Hunyuan-MT1.5-1.8B-MNN

HY-MT1.5-1.8B-MNN

This is a 4-bit quantized MNN version of Tencent's HY-MT1.5-1.8B translation model, optimized for Apple Silicon (iOS/macOS) edge inference.

Model Description

HY-MT1.5-1.8B is a lightweight version of the HY-MT1.5 series, specifically designed for edge devices:

• 36 Language Support: Extended language coverage
• Edge Optimized: Designed for mobile and edge deployment
• Terminology Intervention: Custom terminology control during translation
• Context-Aware Translation: Improved accuracy with context understanding
• Industry-Leading Performance: Best-in-class for its parameter size

Quantization Details

Hardware Acceleration

Optimized for Apple Silicon with:

• ✅ INT8 Dot Product (i8sdot)
• ✅ FP16 Operations
• ✅ INT8 Matrix Multiply (i8mm)
• ✅ Scalable Matrix Extension 2 (sme2)
• ✅ Metal GPU Acceleration
• ✅ Apple Neural Engine (ANE) compatible

Files

├── llm.mnn              # Model structure (576 KB)
├── llm.mnn.weight       # Quantized weights (1.07 GB)
├── tokenizer.txt        # Tokenizer vocabulary
├── llm_config.json      # MNN runtime config
├── config.json          # Model config
├── model_info.json      # Model metadata
└── export_args.json     # Conversion parameters

Usage

With MNN LLM Demo

# Clone MNN and build llm_demo
git clone https://github.com/alibaba/MNN.git
cd MNN && mkdir build && cd build
cmake .. -DMNN_BUILD_LLM=ON -DMNN_LOW_MEMORY=ON
make -j8 llm_demo

# Run inference
cd /path/to/HY-MT1.5-1.8B-MNN
./llm_demo ./

Example

User: Translate into English: 今天天氣很好
A: The weather is very nice today.

Prompt Templates

# Basic translation
Translate into {language}:
{text}

# With terminology
Translate into {language}, using terms: {terms}
{text}

# With context
Context: {context}
Translate into {language}:
{text}

Performance

iOS Integration

This model is ideal for iOS apps. Example using MNN iOS SDK:

import MNN

let llm = LLM(modelPath: "HY-MT1.5-1.8B-MNN")
let result = llm.generate("Translate into English: 今天天氣很好")
print(result) // "The weather is very nice today."

Conversion Info

• Tool: MNN llmexport.py
• MNN Version: 3.0.0
• Conversion Date: 2025-12-31
• Source Format: HuggingFace safetensors

Related Models

• HY-MT1.5-7B-MNN - Larger version for higher quality
• Hunyuan-MT-7B-MNN - Original WMT25 version

Why Choose 1.8B?

Choose 1.8B for: Mobile apps, real-time translation, resource-constrained devices

Choose 7B for: Desktop apps, highest translation quality, batch processing

License

This model inherits the license from the original HY-MT1.5-1.8B model.

Acknowledgments

• Tencent Hunyuan Team for the original model
• Alibaba MNN Team for the inference framework