If you run local AI models, you know the brutal reality of the VRAM paywall. If an AI model requires 18 GB of memory and your computer has 16 GB, the model simply crashes with an Out of Memory (OOM) error.
Historically, solving this meant spending $1,500 to $2,500 on an enterprise-grade GPU or buying a whole new workstation. But with the official release of RAMDeck Distributed AI on the Apple App Store, an entirely new solution is available: pooling the idle memory of the devices already sitting on your desk.
The Apple Silicon Advantage
Modern iPhones (such as the iPhone 15 Pro and iPhone 16 series) feature A17 Pro and A18 chips with Apple Metal 3 GPU shaders and unified memory delivering ~60 GB/s to 68 GB/s bandwidth. While iOS reserves roughly 3.5 GB for operating system processes, an iPhone safely contributes ~3.2 GB to 4.5 GB of active working memory to a local cluster.
Docking two iPhones overnight adds over 5.2 GB of active GPU memory—providing the exact headroom needed to load and evaluate 30B parameter models without buying new hardware.
Proven in Live Benchmarks
In verified live hardware testing, a MacBook M3 that could not fit an 18GB Qwen 30B model alone was paired with an iPhone 16 and an iPhone XS over standard Wi-Fi. The sharded model loaded in under 30 seconds and generated conversational responses in under 5 seconds.
The RAMDeck iOS Node is available on the Apple App Store. Hardware hubs are currently available for pre-order at $109 on Indiegogo.
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