Access Mac Studios with 512GB unified memory for AI inference, ML training, and GPU workloads impossible anywhere else. Enterprise power, pay-per-use simplicity.
Join developers worldwide on the waitlist. No spam, ever.
Why MetalCloud
The only cloud purpose-built for Apple Silicon. Run what others can't.
Run 70B+ parameter models unquantized. 512GB unified memory means no model splitting, no compromises on quality.
Native Metal Performance Shaders deliver GPU acceleration without the CUDA dependency. Built for Apple from the ground up.
Hardware-isolated execution, encrypted tunnels, and SOC 2 compliance. Your models and data never leave your control.
Distributed compute from Mac owners worldwide. No hyperscaler markup, no minimum commitments.
Compute nodes in 40+ countries. Run inference close to your users for sub-50ms latency.
Python SDK, REST API, and CLI tools. Deploy in minutes with familiar workflows. No lock-in.
Mac Studio M3 Ultra delivers capabilities no other cloud can match. This isn't just different-it's impossible on traditional infrastructure.
Get Started
From signup to inference in under 5 minutes. No infrastructure to manage.
One command: pip install metalcloud. Works with your existing Python environment.
Use our simple API to submit inference requests. We handle scheduling, load balancing, and failover automatically.
Receive responses in real-time via streaming or batch. Pay only for compute time used, billed per second.
Simple Pricing
No subscriptions, no minimums. Just compute when you need it.
Perfect for development and small workloads
For production workloads and teams
Maximum capability for demanding workloads
FAQ
Everything you need to know about MetalCloud and Apple Silicon GPU computing.
MetalCloud offers access to Mac Studio M3 Ultra machines with 512GB of unified memory-the largest GPU-accessible memory available in any cloud. This is 6x more than a single NVIDIA H100 (80GB) and enables running Llama 70B at full FP16 precision on a single machine with 344GB to spare.
Yes. Llama 70B at full FP16 precision requires approximately 168GB of memory. MetalCloud's 512GB unified memory handles this easily-no quantization needed, no multi-GPU complexity. You can even add 128K+ token context windows without memory pressure. This capability is impossible on any single NVIDIA GPU.
MetalCloud offers Apple Silicon GPU compute from £0.40/hour (M3 Pro) to £3.50/hour (M3 Ultra with 512GB). For workloads requiring 512GB memory capacity, this is up to 10x cheaper than equivalent multi-GPU NVIDIA setups on AWS, which require 2-4 H100 GPUs costing $6,000-$12,000/month.
Unified memory is Apple Silicon's architecture where CPU and GPU share the same physical memory pool. Unlike NVIDIA GPUs with separate VRAM, unified memory means zero data transfer overhead, no PCIe bottleneck, and the full 512GB is accessible to GPU compute. This enables massive models and long context windows on a single machine.
MetalCloud is optimized for MLX (Apple's machine learning framework), PyTorch with Metal backend, TensorFlow Metal, and any workload that benefits from Apple Silicon. Our Python SDK makes deployment simple with familiar APIs. We also support iOS/macOS CI/CD workloads.
Join our waitlist to get early access. Once approved, install our Python SDK with pip install metalcloud, authenticate with your API key, and submit your first job. Most developers go from signup to running inference in under 5 minutes. No infrastructure to manage-we handle scheduling, load balancing, and failover.
Join thousands of developers already on the waitlist. Be first to access hardware that changes everything.