RegNet-Y-800MF: Optimized for Qualcomm Devices
RegNet_Y_800MF is part of the RegNet family of models designed for efficient and scalable image classification. It uses a simple yet effective design space to balance performance and computational cost, making it suitable for mobile and edge devices.
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 2.45, ONNX Runtime 1.25.0 | Download |
| ONNX | w8a8 | Universal | QAIRT 2.45, ONNX Runtime 1.25.0 | 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 RegNet-Y-800MF 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 RegNet-Y-800MF on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.image_classification
Model Stats:
- Model checkpoint: regnet_y_800mf-1b27b58c.pth
- Input resolution: 1x3x224
- Model size: ~6.3 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| RegNet-Y-800MF | ONNX | float | Snapdragon® X2 Elite | 0.539 ms | 212 - 212 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Snapdragon® X Elite | 1.132 ms | 181 - 181 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.708 ms | 0 - 66 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 1.458 ms | 1 - 65 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Qualcomm® QCS8550 (Proxy) | 1.087 ms | 0 - 32 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Qualcomm® QCS8450 | 1.458 ms | 1 - 65 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Snapdragon® 8 Elite Mobile | 0.56 ms | 0 - 55 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.535 ms | 1 - 51 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Qualcomm® QCS9075 | 1.473 ms | 1 - 46 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Qualcomm® QCS8750 | 0.56 ms | 0 - 55 MB | NPU |
| RegNet-Y-800MF | ONNX | float | Qualcomm® QCS7181 | 1.132 ms | 181 - 181 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® X2 Elite | 0.375 ms | 213 - 213 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® X Elite | 0.723 ms | 156 - 156 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.486 ms | 0 - 77 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 8 Gen 1 Mobile | 0.871 ms | 0 - 74 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS6490 | 1.549 ms | 0 - 45 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.701 ms | 0 - 98 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS8450 | 0.871 ms | 0 - 74 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.378 ms | 0 - 56 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.691 ms | 0 - 53 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCM6690 | 2.58 ms | 0 - 58 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS9075 | 0.861 ms | 0 - 53 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 8 Elite Mobile | 0.429 ms | 0 - 56 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS7790 | 0.691 ms | 0 - 53 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS8750 | 0.429 ms | 0 - 56 MB | NPU |
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS7181 | 0.723 ms | 156 - 156 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® X2 Elite | 0.826 ms | 1 - 1 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® X Elite | 1.615 ms | 1 - 1 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.907 ms | 0 - 75 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 2.223 ms | 1 - 75 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS8275 | 4.026 ms | 1 - 49 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 1.414 ms | 0 - 12 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS8450 | 2.223 ms | 1 - 75 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 0.695 ms | 1 - 52 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® SA8295P | 2.122 ms | 0 - 44 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.621 ms | 1 - 56 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® SA7255P | 4.026 ms | 1 - 49 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS9075 | 1.696 ms | 1 - 3 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS8750 | 0.695 ms | 1 - 52 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS7181 | 1.615 ms | 1 - 1 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.453 ms | 0 - 0 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® X Elite | 0.844 ms | 0 - 0 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.483 ms | 0 - 66 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 8 Gen 1 Mobile | 0.862 ms | 0 - 70 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 1.696 ms | 0 - 2 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS8275 | 1.57 ms | 0 - 48 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.69 ms | 0 - 2 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS8450 | 0.862 ms | 0 - 70 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.314 ms | 0 - 48 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.723 ms | 0 - 47 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 2.874 ms | 0 - 48 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 0.843 ms | 0 - 2 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® SA7255P | 1.57 ms | 0 - 48 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 8 Elite Mobile | 0.38 ms | 0 - 47 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® SA8295P | 1.107 ms | 0 - 46 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS7790 | 0.723 ms | 0 - 47 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS8750 | 0.38 ms | 0 - 47 MB | NPU |
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS7181 | 0.844 ms | 0 - 0 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.909 ms | 0 - 88 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 2.21 ms | 0 - 80 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS8275 | 4.049 ms | 0 - 59 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 1.414 ms | 0 - 7 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA8775P | 5.722 ms | 0 - 28 MB | GPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA8650P | 5.722 ms | 0 - 28 MB | GPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA8255P | 5.722 ms | 0 - 28 MB | GPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS8450 | 2.21 ms | 0 - 80 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Snapdragon® 8 Elite Mobile | 0.685 ms | 0 - 54 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA8295P | 2.149 ms | 0 - 50 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.613 ms | 0 - 59 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA7255P | 4.049 ms | 0 - 59 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS9075 | 1.706 ms | 0 - 17 MB | NPU |
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS8750 | 0.685 ms | 0 - 54 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.354 ms | 0 - 66 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 8 Gen 1 Mobile | 0.671 ms | 0 - 66 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS6490 | 1.171 ms | 0 - 9 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS8275 | 1.257 ms | 0 - 48 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.52 ms | 0 - 2 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA8775P | 6.088 ms | 0 - 28 MB | GPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA8650P | 6.088 ms | 0 - 28 MB | GPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA8255P | 6.088 ms | 0 - 28 MB | GPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS8450 | 0.671 ms | 0 - 66 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.255 ms | 0 - 43 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.534 ms | 0 - 43 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCM6690 | 2.334 ms | 0 - 44 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.67 ms | 0 - 10 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA7255P | 1.257 ms | 0 - 48 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 8 Elite Mobile | 0.302 ms | 0 - 43 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA8295P | 0.919 ms | 0 - 44 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS7790 | 0.534 ms | 0 - 43 MB | NPU |
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS8750 | 0.302 ms | 0 - 43 MB | NPU |
License
- The license for the original implementation of RegNet-Y-800MF can be found here.
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.
