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Hunyuan(@TXhunyuan)

We're open-sourcing Hy-MT1.5-1.8B-1.25bit — a 440MB translation model that runs fully offline on you...

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We're open-sourcing Hy-MT1.5-1.8B-1.25bit — a 440MB translation model that runs fully offline on you...

TL;DR · AI 摘要

腾讯混元开源 Hy-MT1.5-1.8B-1.25bit 翻译模型:仅440MB,支持33种语言+5种方言,1.25-bit量化无损精度,手机端全离线运行,性能超越Google Translate及部分商用API。

核心要点

  • 25-bit超低比特量化实现440MB体积,较FP16压缩7.5倍且零精度损失
  • 支持1056个翻译方向,覆盖藏语、蒙古语等少数民族语言
  • 在标准机器翻译基准上媲美235B参数大模型和商业API

结构提纲

按章节快速跳转。

  1. 宣布开源Hy-MT1.5-1.8B-1.25bit翻译模型及其核心指标。

  2. 通过创新量化方案将模型从3.3GB压缩至440MB,速度提升10%,精度无损。

  3. 支持33种语言、5种方言、1056个翻译方向,含藏语、蒙古语等稀缺语种。

  4. 在主流MT基准上超越Google Translate,已落地多个腾讯产品并获30项国际竞赛冠军。

  5. 提供Android APK、Hugging Face模型页、GitHub代码库及论文链接。

思维导图

用一张图看清主题之间的关系。

查看大纲文本(无障碍 / 无 JS 友好)
  • Hy-MT1.5-1.8B-1.25bit
    • 核心技术
      • 1.25-bit量化(无损)
      • 1.8B参数规模
    • 能力特性
      • 33语言+5方言+1056方向
      • 离线手机端运行(440MB)
    • 实证表现
      • 超越Google Translate
      • 媲美235B模型/商用API
      • 30项国际MT竞赛冠军

金句 / Highlights

值得收藏与分享的关键句。

  • By quantizing to 1.25-bit, memory drops from 3.3GB (FP16) to 440MB — 25% smaller and ~10% faster than prior 1.67-bit approaches, with no accuracy loss.

    正文段落1

    ⬇︎ 下载 PNG𝕏 分享到 X
  • Covers 33 languages, 5 dialects, and 1,056 translation directions including minority languages like Tibetan and Mongolian.

    正文段落1

    ⬇︎ 下载 PNG𝕏 分享到 X
  • At 1.8B parameters, it matches commercial translation APIs and 235B-scale models on standard benchmarks.

    正文段落1

    ⬇︎ 下载 PNG𝕏 分享到 X
  • Our translation model has won 30 first-place rankings in international MT competitions and is already deployed across multiple Tencent products.

    正文段落1

    ⬇︎ 下载 PNG𝕏 分享到 X
#机器翻译#模型量化#开源模型#端侧AI#腾讯
打开原文

At 1.8B parameters, it matches commercial translation APIs and 235B-scale models on standard benchmarks. By https://t.co/4kgWldn4p1" / X

Image 1: Square profile picture

Tencent Hy

@TencentHunyuan

We're open-sourcing Hy-MT1.5-1.8B-1.25bit — a 440MB translation model that runs fully offline on your phone, supports 33 languages, and outperforms Google Translate. At 1.8B parameters, it matches commercial translation APIs and 235B-scale models on standard benchmarks. By quantizing to 1.25-bit, memory drops from 3.3GB (FP16) to 440MB — 25% smaller and ~10% faster than prior 1.67-bit approaches, with no accuracy loss. Covers 33 languages, 5 dialects, and 1,056 translation directions including minority languages like Tibetan and Mongolian. Our translation model has won 30 first-place rankings in international MT competitions and is already deployed across multiple Tencent products.Image 2: 🏆Image 3: 📲Demo APK (Android): huggingface.co/AngelSlim/Hy-MImage 4: 🤗Hugging Face:: huggingface.co/AngelSlim/Hy-MImage 5: 🔗GitHub: github.com/tencent/AngelSImage 6: 📄Paper: arxiv.org/abs/2601.07892

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1:55 PM · Apr 29, 2026

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