EfficientNet-B4: Optimized for Qualcomm Devices
EfficientNetB4 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 EfficientNet-B4 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 2.45, ONNX Runtime 1.27.1 | Download |
| ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.45 | Download |
| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | Download |
| TFLITE | float | Universal | QAIRT 2.45 | Download |
For more device-specific assets and performance metrics, visit EfficientNet-B4 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 EfficientNet-B4 on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.image_classification
Model Stats:
- Input resolution: 380x380
- Model checkpoint: Imagenet
- Model size (float): 73.6 MB
- Model size (w8a16): 24.0 MB
- Number of parameters: 19.3M
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| EfficientNet-B4 | ONNX | float | Snapdragon® X2 Elite | 3.926 ms | 2 - 2 MB | NPU |
| EfficientNet-B4 | ONNX | float | Snapdragon® X Elite | 7.685 ms | 45 - 45 MB | NPU |
| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 5.316 ms | 0 - 150 MB | NPU |
| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 20.51 ms | 0 - 190 MB | NPU |
| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 9.585 ms | 2 - 7 MB | NPU |
| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 7.329 ms | 0 - 215 MB | NPU |
| EfficientNet-B4 | ONNX | float | Qualcomm® QCS8450 | 20.51 ms | 0 - 190 MB | NPU |
| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 11.231 ms | 1 - 6 MB | NPU |
| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 7.685 ms | 45 - 45 MB | NPU |
| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 4.04 ms | 0 - 90 MB | NPU |
| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Elite Mobile | 4.04 ms | 0 - 90 MB | NPU |
| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.114 ms | 0 - 206 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® X2 Elite | 2.917 ms | 2 - 2 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® X Elite | 7.998 ms | 24 - 24 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 5.071 ms | 1 - 226 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 8.902 ms | 0 - 226 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 32.879 ms | 0 - 4 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 6.951 ms | 1 - 4 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 7.624 ms | 0 - 30 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® QCS8450 | 8.902 ms | 0 - 226 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 8.015 ms | 1 - 4 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 7.998 ms | 24 - 24 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 53.875 ms | 1 - 296 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 8.929 ms | 1 - 288 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 3.413 ms | 0 - 165 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 3.413 ms | 0 - 165 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.744 ms | 0 - 176 MB | NPU |
| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 8.929 ms | 1 - 288 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Snapdragon® X2 Elite | 4.518 ms | 2 - 2 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Snapdragon® X Elite | 8.905 ms | 2 - 2 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 5.813 ms | 0 - 142 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 22.944 ms | 2 - 188 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 10.038 ms | 2 - 6 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 29.128 ms | 2 - 81 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 8.13 ms | 2 - 3 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8775P | 10.309 ms | 2 - 85 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8650P | 10.309 ms | 2 - 85 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8255P | 10.309 ms | 2 - 85 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® QCS8450 | 22.944 ms | 2 - 188 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 10.033 ms | 4 - 7 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 8.905 ms | 2 - 2 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 4.304 ms | 2 - 87 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA7255P | 29.128 ms | 2 - 81 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8295P | 18.789 ms | 2 - 124 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 4.304 ms | 2 - 87 MB | NPU |
| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.254 ms | 2 - 207 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 3.541 ms | 1 - 1 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® X Elite | 9.091 ms | 1 - 1 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 5.643 ms | 0 - 196 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 1 Mobile | 11.391 ms | 1 - 202 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 33.692 ms | 1 - 3 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 7.617 ms | 1 - 4 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 15.42 ms | 1 - 141 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 8.358 ms | 1 - 136 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8775P | 8.902 ms | 1 - 144 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8650P | 8.902 ms | 1 - 144 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8255P | 8.902 ms | 1 - 144 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® QCS8450 | 11.391 ms | 1 - 202 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 8.652 ms | 2 - 5 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 9.091 ms | 1 - 1 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 60.7 ms | 1 - 275 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 9.803 ms | 1 - 268 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 3.716 ms | 0 - 145 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA7255P | 15.42 ms | 1 - 141 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8295P | 10.91 ms | 1 - 144 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 3.716 ms | 0 - 145 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 3.008 ms | 1 - 155 MB | NPU |
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 9.803 ms | 1 - 268 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 5.745 ms | 0 - 159 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 21.784 ms | 0 - 205 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 9.984 ms | 0 - 50 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 28.92 ms | 0 - 98 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 8.024 ms | 0 - 3 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8775P | 10.285 ms | 0 - 100 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8650P | 10.285 ms | 0 - 100 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8255P | 10.285 ms | 0 - 100 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® QCS8450 | 21.784 ms | 0 - 205 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 10.0 ms | 0 - 49 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 4.334 ms | 0 - 104 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA7255P | 28.92 ms | 0 - 98 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8295P | 18.869 ms | 0 - 139 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Elite Mobile | 4.334 ms | 0 - 104 MB | NPU |
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.316 ms | 0 - 99 MB | NPU |
License
- The license for the original implementation of EfficientNet-B4 can be found here.
References
- EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- Source Model Implementation
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.
