RunAnywhere: Production-Grade On-Device AI Infrastructure
The Problem
Teams can get one model running on one device in a few days. Shipping that to a production device fleet is a different problem entirely.
The real blockers are:
- Fragmentation. Every platform, OS version, and device class behaves differently.
- Runtime complexity. Different model formats and backends need different integration paths.
- Operational overhead. Updating models, rolling back broken versions, and monitoring inference health across a fleet requires a control plane that most teams do not have.
- Latency. Interactive AI experiences, especially voice, need lower latency than cloud round-trips can deliver.
- Privacy. Finance, healthcare, and enterprise workloads cannot send raw user data to external APIs.
Without an abstraction layer, teams spend months building custom infrastructure before shipping anything.
What RunAnywhere Provides
Unified SDK
One API across six platforms:
| Platform | Status |
|---|---|
| Android | Production |
| iOS | Production |
| Web | Production |
| React Native | Production |
| macOS | Production |
| Flutter | Production |
Write the integration once. Deploy everywhere.
Multimodal Inference
RunAnywhere handles three AI modalities out of the box:
- LLM text generation and chat
- Speech-to-Text transcription
- Text-to-Speech synthesis
All running on-device. All through the same SDK.
Model-Agnostic
RunAnywhere does not lock you into a specific model family or format. The SDK supports any model that fits the device, from compact 135M parameter models to 4B+ parameter models on capable hardware. Bring whatever works for your use case.
Control Plane
The SDK is only the runtime layer. RunAnywhere also provides operational tooling:
- OTA model updates and rollback controls
- Policy-based hybrid routing (on-device first, cloud fallback when needed)
- Device and session analytics
- Fleet observability and reliability monitoring
This is the difference between "we can run a model" and "we can operate AI across a device fleet."
Built for Real Devices
RunAnywhere runs on real hardware in production, not just benchmarks on flagship devices. The SDK handles the full spectrum from high-end to budget:
- Flagship: iPhone 17 Pro Max, Galaxy S24 Ultra, iPad
- Mid-range: OPPO, Xiaomi, Samsung Galaxy A series
- Budget: Infinix, entry-level Samsung
- Desktop: MacBook (macOS)
- Web: Chrome, Safari, Firefox
This matters because most of the world does not own flagship hardware. If your on-device AI only works on the latest iPhone, it does not work at scale.
The platform currently processes over 250,000 on-device inference events per week across all supported platforms and device types.
MetalRT: Our Apple Silicon Inference Engine
For Apple devices, RunAnywhere ships MetalRT, a native C++ inference engine built directly on Apple's Metal GPU API.
MetalRT is the fastest inference engine available for Apple Silicon across all three AI modalities.
LLM Decode
| Model | MetalRT | llama.cpp | Apple MLX |
|---|---|---|---|
| Qwen3-0.6B | 658 tok/s | 295 | 552 |
| Qwen3-4B | 186 tok/s | 87 | 170 |
| LFM2.5-1.2B | 570 tok/s | 372 | 509 |
1.67x faster than llama.cpp. 1.19x faster than Apple MLX on the same model files.
Speech-to-Text (Whisper Tiny, 70s audio)
| Engine | Latency |
|---|---|
| MetalRT | 101ms |
| mlx-whisper | 463ms |
| sherpa-onnx | 554ms |
4.6x faster than Apple MLX. 714x faster than real-time.
Text-to-Speech (Kokoro-82M, 4 words)
| Engine | Latency |
|---|---|
| MetalRT | 178ms |
| mlx-audio | 493ms |
| sherpa-onnx | 504ms |
2.8x faster than Apple MLX.
All benchmarks on Apple M4 Max, 64 GB, macOS 26.3. Full benchmark methodology and results published separately.
Summary
RunAnywhere is production-grade on-device AI infrastructure. Not a wrapper around llama.cpp. Not a demo. Not a single-platform SDK.
It is a complete system for deploying, running, and operating multimodal AI across real device fleets at scale.
- Six platforms in production
- Multimodal: LLM, STT, and TTS through one SDK
- MetalRT: 658 tok/s LLM decode, 101ms STT, 178ms TTS on Apple Silicon
- Model-agnostic: works with any model that fits the device
If you are building AI that needs to run on real devices, in production, across platforms, RunAnywhere is the infrastructure for that.
- Website: runanywhere.ai
- GitHub: runanywhere-sdks
MetalRT benchmarks on Apple M4 Max, 64 GB, macOS 26.3.
