> ## Documentation Index
> Fetch the complete documentation index at: https://dragonwingdocs-staging.qualcomm.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Prepare a GenAI model
> Prepare a generative AI (GenAI) model for deployment on Qualcomm Dragonwing IoT platforms using Qualcomm AI Hub or Qualcomm Jupyter notebooks.
To prepare a GenAI model for execution on Qualcomm® Dragonwing™ IQ series
evaluation kits, use [Qualcomm AI Hub](https://aihub.qualcomm.com/iot/models)
to export model binaries from a model with precomputed encodings or
[Qualcomm Jupyter notebooks](https://qpm.qualcomm.com/#/main/tools/details/Tutorial_for_LLaVA1_5_7b_IoT)
to generate model binaries from a pre-trained model.
For more Jupyter notebook examples, go to [Qualcomm Package Manager](https://qpm.qualcomm.com/#/main/home),
select **Tools**, and search for **Generative AI Tutorials**.
The following image shows the preparation process and base system requirements
for both options.
Qualcomm AI Model Efficiency Toolkit (AIMET) supports advanced quantization techniques.
Depending on the model used, you may need to choose a different quantization technique
for better accuracy.
The following table summarizes approaches to GenAI model preparation.
| Feature | AI Hub | Jupyter notebooks |
| - | - | - |
| Automation | High: One command export | Medium: Step-by-step process guided by Jupyter notebook |
| Customization | Limited: Only applicable to models hosted on AI Hub | High: Full control over quantization and graph optimization |
| Target audience | Users seeking quick deployment | Researchers and advanced users |
| Host system requirements | Medium: 80 GB RAM + swap space | High: High-End GPU like A100 and RAM + swap space |