---
library_name: pytorch
license: other
tags:
- backbone
- bu_auto
- android
pipeline_tag: image-classification

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/swin_small/web-assets/model_demo.png)

# Swin-Small: Optimized for Qualcomm Devices

SwinSmall 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 Swin-Small found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/swin_transformer.py).
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/swin_small) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).

Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) 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](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/swin_small/releases/v0.59.0/swin_small-onnx-float.zip)
| ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/swin_small/releases/v0.59.0/swin_small-onnx-w8a16.zip)
| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/swin_small/releases/v0.59.0/swin_small-qnn_dlc-float.zip)
| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/swin_small/releases/v0.59.0/swin_small-qnn_dlc-w8a16.zip)
| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/swin_small/releases/v0.59.0/swin_small-tflite-float.zip)

For more device-specific assets and performance metrics, visit **[Swin-Small on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/swin_small)**.


### Option 2: Export with Custom Configurations

Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/swin_small) 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 [Swin-Small on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/swin_small) for usage instructions.

## Model Details

**Model Type:** Model_use_case.image_classification

**Model Stats:**
- Model checkpoint: Imagenet
- Input resolution: 224x224
- Number of parameters: 50.4M
- Model size (float): 193 MB
- Model size (w8a16): 52.5 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| Swin-Small | ONNX | float | Snapdragon® X2 Elite | 6.803 ms | 2 - 2 MB | NPU
| Swin-Small | ONNX | float | Snapdragon® X Elite | 16.29 ms | 101 - 101 MB | NPU
| Swin-Small | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 10.219 ms | 0 - 419 MB | NPU
| Swin-Small | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 23.899 ms | 0 - 410 MB | NPU
| Swin-Small | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 15.516 ms | 0 - 8 MB | NPU
| Swin-Small | ONNX | float | Qualcomm® QCS8450 | 23.899 ms | 0 - 410 MB | NPU
| Swin-Small | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 17.884 ms | 0 - 4 MB | NPU
| Swin-Small | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 16.29 ms | 101 - 101 MB | NPU
| Swin-Small | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 7.823 ms | 1 - 606 MB | NPU
| Swin-Small | ONNX | float | Snapdragon® 8 Elite Mobile | 7.823 ms | 1 - 606 MB | NPU
| Swin-Small | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 6.424 ms | 1 - 621 MB | NPU
| Swin-Small | ONNX | w8a16 | Snapdragon® X2 Elite | 5.98 ms | 1 - 1 MB | NPU
| Swin-Small | ONNX | w8a16 | Snapdragon® X Elite | 13.798 ms | 54 - 54 MB | NPU
| Swin-Small | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 8.712 ms | 0 - 528 MB | NPU
| Swin-Small | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 16.407 ms | 0 - 440 MB | NPU
| Swin-Small | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 40.257 ms | 0 - 3 MB | NPU
| Swin-Small | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 13.191 ms | 0 - 58 MB | NPU
| Swin-Small | ONNX | w8a16 | Qualcomm® QCS8450 | 16.407 ms | 0 - 440 MB | NPU
| Swin-Small | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 13.691 ms | 0 - 3 MB | NPU
| Swin-Small | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 13.798 ms | 54 - 54 MB | NPU
| Swin-Small | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 6.926 ms | 0 - 441 MB | NPU
| Swin-Small | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 6.926 ms | 0 - 441 MB | NPU
| Swin-Small | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 5.65 ms | 0 - 453 MB | NPU
| Swin-Small | QNN_DLC | float | Snapdragon® X2 Elite | 7.113 ms | 1 - 1 MB | NPU
| Swin-Small | QNN_DLC | float | Snapdragon® X Elite | 16.346 ms | 1 - 1 MB | NPU
| Swin-Small | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 9.934 ms | 0 - 405 MB | NPU
| Swin-Small | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 23.922 ms | 0 - 396 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8275 | 37.942 ms | 1 - 275 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 15.374 ms | 1 - 4 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® SA8775P | 17.388 ms | 1 - 593 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® SA8650P | 17.388 ms | 1 - 593 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® SA8255P | 17.388 ms | 1 - 593 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® QCS8450 | 23.922 ms | 0 - 396 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 17.609 ms | 1 - 3 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 16.346 ms | 1 - 1 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 7.617 ms | 1 - 586 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® SA7255P | 37.942 ms | 1 - 275 MB | NPU
| Swin-Small | QNN_DLC | float | Qualcomm® SA8295P | 22.636 ms | 1 - 269 MB | NPU
| Swin-Small | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 7.617 ms | 1 - 586 MB | NPU
| Swin-Small | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 6.248 ms | 0 - 602 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 7.213 ms | 0 - 0 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Snapdragon® X Elite | 17.313 ms | 0 - 0 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 10.768 ms | 0 - 870 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8275 | 29.258 ms | 0 - 636 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 16.192 ms | 0 - 3 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® SA8775P | 16.763 ms | 0 - 638 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® SA8650P | 16.763 ms | 0 - 638 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® SA8255P | 16.763 ms | 0 - 638 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 17.063 ms | 0 - 2 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 17.313 ms | 0 - 0 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 74.076 ms | 0 - 752 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 17.237 ms | 0 - 652 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 8.108 ms | 0 - 622 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Qualcomm® SA7255P | 29.258 ms | 0 - 636 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 8.108 ms | 0 - 622 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 6.502 ms | 0 - 641 MB | NPU
| Swin-Small | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 17.237 ms | 0 - 652 MB | NPU
| Swin-Small | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 10.204 ms | 0 - 433 MB | NPU
| Swin-Small | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 23.391 ms | 0 - 410 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® Dragonwing™ QCS8275 | 37.439 ms | 0 - 302 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 15.556 ms | 0 - 4 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® SA8775P | 17.487 ms | 0 - 306 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® SA8650P | 17.487 ms | 0 - 306 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® SA8255P | 17.487 ms | 0 - 306 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® QCS8450 | 23.391 ms | 0 - 410 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 17.613 ms | 0 - 104 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 7.825 ms | 0 - 303 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® SA7255P | 37.439 ms | 0 - 302 MB | NPU
| Swin-Small | TFLITE | float | Qualcomm® SA8295P | 22.998 ms | 0 - 297 MB | NPU
| Swin-Small | TFLITE | float | Snapdragon® 8 Elite Mobile | 7.825 ms | 0 - 303 MB | NPU
| Swin-Small | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 6.601 ms | 0 - 322 MB | NPU

## License
* The license for the original implementation of Swin-Small can be found
  [here](https://github.com/pytorch/vision/blob/main/LICENSE).

## References
* [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030)
* [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/swin_transformer.py)

## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).