RunAnywhere SDK

Cross-platform on-device AI inference SDK

RunAnywhere SDK is a production-ready toolkit for running AI models entirely on-device across iOS, macOS, Android, Web, React Native, and Flutter. It provides a unified C++ core with platform-specific bindings for LLM text generation via llama.cpp, vision-language models, Whisper speech-to-text, Piper text-to-speech, and on-device image generation. All processing stays local with zero cloud dependency, ensuring privacy and low latency for mobile and edge AI applications.

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About RunAnywhere SDK

RunAnywhere SDK tackles the complexity of deploying AI models across heterogeneous mobile and edge devices. Rather than maintaining separate inference stacks for each platform, it provides a shared C++ core with native bindings for iOS, macOS, Android, WebAssembly, React Native, and Flutter. This architecture means a single model integration works consistently whether the app runs on an iPhone, an Android tablet, or a browser, without any cloud round-trips.

The SDK covers the full spectrum of on-device AI capabilities: LLM text generation powered by llama.cpp with streaming support, vision-language model inference for image understanding, Whisper-based speech-to-text, Piper text-to-speech, on-device image generation, and structured tool calling. A complete voice pipeline chains these components together for conversational AI experiences that run entirely locally. All data stays on the device, making it suitable for privacy-sensitive applications in healthcare, finance, and enterprise contexts.

Backed by Y Combinator, RunAnywhere also offers a cloud control plane for managing model deployments, enforcing policies, and measuring performance metrics across thousands of devices at scale. Starter templates and demo apps are provided for Swift, React Native with Expo, and Flutter, making it straightforward to prototype and ship on-device AI features. For developers building the next generation of offline-capable AI applications, RunAnywhere removes the infrastructure friction of cross-platform model deployment.

Pricing & Platform Specs

Pricing Summary

RunAnywhere SDK is a free and open-source cross-platform framework for on-device AI model execution across mobile, desktop, and edge hardware. Users run models locally with zero inference API costs, with optional commercial cloud fleet management and over-the-air model deployment available for enterprises.

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Supported Platforms

iOS, macOS, Android, Web, React Native, Flutter

Explore categories, tags & use cases

Use Cases

Local AI Workflows Mobile Development

Alternatives

All RunAnywhere SDK alternatives →

Ollama

Run LLMs locally with one command

Tool for running large language models locally on your machine with a simple CLI interface. Download and run Llama 3, Mistral, Gemma, Phi, Code Llama, and dozens of other open-source models with a single command. Features model management, GPU acceleration (NVIDIA/AMD/Apple Silicon), OpenAI-compatible API server, Modelfile for customization, and multi-model switching. Ideal for offline AI development, privacy-sensitive use cases, and local testing. 120K+ GitHub stars.

Open Source

llama.cpp

High-performance local LLM inference in C/C++

llama.cpp is the foundational C/C++ library with 75K+ GitHub stars powering local LLM inference on consumer hardware. Provides optimized CPU and GPU inference for quantized models in GGUF format. Supports LLaMA, Mistral, Phi, Gemma, and most open-weight families. Features 2-8 bit quantization for reduced memory, multi-GPU support, context extension, grammar-constrained output, and an OpenAI-compatible API server. The engine behind Ollama and LM Studio.

Open Source

vLLM

High-throughput LLM serving engine

vLLM is an Apache-2.0 LLM inference and serving engine focused on high-throughput self-hosted model APIs. It combines PagedAttention, continuous batching, prefix caching, quantization options, OpenAI-compatible serving, structured outputs, metrics, Docker/Kubernetes deployment guidance and integrations with agent and LLM frameworks.

Open Source

Nexa SDK

Cross-platform on-device AI model runtime

Nexa SDK enables running frontier LLMs and multimodal models locally across PC, mobile, IoT, and wearables with automatic hardware acceleration for GPU, NPU, and CPU. It supports Qwen, Gemma, Llama, DeepSeek models with Python/C++ desktop SDKs, Android/iOS mobile SDKs, and Docker for edge deployment. Includes an OpenAI-compatible API server with chat and function calling support.

Open Source

NCNN

High-performance mobile neural network inference

NCNN is Tencent's high-performance neural network inference framework optimized for mobile and embedded platforms. It features pure C++ with zero dependencies, ARM NEON assembly optimization, Vulkan GPU acceleration, and sophisticated memory management for minimal footprint. Supports importing models from PyTorch, ONNX, Caffe, TensorFlow, and Keras with 8-bit quantization and half-precision storage for efficient on-device deployment across Android, iOS, and Linux.

Open Source

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LLaMA-Factory

Unified framework for fine-tuning 100+ large language models

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Open Source

Tavily

Real-time search API built for AI agents

Tavily is an AI-native search API that provides real-time web search, content extraction, and crawling capabilities specifically designed for LLM applications and autonomous agents. It returns structured, citation-ready results optimized for RAG workflows with built-in safety features including prompt injection protection and PII leak prevention. Acquired by Nebius in 2026, Tavily integrates with LangChain, LlamaIndex, and major agent frameworks, serving over one million developers worldwide.

freemium

Firecrawl

Turn websites into LLM-ready structured data

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freemiumOpen Source

Unsloth

2x faster LLM fine-tuning with 70% less VRAM on a single GPU

Unsloth is an open-source framework for fine-tuning large language models up to 2x faster while using 70% less VRAM. Built with custom Triton kernels, it supports 500+ model architectures including Llama 4, Qwen 3, and DeepSeek on consumer NVIDIA GPUs. Unsloth Studio adds a no-code web UI for dataset creation, training observability, model comparison, and GGUF export for Ollama and vLLM deployment.

Open Source

VibeVoice

Microsoft's open-source frontier voice AI for long-form multi-speaker audio

VibeVoice is Microsoft's open-source voice AI family with both TTS and speech recognition models. The TTS model generates up to 90 minutes of expressive multi-speaker audio with 4 distinct voices. VibeVoice-ASR transcribes 60-minute recordings in a single pass with speaker identification and timestamps. Built on continuous speech tokenizers at 7.5 Hz and next-token diffusion, it compresses audio 80x more efficiently than Encodec while preserving fidelity.

Open Source

Community experience

Sources & verification

Sources checked: August 26, 2026
Content verified: August 26, 2026

Verification dates are editorial checks. Routine CMS saves and automatic updatedAt timestamps do not advance them.

FAQ

What is RunAnywhere SDK?

Is RunAnywhere SDK free?

RunAnywhere SDK offers a free tier alongside paid plans. RunAnywhere SDK is a free and open-source cross-platform framework for on-device AI model execution across mobile, desktop, and edge hardware. Users run models locally with zero inference API costs, with optional commercial cloud fleet management and over-the-air model deployment available for enterprises.

Is RunAnywhere SDK open source?

Yes — RunAnywhere SDK is open source.

Is RunAnywhere SDK still maintained?

Yes — RunAnywhere SDK is active. Its listing was last verified on August 26, 2026.

What are the best RunAnywhere SDK alternatives?

The first editor-selected RunAnywhere SDK alternatives are Ollama, llama.cpp, vLLM, and more.

RunAnywhere SDK

About RunAnywhere SDK

Pricing & Platform Specs

Pricing Summary

Supported Platforms

Categories

Tags

Use Cases

Alternatives

Ollama

llama.cpp

vLLM

Nexa SDK

NCNN