OpusMT-En-Zh: Optimized for Qualcomm Devices
OpusMT English to Chinese translation model is a state-of-the-art neural machine translation system designed for translating English text into Chinese. This model is based on the Marian transformer architecture and has been optimized for edge inference by splitting into encoder and decoder components with modified attention mechanisms. It exhibits robust performance for real-world translation tasks, making it highly reliable for practical applications. The model supports input sequences up to 256 tokens and can generate Chinese translations with high accuracy.
This is based on the implementation of OpusMT-En-Zh found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.
Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.
Getting Started
There are two ways to deploy this model on your device:
Option 1: Download Pre-Exported Models
Below are pre-exported model assets ready for deployment.
| Runtime | Precision | Chipset | SDK Versions | Download |
|---|---|---|---|---|
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| PRECOMPILED_QNN_ONNX | float | Snapdragon® X2 Elite | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| PRECOMPILED_QNN_ONNX | float | Snapdragon® X Elite | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Gen 3 Mobile | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS8550 (Proxy) | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS9075 | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite Gen 5 Mobile | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® X2 Elite | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® X Elite | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Gen 3 Mobile | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8550 (Proxy) | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® SA8775P | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite For Galaxy Mobile | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® SA7255P | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® SA8295P | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS9075 | QAIRT 2.43 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8450 (Proxy) | QAIRT 2.43 | Download |
For more device-specific assets and performance metrics, visit OpusMT-En-Zh on Qualcomm® AI Hub.
Option 2: Export with Custom Configurations
Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:
- Custom weights (e.g., fine-tuned checkpoints)
- Custom input shapes
- Target device and runtime configurations
This option is ideal if you need to customize the model beyond the default configuration provided here.
See our repository for OpusMT-En-Zh on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.text_generation
Model Stats:
- Model checkpoint: Helsinki-NLP/opus-mt-en-zh
- Input resolution: 256 tokens (English text)
- Max input sequence length: 256 tokens
- Max output sequence length: 256 tokens
- Number of parameters (OpusMTEncoder): ~74M
- Model size (OpusMTEncoder) (float): ~280 MB
- Number of parameters (OpusMTDecoder): ~74M
- Model size (OpusMTDecoder) (float): ~280 MB
- Number of encoder layers: 6
- Number of decoder layers: 6
- Attention heads: 8
- Hidden dimension: 512
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| OpusMTDecoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.179 ms | 1 - 11 MB | NPU |
| OpusMTDecoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® X2 Elite | 1.712 ms | 160 - 160 MB | NPU |
| OpusMTDecoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® X Elite | 3.161 ms | 160 - 160 MB | NPU |
| OpusMTDecoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Gen 3 Mobile | 2.698 ms | 0 - 10 MB | NPU |
| OpusMTDecoder | PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS8550 (Proxy) | 3.446 ms | 12 - 14 MB | NPU |
| OpusMTDecoder | PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS9075 | 3.968 ms | 12 - 27 MB | NPU |
| OpusMTDecoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.341 ms | 0 - 12 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.166 ms | 1 - 11 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Snapdragon® X2 Elite | 2.209 ms | 12 - 12 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Snapdragon® X Elite | 3.108 ms | 12 - 12 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Gen 3 Mobile | 2.887 ms | 12 - 20 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8275 (Proxy) | 6.733 ms | 12 - 20 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8550 (Proxy) | 3.398 ms | 4 - 6 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Qualcomm® SA8775P | 4.238 ms | 12 - 20 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS9075 | 3.955 ms | 12 - 26 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8450 (Proxy) | 4.773 ms | 12 - 21 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Qualcomm® SA7255P | 6.733 ms | 12 - 20 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Qualcomm® SA8295P | 4.879 ms | 12 - 17 MB | NPU |
| OpusMTDecoder | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.559 ms | 2 - 15 MB | NPU |
| OpusMTEncoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.767 ms | 0 - 10 MB | NPU |
| OpusMTEncoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® X2 Elite | 1.855 ms | 107 - 107 MB | NPU |
| OpusMTEncoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® X Elite | 3.979 ms | 107 - 107 MB | NPU |
| OpusMTEncoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Gen 3 Mobile | 2.657 ms | 0 - 7 MB | NPU |
| OpusMTEncoder | PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS8550 (Proxy) | 3.775 ms | 0 - 114 MB | NPU |
| OpusMTEncoder | PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS9075 | 4.733 ms | 16 - 18 MB | NPU |
| OpusMTEncoder | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.301 ms | 0 - 11 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.738 ms | 0 - 10 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Snapdragon® X2 Elite | 2.21 ms | 0 - 0 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Snapdragon® X Elite | 3.947 ms | 0 - 0 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Gen 3 Mobile | 2.644 ms | 0 - 7 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8275 (Proxy) | 12.716 ms | 0 - 7 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8550 (Proxy) | 3.656 ms | 0 - 2 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Qualcomm® SA8775P | 4.743 ms | 0 - 9 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS9075 | 4.58 ms | 0 - 8 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8450 (Proxy) | 5.047 ms | 0 - 9 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Qualcomm® SA7255P | 12.716 ms | 0 - 7 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Qualcomm® SA8295P | 5.542 ms | 0 - 5 MB | NPU |
| OpusMTEncoder | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.24 ms | 0 - 13 MB | NPU |
License
- The license for the original implementation of OpusMT-En-Zh can be found here.
References
Community
- Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
- For questions or feedback please reach out to us.
