React Native AI

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.

Features

• 🚀 Instant AI - Use built-in system models immediately without downloads
• 🔒 Privacy-first - All processing happens on-device, data stays local
• 🎯 Vercel AI SDK compatible - Drop-in replacement with familiar APIs
• 🎨 Complete toolkit - Text generation, embeddings, transcription, speech synthesis

AI SDK Compatibility

React Native AI	AI SDK
0.11 and below	v5
0.12 and above	v6

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.

npm install @react-native-ai/dev-tools

Rozenite must be installed and enabled in your app. See the Rozenite getting started guide.

Available Providers

Provider	Built-in	Platforms	Runtime	Description
Apple	✅ Yes	iOS	Apple	Apple Foundation Models, embeddings, transcription, speech
Llama	❌ No	iOS, Android	llama.rn	Run GGUF models via llama.rn
MLC	❌ No	iOS, Android	MLC LLM	Run open-source LLMs via MLC runtime

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Apple

Native integration with Apple's on-device AI capabilities. Built-in - no model downloads required, uses system models.

• Text Generation - Apple Foundation Models for chat and completion
• Embeddings - NLContextualEmbedding for 512-dimensional semantic vectors
• Transcription - SpeechAnalyzer for fast, accurate speech-to-text
• Speech Synthesis - AVSpeechSynthesizer for natural text-to-speech with system voices

Installation

npm install @react-native-ai/apple

No additional linking needed, works immediately on iOS devices (autolinked).

Usage

import { apple } from '@react-native-ai/apple'
import {
  generateText,
  embed,
  experimental_transcribe as transcribe,
  experimental_generateSpeech as speech,
} from 'ai'

// Text generation with Apple Intelligence
const { text } = await generateText({
  model: apple(),
  prompt: 'Explain quantum computing',
})

// Generate embeddings
const { embedding } = await embed({
  model: apple.textEmbeddingModel(),
  value: 'Hello world',
})

// Transcribe audio
const { text } = await transcribe({
  model: apple.transcriptionModel(),
  audio: audioBuffer,
})

// Text-to-speech
const { audio } = await speech({
  model: apple.speechModel(),
  text: 'Hello from Apple!',
})

Availability

Feature	iOS Version	Additional Requirements
Text Generation	iOS 26+	Apple Intelligence device
Embeddings	iOS 17+	-
Transcription	iOS 26+	-
Speech Synthesis	iOS 13+	iOS 17+ for Personal Voice

See the Apple documentation for detailed setup and usage guides.

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Llama

Run any GGUF model on-device using llama.rn. Requires download - models are downloaded from HuggingFace.

Supported Features

Feature	Method	Description
Text Generation	llama.languageModel()	Chat, completion, streaming, reasoning models
Embeddings	llama.textEmbeddingModel()	Text embeddings for RAG and similarity search
Speech	llama.speechModel()	Text-to-speech with vocoder models

Installation

npm install @react-native-ai/llama llama.rn react-native-blob-util

Usage

import { llama } from '@react-native-ai/llama'
import { generateText, streamText } from 'ai'

// Create model instance (Model ID format: "owner/repo/filename.gguf")
const model = llama.languageModel(
  'ggml-org/SmolLM3-3B-GGUF/SmolLM3-Q4_K_M.gguf'
)

// Download from HuggingFace (with progress)
await model.download((progress) => {
  console.log(`Downloading: ${progress.percentage}%`)
})

// Initialize model (loads into memory)
await model.prepare()

// Generate text
const { text } = await generateText({
  model,
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Write a haiku about coding.' },
  ],
})

// Cleanup when done
await model.unload()

Model Compatibility

Any GGUF model from HuggingFace can be used. Use the format owner/repo/filename.gguf as the model ID. Popular choices include:

• ggml-org/SmolLM3-3B-GGUF/SmolLM3-Q4_K_M.gguf
• bartowski/Llama-3.2-3B-Instruct-GGUF/Llama-3.2-3B-Instruct-Q4_K_M.gguf
• Qwen/Qwen2.5-1.5B-Instruct-GGUF/qwen2.5-1.5b-instruct-q4_k_m.gguf

📚 View full Llama documentation →

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MLC

Run popular open-source LLMs directly on-device using MLC LLM's optimized runtime. Requires download - models must be downloaded before use.

Installation

npm install @react-native-ai/mlc

Requires the "Increased Memory Limit" capability in Xcode. See the getting started guide for setup instructions.

Usage

import { mlc } from '@react-native-ai/mlc'
import { generateText } from 'ai'

// Create model instance
const model = mlc.languageModel('Llama-3.2-3B-Instruct')

// Download and prepare model (one-time setup)
await model.download()
await model.prepare()

// Generate response with Llama via MLC engine
const { text } = await generateText({
  model,
  prompt: 'Explain quantum computing',
})

Available Models

Model ID	Size
Llama-3.2-3B-Instruct	~2GB
Phi-3-mini-4k-instruct	~2.5GB
Mistral-7B-Instruct	~4.5GB
Qwen2.5-1.5B-Instruct	~1GB

Documentation

Comprehensive guides and API references are available at react-native-ai.dev.

Contributing

Read the contribution guidelines before contributing.

Agent skills

This repository provides agent skills to help you integrate and use the packages. You can easily install them with:

npx skills add https://github.com/callstackincubator/react-native-ai --skill react-native-ai-skills

or manually by copying the skills/ directory in your .cursor/ directory.

Made with ❤️ at Callstack

react-native-ai is an open source project and will always remain free to use. If you think it's cool, please star it 🌟.

Callstack is a group of React and React Native geeks, contact us at hello@callstack.com if you need any help with these or just want to say hi!

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Made with create-react-native-library