Phi Cookbook is a collection of hands-on examples and guides for working with Microsoft's Phi family of small language models.
The cookbook addresses the challenge of getting started with capable small language models by providing practical examples across multiple scenarios. Phi models are designed to deliver strong performance on language, reasoning, coding, and math tasks while maintaining a smaller footprint than larger alternatives. The approach centers on demonstrating how to deploy and build generative AI applications with these models, whether targeting cloud infrastructure or edge devices with limited computing resources.
Developers should consider this resource if they are evaluating small language models for production use and want concrete examples of implementation patterns. The cookbook suits projects where model size and inference cost matter—such as edge deployments, resource-constrained environments, or applications requiring efficient inference. The material covers multiple Phi model variants, including multimodal versions, so teams can explore different capabilities within the same family.
The project maintains active development with regular updates to examples and documentation. The repository includes automated processes to keep content synchronized across multiple languages. Community engagement is facilitated through an associated Discord channel where developers can connect with maintainers and peers working with Phi models.
