https://blog-8ye.pages.dev/en/categories/ai-ops/ Recent content in Ai-Ops on Tech Blog Hugo -- gohugo.io en © 2026 Plus Tue, 31 Mar 2026 09:00:00 +0900 https://blog-8ye.pages.dev/en/posts/apple-silicon-ollama-mlx-local-llm-optimization/ Tue, 31 Mar 2026 09:00:00 +0900 https://blog-8ye.pages.dev/en/posts/apple-silicon-ollama-mlx-local-llm-optimization/ <p><figure><img class="my-0 rounded-md" loading="lazy" decoding="async" fetchpriority="low" alt="Apple Silicon Unified Memory Architecture and Local LLM Execution" src="https://blog-8ye.pages.dev/images/posts/apple-silicon-ollama-mlx-local-llm-optimization/svg-1-en.svg" ></figure> </p> <p>A single cloud API call costs a few cents. Hundreds of calls per day, and the monthly bill becomes alarming. Add data privacy concerns, and a natural question arises: <strong>&ldquo;Can I just run the LLM on my MacBook?&rdquo;</strong></p> <p>The answer is a resounding yes. Apple Silicon&rsquo;s <strong>Unified Memory Architecture (UMA)</strong> is a game changer for local LLM inference. Because the CPU and GPU share the same memory pool, there&rsquo;s no need to split models across VRAM boundaries or deal with PCIe offloading bottlenecks — you can load massive models directly into unified memory.</p>