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LatestTencent2
TencentText / LLM

Tencent Releases 1.8B Model for Multilingual Translation

The 1.8 billion-parameter model from the Chinese tech giant is designed for high-quality translation across a wide range of language pairs.

May 11, 2026
NotableOther
Hunyuan-MT2 1.8B

Chinese technology firm Tencent has released Hunyuan-MT2, a new 1.8 billion-parameter model specialized for machine translation. This dense model, not a Mixture-of-Experts, represents a focused effort by the company to advance multilingual AI capabilities. The model and its weights are now available on Hugging Face.

Unlike general-purpose chatbots, Hunyuan-MT2 is a purpose-built tool designed for a single, complex task: translating text between multiple languages. While the specific language pairs are not detailed, its design suggests an aim for broad coverage and high-fidelity output, making it a potentially valuable component for developers building global applications.

This release adds a significant, specialized tool to the open-weights ecosystem. It provides an alternative to relying on large, proprietary translation APIs or fine-tuning generalist models for translation tasks. However, developers should note that the model is governed by a custom "Tencent Hunyuan Model License Agreement," which carries specific restrictions and should be reviewed carefully before use.

Sources

  • tencent/Hy-MT2-1.8B

    Hugging Face

    Visit
OlderSupertone Releases On-Device Multilingual TTS ModelSupertone · Text → Speech · 6 months agoNewerLightricks Releases LoRA for AI Lip-DubbingLightricks · Image → Video · 6 months ago

Get the model

Hugging Face

Specs

Parameters1.8B
Context window262K tokens
Size4.1 GB
PrecisionBF16
ArchitectureHunYuanDenseV1ForCausalLM
LicenseOTHER
Downloads25.8K
Likes1.3K

Can you run it?

Runs on just about anything.

  • BF16 (as published)

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    5.6 GB
  • 8-bit

    Any modern laptop · 8 GB RAM

    3.7 GB
  • 4-bit

    Any modern laptop · 8 GB RAM

    2.8 GB
Your machine
GGUF builds
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text / LLM

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