How to Run Llama 4 Scout on Apple Silicon via Ollama MLX Verify your Mac has Apple Silicon (M1+) with at least 16 GB unified memory and macOS 13+. Install Ollama via Homebrew and confirm the MLX backend is active in server logs. Select a quantization level (Q4–Q8) matched to your Mac's memory tier. Pull the appropriate Llama 4 Scout model tag from the Ollama registry. Configure environment variables for memory management and context window size. Run interactive inference with --verbose to validate token throughput. Monitor memory pressure during generation to ensure swap stays minimal. Integrate with Python applications using Ollama's OpenAI-compatible REST API. Scout's MoE sparsity and Apple's unified memory solve each other's bottlenecks. Running Llama 4 Scout locally on Apple Silicon through Ollama eliminates cloud inference costs while delivering performance that consumer hardware couldn't reach before 2025.…