> For the complete documentation index, see [llms.txt](https://qc-ai-test.gitbook.io/qc-ai-test-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://qc-ai-test.gitbook.io/qc-ai-test-docs/readme.md).

# Welcome

Welcome to the AI docs for Qualcomm Dragonwing. Dragonwing is a family of IoT SoCs that offer high performance, advanced connectivity and efficient power - paired with fast GPUs and NPUs; and running a variety of operating systems (Ubuntu, Qualcomm Linux, Android and Windows). This makes them perfect for advanced edge AI workloads, or high-performance computer vision applications.

This documentation is where you’ll find all the information you need to set up your Dragonwing platforms, run your first AI or CV application, and how to run your existing workloads at full performance.

{% hint style="info" %}
**Note:** This documentation is work in progress; and is written for development boards running Ubuntu 24.
{% endhint %}

## Getting started

Just getting started? Check out [Getting Started with Qualcomm Dragonwing](/qc-ai-test-docs/getting-started.md) to learn more about where to run your AI model, the basics of NPUs, and more.

## Device setup

We support the following development boards. Follow the setup guide to prepare your development board and install Ubuntu 24:

* [RB3 Gen 2 Vision Kit](/qc-ai-test-docs/device-setup/rb3-gen2-vision-kit.md)
* [Rubik Pi 3](/qc-ai-test-docs/device-setup/rubik-pi3.md)
* [IQ-9075 EVK](/qc-ai-test-docs/device-setup/iq9075-evk.md)

Then, [setup Visual Studio Code (VS Code)](/qc-ai-test-docs/device-setup/vscode-ssh-setup.md) to develop for your board remotely via SSH.

## Running AI models

We support a wide range of ways to run AI models. Whether you use a platform like Edge Impulse, want to download pretrained models from AI Hub, or want to bring your own inference pipeline using TensorFlow Lite (LiteRT) or ONNX. Here's a full list of guides:

* [Building your own AI models using Edge Impulse](/qc-ai-test-docs/running-building-ai-models/edge-impulse.md)
* [Find and run pretrained models on AI Hub](/qc-ai-test-docs/running-building-ai-models/ai-hub.md)
* [Run TensorFlow models on NPU](/qc-ai-test-docs/running-building-ai-models/tensorflow.md)
* [Run LiteRT/TFLite models on NPU](/qc-ai-test-docs/running-building-ai-models/lite-rt.md)
* [Run ONNX models on NPU](/qc-ai-test-docs/running-building-ai-models/onnxruntime.md)
* [Run context binaries (.dlc / .bin) on NPU with QAI AppBuilder](/qc-ai-test-docs/running-building-ai-models/context-binaries.md)
* [Run LLMs / VLMs on GPU using Llama.cpp](/qc-ai-test-docs/running-building-ai-models/llama-cpp.md)
* [Run LLMs / VLMs on NPU using Genie](/qc-ai-test-docs/running-building-ai-models/genie.md)
* [Transcribe audio using Whisper on NPU](/qc-ai-test-docs/running-building-ai-models/whisper.md)
* [Running computer vision applications on GPU with IM-SDK](/qc-ai-test-docs/running-building-ai-models/im-sdk.md)

## Tools

* [Use the NPU from inside a Docker container](/qc-ai-test-docs/tools/docker.md)
* [Profiling models](/qc-ai-test-docs/tools/profiling-models.md)