WideResNet50: Optimized for Qualcomm Devices
WideResNet50 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.
This is based on the implementation of WideResNet50 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 1.24.3 | Download |
| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | Download |
| QNN_DLC | float | Universal | QAIRT 2.45 | Download |
| QNN_DLC | w8a8 | Universal | QAIRT 2.45 | Download |
| TFLITE | float | Universal | QAIRT 2.45 | Download |
| TFLITE | w8a8 | Universal | QAIRT 2.45 | Download |
For more device-specific assets and performance metrics, visit WideResNet50 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 WideResNet50 on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.image_classification
Model Stats:
- Model checkpoint: Imagenet
- Input resolution: 224x224
- Number of parameters: 68.9M
- Model size (float): 263 MB
- Model size (w8a8): 66.6 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| WideResNet50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.64 ms | 1 - 189 MB | NPU |
| WideResNet50 | ONNX | float | Snapdragon® X2 Elite | 2.187 ms | 132 - 132 MB | NPU |
| WideResNet50 | ONNX | float | Snapdragon® X Elite | 4.439 ms | 132 - 132 MB | NPU |
| WideResNet50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 3.468 ms | 0 - 226 MB | NPU |
| WideResNet50 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 4.568 ms | 1 - 366 MB | NPU |
| WideResNet50 | ONNX | float | Qualcomm® QCS9075 | 6.776 ms | 1 - 4 MB | NPU |
| WideResNet50 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.81 ms | 0 - 179 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.149 ms | 0 - 53 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Snapdragon® X2 Elite | 0.819 ms | 66 - 66 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Snapdragon® X Elite | 1.788 ms | 66 - 66 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.413 ms | 0 - 131 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Qualcomm® QCS6490 | 77.076 ms | 10 - 111 MB | CPU |
| WideResNet50 | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.857 ms | 0 - 99 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Qualcomm® QCS9075 | 1.929 ms | 0 - 3 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Qualcomm® QCM6690 | 61.735 ms | 0 - 9 MB | CPU |
| WideResNet50 | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.222 ms | 0 - 54 MB | NPU |
| WideResNet50 | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 57.377 ms | 8 - 16 MB | CPU |
| WideResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.554 ms | 1 - 171 MB | NPU |
| WideResNet50 | QNN_DLC | float | Snapdragon® X2 Elite | 2.458 ms | 1 - 1 MB | NPU |
| WideResNet50 | QNN_DLC | float | Snapdragon® X Elite | 4.69 ms | 1 - 1 MB | NPU |
| WideResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 3.644 ms | 0 - 224 MB | NPU |
| WideResNet50 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 24.506 ms | 1 - 174 MB | NPU |
| WideResNet50 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 4.834 ms | 1 - 2 MB | NPU |
| WideResNet50 | QNN_DLC | float | Qualcomm® SA8775P | 7.151 ms | 1 - 169 MB | NPU |
| WideResNet50 | QNN_DLC | float | Qualcomm® QCS9075 | 7.097 ms | 1 - 3 MB | NPU |
| WideResNet50 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 9.199 ms | 0 - 197 MB | NPU |
| WideResNet50 | QNN_DLC | float | Qualcomm® SA7255P | 24.506 ms | 1 - 174 MB | NPU |
| WideResNet50 | QNN_DLC | float | Qualcomm® SA8295P | 7.847 ms | 1 - 153 MB | NPU |
| WideResNet50 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.897 ms | 0 - 175 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.093 ms | 0 - 56 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.899 ms | 0 - 0 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Snapdragon® X Elite | 1.798 ms | 0 - 0 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.41 ms | 0 - 126 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 7.83 ms | 0 - 2 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 4.02 ms | 0 - 53 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.87 ms | 0 - 2 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8775P | 2.014 ms | 0 - 54 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 1.914 ms | 0 - 2 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 17.895 ms | 0 - 215 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 2.518 ms | 0 - 128 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® SA7255P | 4.02 ms | 0 - 53 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 2.754 ms | 0 - 51 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.201 ms | 0 - 54 MB | NPU |
| WideResNet50 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 2.853 ms | 0 - 210 MB | NPU |
| WideResNet50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.513 ms | 0 - 102 MB | NPU |
| WideResNet50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 3.55 ms | 0 - 215 MB | NPU |
| WideResNet50 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 23.784 ms | 0 - 100 MB | NPU |
| WideResNet50 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 4.75 ms | 0 - 2 MB | NPU |
| WideResNet50 | TFLITE | float | Qualcomm® SA8775P | 7.04 ms | 0 - 101 MB | NPU |
| WideResNet50 | TFLITE | float | Qualcomm® QCS9075 | 7.057 ms | 0 - 134 MB | NPU |
| WideResNet50 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 8.181 ms | 0 - 191 MB | NPU |
| WideResNet50 | TFLITE | float | Qualcomm® SA7255P | 23.784 ms | 0 - 100 MB | NPU |
| WideResNet50 | TFLITE | float | Qualcomm® SA8295P | 7.772 ms | 0 - 88 MB | NPU |
| WideResNet50 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.848 ms | 0 - 106 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.05 ms | 0 - 57 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.329 ms | 0 - 131 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® QCS6490 | 6.887 ms | 0 - 68 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 3.762 ms | 0 - 52 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.732 ms | 0 - 3 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® SA8775P | 1.887 ms | 0 - 53 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® QCS9075 | 1.75 ms | 0 - 68 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® QCM6690 | 17.549 ms | 0 - 214 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 2.397 ms | 0 - 126 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® SA7255P | 3.762 ms | 0 - 52 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Qualcomm® SA8295P | 2.572 ms | 0 - 56 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.118 ms | 0 - 53 MB | NPU |
| WideResNet50 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 2.72 ms | 0 - 208 MB | NPU |
License
- The license for the original implementation of WideResNet50 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.
