RunAnywhere is a toolkit for running AI models locally across multiple device platforms and operating systems.
The toolkit addresses the need to deploy language models, vision models, speech processing, voice agents, retrieval-augmented generation, embeddings, and image generation on edge devices while maintaining privacy and enabling offline operation. It accomplishes this through a unified C++ core that abstracts multiple inference engines—including llama.cpp, MLX, ONNX with Sherpa, Core ML, and cloud fallback—and exposes them via eight language-specific SDKs covering iOS, Android, web, React Native, Flutter, and desktop environments. The architecture includes a capability registry that routes each operation to the most appropriate engine available on the device, and hardware acceleration is automatically leveraged through device-specific processors such as the Apple Neural Engine, Hexagon NPU, Metal, CUDA, and WebGPU.
Developers should adopt this toolkit if they need to ship AI features across heterogeneous devices without maintaining separate inference implementations per platform. It suits projects requiring on-device execution for privacy or offline functionality, particularly those targeting mobile platforms alongside web and desktop. The unified semantic API means code written once can discover and use whatever inference capabilities the current device and package provide, reducing the complexity of cross-platform AI deployment.
Development activity shows consistent engagement with the project maintaining active documentation and providing example applications on both major mobile app stores. The toolkit is actively supported with a community Discord channel and curated model collections available through external repositories. The project demonstrates production-readiness through its focus on hardware acceleration across diverse silicon and its explicit capability discovery mechanism that prevents runtime failures from missing engines.
