# Deploy a LiteRT model

You can run LiteRT models on the Qualcomm^®^ development kits
by setting up the prerequisites and downloading the required files.
Use either the precompiled `gst-ai-classification` or the native
`label_image` sample application to run a LiteRT classification model.

Ensure, you have completed the [prerequisites](https://docs.qualcomm.com/doc/80-80022-15B/topic/prerequisites-to-run-litert-sample-applications.html#litert-prerequisites)

Next steps

- [Deploy LiteRT as a Native application](https://docs.qualcomm.com/doc/80-80022-15B/topic/deploy-litert-as-a-native-application.html)
- [Deploy LiteRT with an IMSDK application](https://docs.qualcomm.com/doc/80-80022-15B/topic/deploy-litert-with-an-imsdk-application.html)
- [Deploy LiteRT as a Python application](https://docs.qualcomm.com/doc/80-80022-15B/topic/deploy-litert-as-a-python-application.html)

Last Published: Jun 23, 2026

[Previous Topic
Benchmark Qualcomm AI Runtime using an external delegate](https://docs.qualcomm.com/bundle/publicresource/80-80022-15B/topics/benchmark-qairt-on-external-delegate.md) [Next Topic
Deploy LiteRT as a Native application](https://docs.qualcomm.com/bundle/publicresource/80-80022-15B/topics/deploy-litert-as-a-native-application.md)