AI power.
Right on your desk.

🄏Mac (Apple Silicon)

• ✓ CPU and GPU share the same physical memory pool
• ✓ A 24GB Mac = 24GB available for model loading on GPU
• ✓ No copying between CPU RAM and GPU VRAM—zero transfer overhead
• ✓ Models that exceed traditional GPU VRAM just work—they use the same memory
• ✓ 70B parameter models run on a Mac Studio with 192GB unified memory
• Memory bandwidth:
  M4 = 120 GB/s | M4 Pro = 273 GB/s | M4 Max = 546 GB/s | M4 Ultra ≈ 800+ GB/s

🪟Windows (NVIDIA GPU)

• ✗ CPU has its own RAM (e.g. 64GB DDR5)
• ✗ GPU has separate VRAM (e.g. RTX 4090 = 24GB VRAM)
• ✗ Models must fit entirely in GPU VRAM for fast inference
• ✗ If a model exceeds VRAM, it spills to CPU RAM via slow PCIe bus (~32 GB/s)
• ✗ Running a 70B model? You need 2-4x RTX 4090s ($6,000-$12,000+ in GPUs alone)
• ✗ Most consumer Windows PCs max out at 24GB VRAM

Key Features

• ✓ Apple's open-source ML framework purpose-built for Apple Silicon
• ✓ Lazy evaluation, dynamic graph construction, multi-device support
• ✓ Arrays live in unified memory—operate on by any device without data copies
• ✓ Growing model ecosystem: 5,000+ optimized models on mlx-community/HuggingFace
• ✓ Quantization support (4-bit, 8-bit) for larger models in less memory
• ✓ LoRA fine-tuning directly on your Mac—no cloud GPUs needed

Technical Advantage

MLX is purpose-built for Apple's chip architecture. Unlike CUDA (which targets NVIDIA), MLX is optimized for:

• • Unified memory bandwidth efficiency
• • CPU-GPU kernel fusion for data locality
• • Metal performance for GPU-accelerated linear algebra
• • Zero-copy data sharing across Neural Engine and GPU

Mac mini M4

5-20W idle, 40-65W under full AI load

Windows Rig

200-600W under load (GPU alone = 350W+)

Annual Savings

Significant for 24/7 AI server use (5-10x less power)

5+ Year Lifespan

Apple Silicon ages well. Retains 60-70% value after 3 years

🔒macOS Security

• ✓ Secure Enclave for encryption keys
• ✓ FileVault full-disk encryption (hardware-accelerated)
• ✓ Gatekeeper + XProtect built-in malware protection
• ✓ No telemetry sent to third parties by default
• ✓ Local AI = data never leaves your device
• ✓ PDPO/GDPR compliance easier with local processing

⚠️Windows Telemetry

• ✗ Default telemetry collection
• ✗ Cortana + OneDrive sync
• ✗ Recall feature (screenshots every few seconds)
• ✗ Copilot cloud processing
• ✗ Updates may expose sensitive data
• ✗ AI features require cloud integration

🍎Mac with Homebrew

• ✓ Simple package manager: `brew install ollama` = 60 seconds
• ✓ Docker Desktop native on Apple Silicon (ARM containers)
• ✓ Python, Node.js, Rust—all first-class citizens
• ✓ Terminal + SSH + Unix tools built-in
• ✓ Git, package managers, dev tools pre-optimized

🪟Windows + WSL2

• ✗ Requires WSL2 for most AI tools
• ✗ CUDA driver management and versioning hell
• ✗ cuDNN dependency conflicts
• ✗ DirectML limitations for many frameworks
• ✗ Virtual machine overhead (WSL2 = Hyper-V)

Mac mini

12.7cm × 12.7cm, fits on a shelf. Whisper-quiet under load.

Mac Studio

Compact desktop. Silent (no GPU fans, no coil whine).

24/7 Operation

Perfect for office, studio, or home environments without noise complaints.