RunanywhereAI/runanywhere-sdks

Health v2 · maintenance only

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10282 stars · 369 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

RunAnywhere is a set of cross-platform SDKs (Swift, Kotlin, React Native, Flutter, TypeScript, C++) over a shared C++ core for running AI models fully on-device — LLM chat, speech-to-text, text-to-speech, vision, embeddings, RAG, and image generation. It routes inference to hardware-appropriate engines (llama.cpp, MLX, Core ML, Qualcomm NPU, WebGPU) with a unified API and a console for model deployment and telemetry.

Use cases

• run llm inference locally on ios and android
• build an offline voice assistant with stt and tts
• add private on-device chatbot to a mobile app
• run speech-to-text without a server
• generate images on-device with stable diffusion
• do rag with local embeddings on mobile
• run ai models in the browser with webgpu
• deploy on-device ai across a fleet of devices

When to choose

• you need private, offline AI inference on phones, browsers, or desktops
• you want one unified API across multiple platforms and model engines
• you need low-latency voice pipelines (STT, TTS, VAD) on mobile
• you want to exploit device NPUs/GPUs like Apple Neural Engine or Qualcomm Hexagon

When to avoid

• you need large-scale server-side inference on datacenter GPUs
• you require a permissive open-source license (the license is custom, not OSI-approved)
• you only need a simple cloud API call with no on-device footprint
• your target platform is not among the supported SDKs

Facets

library · maturity active

llm-inference speech-recognition tts rag machine-learning sdk image-processing chatbot artificial-intelligence large-language-models mobile-development cross-platform speech-processing privacy windows browser wasm cpp python cross-platform on-device-ai edge-ai llamacpp npu-acceleration voice-agents multimodal offline-inference react-native flutter mobile-sdk ios android macos linux web swift

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