Run 397B parameter Mixture-of-Experts LLMs on a MacBook using pure C/Metal with SSD streaming
Flash-MoE Inference Engine Skill by ara.so — Daily 2026 Skills collection. Flash-MoE is a pure C/Objective-C/Metal inference engine that runs Qwen3.5-397B-A17B (397B parameter Mixture-of-Experts) on a MacBook Pro with 48GB RAM at 4.4+ tokens/second. It streams 209GB of expert weights from NVMe SSD on demand — no Python, no ML frameworks, just C, Objective-C, and hand-tuned Metal shaders. Requirements Hardware: Apple Silicon Mac (M3 Max or similar), 48GB+ unified memory, 1TB+ SSD with ~210GB free OS: macOS 26+ (Darwin 25+) Tools: Xcode Command Line Tools, Python 3.x (for weight extraction only) Model: Qwen3.5-397B-A17B safetensors weights (download separately from HuggingFace) Installation & Build # Clone the repo git clone https://github.com/danveloper/flash-moe cd flash-moe/metal_infer
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