ResNeXt50: Optimized for Qualcomm Devices
ResNeXt50 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 ResNeXt50 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 ResNeXt50 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 ResNeXt50 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: 25.0M
- Model size (float): 95.4 MB
- Model size (w8a8): 24.8 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| ResNeXt50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.132 ms | 1 - 85 MB | NPU |
| ResNeXt50 | ONNX | float | Snapdragon® X2 Elite | 1.098 ms | 50 - 50 MB | NPU |
| ResNeXt50 | ONNX | float | Snapdragon® X Elite | 2.422 ms | 50 - 50 MB | NPU |
| ResNeXt50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 1.669 ms | 0 - 150 MB | NPU |
| ResNeXt50 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 2.284 ms | 1 - 9 MB | NPU |
| ResNeXt50 | ONNX | float | Qualcomm® QCS9075 | 3.453 ms | 0 - 4 MB | NPU |
| ResNeXt50 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.383 ms | 0 - 85 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.603 ms | 0 - 79 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Snapdragon® X2 Elite | 0.505 ms | 25 - 25 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Snapdragon® X Elite | 1.281 ms | 25 - 25 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.814 ms | 0 - 100 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCS6490 | 46.441 ms | 8 - 24 MB | CPU |
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.128 ms | 0 - 33 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCS9075 | 1.233 ms | 0 - 3 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCM6690 | 26.538 ms | 3 - 12 MB | CPU |
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.692 ms | 0 - 68 MB | NPU |
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 20.706 ms | 5 - 14 MB | CPU |
| ResNeXt50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.157 ms | 1 - 75 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Snapdragon® X2 Elite | 1.447 ms | 1 - 1 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Snapdragon® X Elite | 2.697 ms | 1 - 1 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 1.811 ms | 1 - 136 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 12.03 ms | 1 - 71 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 2.573 ms | 1 - 2 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Qualcomm® SA8775P | 3.825 ms | 1 - 73 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS9075 | 3.636 ms | 3 - 5 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 4.022 ms | 0 - 113 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Qualcomm® SA7255P | 12.03 ms | 1 - 71 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Qualcomm® SA8295P | 4.111 ms | 0 - 56 MB | NPU |
| ResNeXt50 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.472 ms | 0 - 73 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.538 ms | 0 - 75 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.613 ms | 0 - 0 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® X Elite | 1.233 ms | 0 - 0 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.78 ms | 0 - 99 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 3.103 ms | 0 - 2 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 2.454 ms | 0 - 71 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.11 ms | 0 - 129 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® SA8775P | 1.444 ms | 0 - 72 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 1.199 ms | 0 - 2 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 7.622 ms | 0 - 194 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 1.477 ms | 0 - 100 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® SA7255P | 2.454 ms | 0 - 71 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 1.762 ms | 0 - 68 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.635 ms | 0 - 68 MB | NPU |
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.373 ms | 0 - 75 MB | NPU |
| ResNeXt50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.178 ms | 0 - 116 MB | NPU |
| ResNeXt50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 1.771 ms | 0 - 177 MB | NPU |
| ResNeXt50 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 12.032 ms | 0 - 112 MB | NPU |
| ResNeXt50 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 2.473 ms | 0 - 2 MB | NPU |
| ResNeXt50 | TFLITE | float | Qualcomm® SA8775P | 3.84 ms | 0 - 113 MB | NPU |
| ResNeXt50 | TFLITE | float | Qualcomm® QCS9075 | 3.686 ms | 0 - 52 MB | NPU |
| ResNeXt50 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 4.004 ms | 0 - 151 MB | NPU |
| ResNeXt50 | TFLITE | float | Qualcomm® SA7255P | 12.032 ms | 0 - 112 MB | NPU |
| ResNeXt50 | TFLITE | float | Qualcomm® SA8295P | 4.146 ms | 0 - 87 MB | NPU |
| ResNeXt50 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.435 ms | 0 - 116 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.485 ms | 0 - 73 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.676 ms | 0 - 99 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS6490 | 2.807 ms | 0 - 27 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 2.215 ms | 0 - 70 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.894 ms | 0 - 2 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® SA8775P | 1.276 ms | 0 - 71 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.992 ms | 0 - 27 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCM6690 | 7.047 ms | 0 - 198 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 1.286 ms | 0 - 99 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® SA7255P | 2.215 ms | 0 - 70 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® SA8295P | 1.556 ms | 0 - 65 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.551 ms | 0 - 64 MB | NPU |
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.218 ms | 0 - 70 MB | NPU |
License
- The license for the original implementation of ResNeXt50 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.
