On-device AI for every platform.
Run LLMs, vision, speech-to-text, and text-to-speech locally. Private, offline, fast.
One SDK for iOS, Android, Flutter, React Native, and Web, with Hexagon NPU acceleration on Snapdragon.

RunAnywhere lets you add AI features to your app that run entirely on-device, with no cloud, no latency, and no data leaving the device:

• LLM Chat: Llama, Qwen, Gemma, Phi, LFM, Mistral, and more
• Vision (VLM): image understanding and captioning
• Speech-to-Text: Whisper- and Moonshine-based transcription
• Text-to-Speech: neural voice synthesis
• Voice Assistant: a full speech-to-text, LLM, and text-to-speech pipeline

One API spans iOS, Android, Flutter, React Native, and Web, and routes to the best engine on each device: Core ML on Apple, WebGPU in the browser, llama.cpp everywhere as a fallback, and the Hexagon NPU on Snapdragon.

QHexRT is RunAnywhere's inference runtime for the Qualcomm Hexagon NPU. It runs LLM, vision, speech, and text-to-speech models directly on the Snapdragon NPU (Hexagon v79 / v81) and ships as a built-in accelerator: your app calls the same loadModel and generate, and it uses the NPU automatically on supported devices.

• Runs LLM, VLM, speech-to-text, and text-to-speech on the NPU, including text-to-speech, which other runtimes run on the CPU.
• Runs Mixture-of-Experts and hybrid-attention models on the NPU (Phi-tiny-MoE, Qwen3.5).
• Fast prefill and low time-to-first-token, with context that extends past the compiled window.
• Prebuilt model bundles published on Hugging Face; the SDK downloads the one matching the device.

Measured on a Samsung Galaxy S25 (Snapdragon 8 Elite, Hexagon v79):

Available on the Kotlin, Flutter, and React Native SDKs. Snapdragon (Android arm64) only.

Text Generation LLM inference, 100% on-device		Voice AI STT to LLM to TTS pipeline, fully offline
Image Generation On-device diffusion model		Visual Language Model Vision + language understanding on-device

import RunAnywhere
import LlamaCPPRuntime

// 1. Initialize
LlamaCPP.register()
try RunAnywhere.initialize()

// 2. Load a model
var load = RAModelLoadRequest()
load.modelID = "smollm2-360m"
load.category = .language
load.framework = .llamaCpp
_ = await RunAnywhere.loadModel(load)

// 3. Generate
var req = RALLMGenerateRequest()
req.prompt = "What is the capital of France?"
let result = try await RunAnywhere.generate(req)
print(result.text) // "Paris is the capital of France."

Install via Swift Package Manager:

https://github.com/RunanywhereAI/runanywhere-sdks

Documentation · Source code

import com.runanywhere.sdk.public.RunAnywhere
import com.runanywhere.sdk.public.extensions.*

// 1. Initialize
LlamaCPP.register()
RunAnywhere.initialize(environment = SDKEnvironment.DEVELOPMENT)

// 2. Load a model
RunAnywhere.downloadModel("smollm2-360m").collect { println("${it.progress * 100}%") }
RunAnywhere.loadLLMModel("smollm2-360m")

// 3. Generate
val response = RunAnywhere.chat("What is the capital of France?")
println(response) // "Paris is the capital of France."

Install via Gradle:

dependencies {
    implementation("com.runanywhere.sdk:runanywhere-kotlin:0.16.1")
    implementation("com.runanywhere.sdk:runanywhere-core-llamacpp:0.16.1")
}

Documentation · Source code

import { RunAnywhere, SDKEnvironment } from '@runanywhere/core';
import { LlamaCPP } from '@runanywhere/llamacpp';

// 1. Initialize
await RunAnywhere.initialize({ environment: SDKEnvironment.Development });
LlamaCPP.register();

// 2. Load a model
await RunAnywhere.downloadModel('smollm2-360m');
await RunAnywhere.loadModel('smollm2-360m');

// 3. Generate
const response = await RunAnywhere.chat('What is the capital of France?');
console.log(response); // "Paris is the capital of France."

Install via npm:

npm install @runanywhere/core @runanywhere/llamacpp

Documentation · Source code

import 'package:runanywhere/runanywhere.dart';
import 'package:runanywhere_llamacpp/runanywhere_llamacpp.dart';

// 1. Initialize
await RunAnywhere.initialize();
await LlamaCpp.register();

// 2. Load a model
await RunAnywhere.downloadModel('smollm2-360m');
await RunAnywhere.loadModel('smollm2-360m');

// 3. Generate
final response = await RunAnywhere.chat('What is the capital of France?');
print(response); // "Paris is the capital of France."

Install via pub.dev:

dependencies:
  runanywhere: ^0.16.0
  runanywhere_llamacpp: ^0.16.0  # LLM text generation
  # runanywhere_onnx: ^0.16.0   # Add this if you need STT, TTS, or Voice features

Documentation · Source code

import { RunAnywhere } from '@runanywhere/web';

// 1. Initialize
await RunAnywhere.initialize({ environment: 'development' });

// 2. Load a model
await RunAnywhere.loadModel({
  id: 'qwen2.5-0.5b',
  source: '/models/qwen2.5-0.5b-instruct-q4_0.gguf',
});

// 3. Generate
const result = await RunAnywhere.generate({
  prompt: 'What is the capital of France?',
});
console.log(result.text); // "Paris is the capital of France."

Install via npm:

npm install @runanywhere/web

Source code

Prebuilt bundles published on Hugging Face; the SDK downloads the one matching the device.

Browse all models on Hugging Face

The Android, Flutter, and React Native apps include an NPU section that detects the device's Hexagon arch and runs LLM, vision, speech, and text-to-speech on the NPU.

Minimal projects to get up and running on each platform:

Real-world projects built with RunAnywhere. Each ships as a standalone app you can build and run.

• Android Use Agent: an on-device autonomous Android agent that reads the screen and controls the phone with an on-device LLM. Benchmarks.
• On-Device Browser Agent: a Chrome extension that automates browser tasks on-device with WebLLM and WebGPU.
• Swift Starter App: a SwiftUI app with LLM chat, speech-to-text, text-to-speech, and a full voice pipeline.
• Linux Voice Assistant: an on-device voice pipeline (wake word, VAD, STT, LLM, TTS) in one C++ binary for Raspberry Pi 5, x86_64, and ARM64.
• OpenClaw Hybrid Assistant: on-device wake word, VAD, STT, and TTS with cloud LLM reasoning and barge-in.

A single C/C++ core (runanywhere-commons) behind a C ABI, with thin platform SDKs on top and a plugin registry that selects the best engine per device (llama.cpp, ONNX/sherpa, Core ML, Metal, and QHexRT on the Hexagon NPU). Business logic lives in the core, so one fix lands on all five SDKs.

runanywhere-sdks/
├── sdk/
│   ├── runanywhere-swift/          # iOS/macOS SDK
│   ├── runanywhere-kotlin/         # Android SDK
│   ├── runanywhere-web/            # Web SDK (WebAssembly / WebGPU)
│   ├── runanywhere-react-native/   # React Native SDK
│   ├── runanywhere-flutter/        # Flutter SDK
│   └── runanywhere-commons/        # Shared C/C++ core
│
├── engines/                        # Pluggable inference backends
├── examples/                       # Sample apps
├── Playground/                     # Real-world reference apps
└── docs/                           # Documentation

Hexagon NPU: Snapdragon with Hexagon v79 / v81 (Snapdragon 8 Elite class), Android arm64. Memory: 2 GB minimum, 4 GB+ recommended for larger models.

We welcome contributions. See our Contributing Guide for details.

git clone https://github.com/RunanywhereAI/runanywhere-sdks.git
cd runanywhere-sdks

# Build the native XCFrameworks into sdk/runanywhere-swift/Binaries/.
# Required for local Swift development.
./sdk/runanywhere-swift/scripts/build-core-xcframework.sh

# Run the iOS sample app
cd examples/ios/RunAnywhereAI
open RunAnywhereAI.xcodeproj

• Docs: docs.runanywhere.ai
• Discord: Join our community
• Issues: GitHub Issues
• Email: founders@runanywhere.ai
• Twitter: @RunanywhereAI

Apache 2.0. See LICENSE for details.