A collection of on-device AI primitives for React Native is available, supporting low-latency inference without server costs and ensuring data privacy. The toolkit includes features such as text generation, embeddings, transcription, and speech synthesis, all optimized for Apple devices and compatible with the Vercel AI SDK. Additionally, users can run popular open-source language models directly on their devices using MLC's optimized runtime.

A React Native plugin enables access to Apple's on-device Intelligence Foundation Model framework, allowing developers to utilize local LLM APIs for generating structured outputs and managing sessions. It focuses on privacy by processing data on-device and supports various features like TypeScript, custom tools, and session management, making it suitable for AI-powered mobile applications.

React Native RAG is a new local library that enhances large language models (LLMs) with Retrieval-Augmented Generation (RAG) capabilities, allowing for improved, context-rich responses by retrieving relevant information from a local knowledge base. It offers benefits such as privacy, offline functionality, and scalability, while providing a modular toolkit for developers to customize their implementations. The library integrates seamlessly with React Native ExecuTorch for efficient on-device processing.