What is RunAnywhere?

RunAnywhere provides infrastructure for deploying AI models directly on mobile and edge devices. Part of YC W2026, it was founded by Sanchit Monga (CEO, ex-Intuit, products used by 50M+ users) and Shubham Malhotra (CTO, who built MetalRT — the first complete multi-modal inference engine for Apple Silicon, ex-Amazon EC2 Spot M+ ARR).

The offering is a unified SDK (iOS Swift, Android Kotlin, React Native, Flutter) plus an enterprise control plane for managing model rollouts, policies, and analytics across thousands of devices. The SDK includes MetalRT achieving 668 tokens/second LLM decode on Apple Silicon, 101ms speech-to-text latency, and 287 tokens/second vision inference — all running locally on device.

A key differentiator is hybrid routing: when a device cannot handle a model locally, requests automatically fall back to cloud inference. The control plane enables OTA model updates without app store releases. The open-source SDKs have 10.1K GitHub stars with demo apps live on both iOS App Store and Google Play.

Key features

Core capabilities this platform advertises.

On-device AI deployment
Edge orchestration
Scale management
Device-agnostic runtime

Strengths and tradeoffs

What this tool does well, and the limitations to keep in mind.

Pros

Strong open-source traction with 10.1K GitHub stars and working mobile apps
CTO built MetalRT from scratch with impressive on-device benchmarks
Hybrid routing solves the key reliability problem of on-device AI
Multi-platform SDK covers the entire mobile ecosystem
Enterprise control plane with OTA updates creates clear monetization path

Cons

Plans & pricing

What's included in each plan, and how the tiers compare.

Open Source SDK

Free

iOS, Android, React Native, Flutter
MetalRT runtime
On-device inference

Enterprise Control Plane

Contact for pricing

Common use cases

Teams deploying AI models on edge devices

Edge AI deployment
On-device inference
IoT AI applications
Offline AI

Using RunAnywhere with Respan

RunAnywhere deploys models on edge devices while Respan monitors cloud-based LLM calls. For hybrid routing scenarios, Respan can track the cloud inference fallbacks.

Monitor cloud fallback LLM calls from RunAnywhere devices via Respan
Track hybrid routing costs across on-device and cloud inference
Evaluate output quality differences between on-device and cloud inference via Respan