react-native-nitro-tflite

High-performance TensorFlow Lite library for React Native, powered by Nitro Modules.

Note: This is an unofficial Nitro Module migration of react-native-fast-tflite, fully optimized for the New Architecture, Bridgeless mode, and Vision Camera frame processors.

This library provides the same API as the original, with the following improvements:

• ✅ HybridObject-based — No more install() or global JSI functions
• ✅ Works from any frame processor/worklet — Can be called from any thread/runtime
• ✅ Bridge/Bridgeless agnostic — Works on both architectures automatically
• ✅ Same API — Drop-in replacement, same loadTensorflowModel() and useTensorflowModel()

Installation

npm install react-native-nitro-tflite react-native-nitro-modules

iOS

cd ios && pod install

Android

No additional steps needed. The TFLite libraries are automatically downloaded via Gradle.

Usage

import { useTensorflowModel } from 'react-native-nitro-tflite'

function App() {
  const model = useTensorflowModel(require('./model.tflite'))

  if (model.state === 'loaded') {
    console.log('Inputs:', model.model.inputs)
    console.log('Outputs:', model.model.outputs)

    // Run inference
    const output = model.model.runSync([inputData])
  }

  return <View />
}

Loading from URL

import { loadTensorflowModel } from 'react-native-nitro-tflite'

const model = await loadTensorflowModel(
  { url: 'https://example.com/model.tflite' },
  'default'
)

Delegates

| Delegate | Platform | Description | | ------------- | -------- | ----------------------------- | | default | Both | CPU inference | | core-ml | iOS | Apple CoreML acceleration | | metal | iOS | Metal GPU (not yet supported) | | nnapi | Android | Android Neural Networks API | | android-gpu | Android | Android GPU delegate |

Architecture

This library uses Nitro Modules with manual C++ HybridObject implementation:

• HybridTfliteModel — Wraps TfLiteInterpreter with run/runSync/inputs/outputs/delegate
• HybridTfliteModelFactory — Factory for loading models with platform-specific URL fetching

JS:  loadTensorflowModel()
       ↓
     NitroModules.createHybridObject("TfliteModelFactory")
       ↓
     factory.loadModel(url, delegate)
       ↓
C++: HybridTfliteModelFactory::loadModelRaw()
       ↓
     TfLiteModelCreate() + TfLiteInterpreterCreate()
       ↓
     new HybridTfliteModel(interpreter)  ← returned to JS as HybridObject

Metro Configuration

Add tflite as an asset extension in your metro.config.js:

const { getDefaultConfig } = require('@react-native/metro-config')

const config = getDefaultConfig(__dirname)
config.resolver.assetExts.push('tflite')

module.exports = config

License

MIT