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 - Inference runs on-device, so data stays local. Cloud models are opt-in
• 🎯 Vercel AI SDK compatible - Use generateText, streamText, embed and other AI SDK functions with local models
• 🎨 Beyond text - Embeddings, transcription, speech synthesis and image generation

AI SDK Compatibility

React Native AI	AI SDK
0.11 and below	v5
0.12	v6
0.13 and above	v7

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.

The Expo demo app in apps/expo-example includes native-development Rozenite wiring for this plugin. Run the example app, open React Native DevTools, and select AI SDK Profiler to inspect chat spans emitted by the Vercel AI SDK.

If the AI SDK Profiler panel stays empty after you send a message, close the React Native DevTools window and open a new one. A stale debugger session can keep the panel mounted without receiving telemetry.

Available Providers

Provider	Built-in	Platforms	Runtime	Description
Apple	✅ Yes	iOS	Apple	Apple Foundation Models, embeddings, transcription, speech
Core AI	❌ No	iOS	Core AI	Run app-provided Core AI model bundles
ADK	✅ Yes	Android	Google ADK	On-device Gemini Nano, with optional cloud Gemini
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,
  transcribe,
  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.embeddingModel(),
  value: 'Hello world',
})

// Transcribe audio
const { text: transcript } = 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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Core AI

Run your own Core AI model bundles (.aimodel) exported with apple/coreai-models. For Apple's built-in system models, use Apple instead.

• Text Generation - generateText and streamText, plus persistent native sessions
• Image Generation - generateImage with diffusion models such as FLUX.2 and Sana Sprint
• Segmentation and Object Detection - Direct native APIs, since the AI SDK has no equivalent

Embeddings and transcription are not supported yet (#237).

Installation

npm install @react-native-ai/core-ai

Important

Apps need an iOS 27 deployment target and build for physical devices only, since the iOS Simulator SDK has no CoreAI framework.

Usage

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

const model = coreAI.languageModel({
  id: 'qwen3-0.6b',
  source: { type: 'file', uri: qwen3ModelDirectory },
  variant: 'iOS',
})

const { text } = await generateText({
  model,
  prompt: 'Explain Core AI',
})

See the Core AI documentation for setup, starter models, and direct native APIs.

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Google ADK

Run Gemini Nano on-device on Android through Google's Agent Development Kit. Built-in - Gemini Nano is provisioned by the system via AICore, so there are no model files to bundle and no API key. Cloud Gemini is available as an option.

• Text Generation - generateText and streamText with on-device Gemini Nano
• Tool Calling - Native ADK agent loop with JavaScript tool executors
• Cloud Gemini - Optional cloud inference via ADK LlmAgent when you need a larger model

Installation

npm install @react-native-ai/adk

Important

Requires Android minSdkVersion 26 and a physical device with AICore support (Android 14+) for Gemini Nano. Your app also needs packaging excludes for duplicate META-INF files, see the getting started guide.

Usage

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

if (!(await adk.isAvailable())) {
  throw new Error('Gemini Nano is not available on this device')
}

await adk.prepareNano()

const { text } = await generateText({
  model: adk(),
  prompt: 'Explain quantum computing',
})

See the ADK documentation for device checks, cloud Gemini, and tool calling.

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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.embeddingModel()	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 { downloadModel, llama } from '@react-native-ai/llama'
import { generateText } from 'ai'

// Download from HuggingFace (Model ID format: "owner/repo/filename.gguf")
const modelPath = await downloadModel(
  'bartowski/Qwen_Qwen3.5-2B-GGUF/Qwen_Qwen3.5-2B-Q4_K_M.gguf',
  (progress) => console.log(`Downloading: ${progress.percentage}%`)
)

// Create model instance
const model = llama.languageModel(modelPath)

// 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:

• bartowski/Qwen_Qwen3.5-2B-GGUF/Qwen_Qwen3.5-2B-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

Note

MLC requires iOS devices with sufficient memory (1-8GB depending on model). The prebuilt runtime supports the models listed above. For other models or custom configurations, you'll need to recompile the MLC runtime from source.

JSON UI

@react-native-ai/json-ui lets a tool-calling model build React Native UI. The model calls tools that add, update, and delete nodes in a JSON spec, and GenerativeUIView renders it. It's designed for small on-device models with limited context.

npm install @react-native-ai/json-ui

See the JSON UI documentation.

Documentation

Guides and API reference 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 into your agent's skills directory (for example .cursor/skills/).

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