#Introduction

A collection of on-device AI primitives for React Native with first-class Vercel AI SDK support. Run AI models directly on users' devices for privacy-preserving, low-latency inference without server costs.

#Why On-Device AI?

• Privacy-first: All processing happens locally—no data leaves the device
• Instant responses: No network latency, immediate AI capabilities
• Offline-ready: Works anywhere, even without internet
• Zero server costs: No API fees or infrastructure to maintain

#DevTools

The AI SDK Profiler plugin captures OpenTelemetry spans from Vercel AI SDK requests and surfaces them in Rozenite DevTools. DevTools are runtime agnostic, so they work with on-device and remote runtimes.

Learn more in the DevTools documentation.

#Available Providers

#Apple Intelligence

Native integration with Apple's on-device AI capabilities through @react-native-ai/apple:

• Text Generation - Apple Foundation Models for chat and completion
• Embeddings - NLContextualEmbedding for semantic search and similarity
• Transcription - SpeechAnalyzer for fast, accurate speech-to-text
• Speech Synthesis - AVSpeechSynthesizer for natural text-to-speech

Production-ready with instant availability on supported iOS devices.

#Llama Engine

Run any GGUF model from HuggingFace locally using llama.rn through @react-native-ai/llama:

• Text Generation - High-performance GGUF inference with full streaming support
• Model Management - Automatic downloading and caching from HuggingFace
• Customizable - Support for context size, threads, and GGUF-specific parameters

Cross-platform parity with optimized performance on both iOS and Android.

#MLC Engine (Work in Progress)

Run any open-source LLM locally using MLC's optimized runtime through @react-native-ai/mlc:

• Support for popular models like Llama, Mistral, and Phi
• Cross-platform compatibility (iOS and Android)

#Google (Coming Soon)

Support for Google's on-device models is planned for future releases.

Get started by choosing the approach that fits your needs!

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