LiteRT supports Qualcomm AI Engine Direct (QNN) through the `CompiledModel` API
for both AOT and on-device compilation.

## Set up development environment

Qualcomm AI Engine Direct has the following development environment
requirements:

- **Operating System**: Ubuntu 22.04 LTS
- **Build System**: Bazel version 7.4.1
- **Standard libraries**: Libc++ and Libc++abi 16+
- **Platform Specific Requirements:**
  - **Android:**
  - **Android SDK**: Android API Level 34 (Android 14).
  - **Android NDK**: Support for API Level 28 (Android 9 Pie).
  - **IoT**: coming soon.
  - **Windows**: coming soon.

You can use the [Quick system setup with Docker](https://github.com/google-ai-edge/LiteRT/blob/main/docker_build/README.md) to configure
dependencies automatically.

## Supported operations

LiteRT lowers a broad set of ops to the QNN Hexagon Tensor Processor (HTP)
backend. Both AOT and on-device compilation are supported. See the
[supported ops](https://github.com/google-ai-edge/LiteRT/blob/main/litert/vendors/qualcomm/compiler/Qualcomm_QNN_Compiler.md)
list.

## Supported SoCs

- Snapdragon 8 Elite Gen 5 Mobile Platform (SM8850)
- Snapdragon 8 Elite Mobile Platform (SM8750)
- Snapdragon 8 Gen 3 Mobile Platform (SM8650)
- Snapdragon 8 Gen 2 Mobile Platform (SM8550)
- Snapdragon 8+ Gen 1 Mobile Platform (SM8475)
- Snapdragon 8 Gen 1 Mobile Platform (SM8450)
- Refer to the [Qualcomm QNN HTP Backend](https://docs.qualcomm.com/doc/80-63442-10/topic/htp_backend.html) Documentation for advanced configuration of the HTP backend

## Next steps

1. Start with the unified NPU guide: [NPU acceleration with LiteRT](https://developers.google.com/edge/litert/next/npu)
2. Follow the conversion and deployment steps there, choosing Qualcomm where applicable.
3. For LLMs, see [Execute LLMs on NPU using LiteRT-LM](https://developers.google.com/edge/litert/next/litert_lm_npu).