neither an internet connection nor a subscription. Currently, domestic users can download it from the ModelScope community, but it runs only on Android devices; iOS support has not yet been adapted.

TENCENT stated that the TENCENT Hunyuan Translation Demo processes everything locally, involving no collection or uploading of personal information, offering permanent use after a single download.

If its actual translation capabilities can rival mainstream tools like Youdao Translator and Google Translate, while maintaining the advantages of being permanently free, running offline locally, and not uploading private data, TENCENT's move will undoubtedly disrupt the landscape of the entire translation sector.

This offline translation model from TENCENT Hunyuan is built upon the Hunyuan Translation Large Model, Hy-mt1.5. Hy-mt1.5 is a professional large translation model developed by the TENCENT Hunyuan team, with 1.8 billion parameters. It natively supports 33 languages, 5 dialects/minority-Han language pairs, and 1,056 translation directions.

TENCENT revealed that Hy-mt1.5 achieves translation quality comparable to commercial translation APIs and large models in the 235-billion-parameter class. In rigorous evaluation benchmarks, its translation quality has also surpassed mainstream systems such as Google Translate.

In actual business scenarios, the Hunyuan team found that the original 1.8B model still occupied 3.3GB of memory even at FP16 precision, which remained too large and slow for mobile phone memory, necessitating quantization and compression.

Therefore, targeting different mobile users, TENCENT specifically introduced two extreme quantization and compression schemes: 2-bit and 1.25-bit.

Amid the current explosion of AI applications, companies are striving to find suitable niche scenarios for their respective large models.

Besides TENCENT Hunyuan, major domestic and international tech giants have long been competing in the field of offline AI translation on mobile devices. Many have launched lightweight, open-source translation models capable of running offline on edge devices, including Alibaba, Google, and Meta.

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