OpusMT-Zh-En: Optimized for Qualcomm Devices
OpusMT Chinese to English translation model is a state-of-the-art neural machine translation system designed for translating Chinese text into English. 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 English translations with high accuracy.
This is based on the implementation of OpusMT-Zh-En 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 |
|---|---|---|---|---|
| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.43 | Download |
| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | Download |
For more device-specific assets and performance metrics, visit OpusMT-Zh-En 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-Zh-En on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.text_generation
Model Stats:
- Model checkpoint: Helsinki-NLP/opus-mt-zh-en
- Input resolution: 256 tokens (Chinese 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 | ONNX | float | Snapdragon® X Elite | 3.311 ms | 160 - 160 MB | NPU |
| OpusMTDecoder | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 2.752 ms | 0 - 397 MB | NPU |
| OpusMTDecoder | ONNX | float | Qualcomm® QCS8550 (Proxy) | 3.515 ms | 12 - 17 MB | NPU |
| OpusMTDecoder | ONNX | float | Qualcomm® QCS9075 | 4.24 ms | 12 - 27 MB | NPU |
| OpusMTDecoder | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.358 ms | 0 - 391 MB | NPU |
| OpusMTDecoder | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.219 ms | 1 - 378 MB | NPU |
| OpusMTDecoder | ONNX | float | Snapdragon® X2 Elite | 1.807 ms | 161 - 161 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Snapdragon® X Elite | 3.082 ms | 6 - 6 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 2.337 ms | 0 - 189 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 6.814 ms | 2 - 167 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 3.091 ms | 0 - 2 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Qualcomm® SA8775P | 3.945 ms | 2 - 168 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Qualcomm® QCS9075 | 3.368 ms | 6 - 14 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 4.004 ms | 6 - 173 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Qualcomm® SA7255P | 6.814 ms | 2 - 167 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Qualcomm® SA8295P | 4.133 ms | 6 - 155 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.133 ms | 0 - 165 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.869 ms | 0 - 171 MB | NPU |
| OpusMTDecoder | QNN_DLC | float | Snapdragon® X2 Elite | 1.858 ms | 6 - 6 MB | NPU |
| OpusMTDecoder | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 2.987 ms | 0 - 381 MB | NPU |
| OpusMTDecoder | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 6.652 ms | 0 - 229 MB | NPU |
| OpusMTDecoder | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 3.478 ms | 0 - 3 MB | NPU |
| OpusMTDecoder | TFLITE | float | Qualcomm® SA8775P | 4.234 ms | 0 - 231 MB | NPU |
| OpusMTDecoder | TFLITE | float | Qualcomm® QCS9075 | 4.206 ms | 0 - 186 MB | NPU |
| OpusMTDecoder | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 4.709 ms | 0 - 354 MB | NPU |
| OpusMTDecoder | TFLITE | float | Qualcomm® SA7255P | 6.652 ms | 0 - 229 MB | NPU |
| OpusMTDecoder | TFLITE | float | Qualcomm® SA8295P | 4.879 ms | 0 - 212 MB | NPU |
| OpusMTDecoder | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.52 ms | 0 - 414 MB | NPU |
| OpusMTDecoder | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.148 ms | 0 - 374 MB | NPU |
| OpusMTEncoder | ONNX | float | Snapdragon® X Elite | 5.068 ms | 108 - 108 MB | NPU |
| OpusMTEncoder | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 3.415 ms | 0 - 261 MB | NPU |
| OpusMTEncoder | ONNX | float | Qualcomm® QCS8550 (Proxy) | 4.761 ms | 16 - 19 MB | NPU |
| OpusMTEncoder | ONNX | float | Qualcomm® QCS9075 | 6.208 ms | 16 - 18 MB | NPU |
| OpusMTEncoder | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.771 ms | 0 - 290 MB | NPU |
| OpusMTEncoder | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.023 ms | 0 - 257 MB | NPU |
| OpusMTEncoder | ONNX | float | Snapdragon® X2 Elite | 2.194 ms | 108 - 108 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Snapdragon® X Elite | 3.862 ms | 0 - 0 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 2.543 ms | 0 - 90 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 12.6 ms | 0 - 52 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 3.536 ms | 0 - 2 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Qualcomm® SA8775P | 4.551 ms | 0 - 54 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Qualcomm® QCS9075 | 4.68 ms | 2 - 7 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 4.759 ms | 0 - 86 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Qualcomm® SA7255P | 12.6 ms | 0 - 52 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Qualcomm® SA8295P | 5.363 ms | 0 - 54 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.141 ms | 0 - 56 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.614 ms | 0 - 58 MB | NPU |
| OpusMTEncoder | QNN_DLC | float | Snapdragon® X2 Elite | 1.969 ms | 0 - 0 MB | NPU |
| OpusMTEncoder | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 2.658 ms | 0 - 261 MB | NPU |
| OpusMTEncoder | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 12.782 ms | 6 - 100 MB | NPU |
| OpusMTEncoder | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 3.688 ms | 4 - 275 MB | NPU |
| OpusMTEncoder | TFLITE | float | Qualcomm® SA8775P | 4.818 ms | 0 - 93 MB | NPU |
| OpusMTEncoder | TFLITE | float | Qualcomm® QCS9075 | 5.138 ms | 6 - 120 MB | NPU |
| OpusMTEncoder | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 5.047 ms | 6 - 258 MB | NPU |
| OpusMTEncoder | TFLITE | float | Qualcomm® SA7255P | 12.782 ms | 6 - 100 MB | NPU |
| OpusMTEncoder | TFLITE | float | Qualcomm® SA8295P | 5.638 ms | 6 - 95 MB | NPU |
| OpusMTEncoder | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.229 ms | 0 - 280 MB | NPU |
| OpusMTEncoder | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.76 ms | 0 - 243 MB | NPU |
License
- The license for the original implementation of OpusMT-Zh-En 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.
