EfficientViT-l2-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-l2-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-l2-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-l2-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): 243 MB
- Number of parameters: 63.7M
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| EfficientViT-l2-cls | ONNX | float | Snapdragon® X2 Elite | 7.037 ms | 2 - 2 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Snapdragon® X Elite | 14.539 ms | 131 - 131 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 10.025 ms | 0 - 478 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 57.144 ms | 0 - 362 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 18.991 ms | 2 - 7 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 14.108 ms | 0 - 191 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Qualcomm® QCS8450 | 57.144 ms | 0 - 362 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 19.322 ms | 1 - 6 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 14.539 ms | 131 - 131 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 7.687 ms | 2 - 352 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Snapdragon® 8 Elite Mobile | 7.687 ms | 2 - 352 MB | NPU |
| EfficientViT-l2-cls | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 6.012 ms | 2 - 377 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Snapdragon® X2 Elite | 5.686 ms | 2 - 2 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Snapdragon® X Elite | 12.824 ms | 67 - 67 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 7.822 ms | 0 - 323 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 14.997 ms | 1 - 325 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 52.172 ms | 0 - 4 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 11.063 ms | 1 - 5 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 11.999 ms | 0 - 431 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® QCS8450 | 14.997 ms | 1 - 325 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 12.9 ms | 0 - 4 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 12.824 ms | 67 - 67 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 111.538 ms | 0 - 459 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 15.03 ms | 1 - 465 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 5.906 ms | 0 - 259 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 5.906 ms | 0 - 259 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 4.762 ms | 0 - 261 MB | NPU |
| EfficientViT-l2-cls | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 15.03 ms | 1 - 465 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Snapdragon® X2 Elite | 8.808 ms | 2 - 2 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Snapdragon® X Elite | 18.237 ms | 2 - 2 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 12.296 ms | 0 - 526 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 43.169 ms | 0 - 355 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 22.32 ms | 2 - 6 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 59.685 ms | 2 - 261 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 16.891 ms | 2 - 4 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® SA8775P | 21.72 ms | 2 - 263 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® SA8650P | 21.72 ms | 2 - 263 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® SA8255P | 21.72 ms | 2 - 263 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® QCS8450 | 43.169 ms | 0 - 355 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 21.914 ms | 2 - 5 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 18.237 ms | 2 - 2 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 8.935 ms | 2 - 260 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® SA7255P | 59.685 ms | 2 - 261 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Qualcomm® SA8295P | 34.949 ms | 2 - 250 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 8.935 ms | 2 - 260 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 7.009 ms | 2 - 270 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 6.866 ms | 1 - 1 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Snapdragon® X Elite | 15.658 ms | 1 - 1 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 9.35 ms | 0 - 308 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 13.344 ms | 1 - 4 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-8275 | 27.635 ms | 1 - 253 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 14.468 ms | 1 - 3 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® SA8775P | 15.001 ms | 1 - 255 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® SA8650P | 15.001 ms | 1 - 255 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® SA8255P | 15.001 ms | 1 - 255 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 15.394 ms | 3 - 5 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 15.658 ms | 1 - 1 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 133.923 ms | 1 - 459 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 18.114 ms | 1 - 391 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 6.967 ms | 1 - 253 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Qualcomm® SA7255P | 27.635 ms | 1 - 253 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 6.967 ms | 1 - 253 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 5.838 ms | 1 - 253 MB | NPU |
| EfficientViT-l2-cls | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 18.114 ms | 1 - 391 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 11.661 ms | 0 - 605 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 42.663 ms | 0 - 441 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 21.446 ms | 0 - 136 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 58.422 ms | 0 - 469 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 16.166 ms | 0 - 3 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® SA8775P | 20.925 ms | 0 - 333 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® SA8650P | 20.925 ms | 0 - 333 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® SA8255P | 20.925 ms | 0 - 333 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® QCS8450 | 42.663 ms | 0 - 441 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 20.852 ms | 0 - 135 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 8.685 ms | 7 - 343 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® SA7255P | 58.422 ms | 0 - 469 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Qualcomm® SA8295P | 34.356 ms | 1 - 322 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Snapdragon® 8 Elite Mobile | 8.685 ms | 7 - 343 MB | NPU |
| EfficientViT-l2-cls | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 6.846 ms | 0 - 468 MB | NPU |
License
- The license for the original implementation of EfficientViT-l2-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.
