EfficientViT-b2-cls: Optimized for Qualcomm Devices
EfficientViT 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 EfficientViT-b2-cls 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 EfficientViT-b2-cls 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 EfficientViT-b2-cls on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.image_classification
Model Stats:
- Input resolution: 224x224
- Model checkpoint: Imagenet
- Model size (float): 92.9 MB
- Number of parameters: 24.3M
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| EfficientViT-b2-cls | ONNX | float | Snapdragon® X2 Elite | 2.529 ms | 2 - 2 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Snapdragon® X Elite | 5.071 ms | 50 - 50 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 3.223 ms | 0 - 144 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 6.353 ms | 1 - 145 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 5.066 ms | 0 - 4 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 4.869 ms | 0 - 73 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Qualcomm® QCS8450 | 6.353 ms | 1 - 145 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 5.53 ms | 0 - 4 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 5.071 ms | 50 - 50 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 2.7 ms | 0 - 71 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Snapdragon® 8 Elite Mobile | 2.7 ms | 0 - 71 MB | NPU |
| EfficientViT-b2-cls | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.442 ms | 1 - 72 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Snapdragon® X2 Elite | 2.342 ms | 1 - 1 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Snapdragon® X Elite | 4.847 ms | 27 - 27 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 3.094 ms | 0 - 157 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 5.8 ms | 0 - 169 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 15.089 ms | 0 - 3 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 4.213 ms | 0 - 4 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 4.6 ms | 0 - 213 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® QCS8450 | 5.8 ms | 0 - 169 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 4.941 ms | 0 - 3 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 4.847 ms | 27 - 27 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 19.551 ms | 0 - 255 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 4.99 ms | 0 - 117 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 2.516 ms | 0 - 114 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 2.516 ms | 0 - 114 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.169 ms | 0 - 115 MB | NPU |
| EfficientViT-b2-cls | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 4.99 ms | 0 - 117 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Snapdragon® X2 Elite | 2.949 ms | 1 - 1 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Snapdragon® X Elite | 6.23 ms | 1 - 1 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 3.738 ms | 0 - 142 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 7.122 ms | 0 - 146 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 6.15 ms | 1 - 4 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 12.815 ms | 1 - 67 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 5.456 ms | 0 - 6 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® SA8775P | 6.789 ms | 1 - 69 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® SA8650P | 6.789 ms | 1 - 69 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® SA8255P | 6.789 ms | 1 - 69 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® QCS8450 | 7.122 ms | 0 - 146 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 6.513 ms | 1 - 3 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 6.23 ms | 1 - 1 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 2.788 ms | 0 - 69 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® SA7255P | 12.815 ms | 1 - 67 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Qualcomm® SA8295P | 7.42 ms | 1 - 72 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 2.788 ms | 0 - 69 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.34 ms | 1 - 74 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 2.633 ms | 0 - 0 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Snapdragon® X Elite | 5.445 ms | 0 - 0 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 3.296 ms | 0 - 146 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 4.433 ms | 0 - 3 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 9.238 ms | 0 - 103 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 4.985 ms | 0 - 87 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® SA8775P | 5.476 ms | 0 - 106 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® SA8650P | 5.476 ms | 0 - 106 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® SA8255P | 5.476 ms | 0 - 106 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 5.291 ms | 0 - 2 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 5.445 ms | 0 - 0 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 21.198 ms | 0 - 229 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 5.184 ms | 0 - 101 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 2.514 ms | 0 - 105 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Qualcomm® SA7255P | 9.238 ms | 0 - 103 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 2.514 ms | 0 - 105 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.113 ms | 0 - 107 MB | NPU |
| EfficientViT-b2-cls | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 5.184 ms | 0 - 101 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 3.748 ms | 0 - 183 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 7.125 ms | 0 - 186 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 6.181 ms | 0 - 52 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 12.891 ms | 0 - 110 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 5.497 ms | 0 - 2 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® SA8775P | 6.769 ms | 0 - 111 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® SA8650P | 6.769 ms | 0 - 111 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® SA8255P | 6.769 ms | 0 - 111 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® QCS8450 | 7.125 ms | 0 - 186 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 6.526 ms | 0 - 52 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 2.768 ms | 0 - 98 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® SA7255P | 12.891 ms | 0 - 110 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Qualcomm® SA8295P | 7.469 ms | 0 - 115 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Snapdragon® 8 Elite Mobile | 2.768 ms | 0 - 98 MB | NPU |
| EfficientViT-b2-cls | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.344 ms | 0 - 117 MB | NPU |
License
- The license for the original implementation of EfficientViT-b2-cls can be found here.
References
- EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction
- 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.
