MLX

MLX is like the engine running under the hood when you train or run AI models on a MacBook. On most computers, the chip that does the calculations and the memory that holds the data are physically separate, so moving data back and forth takes time. Apple Silicon chips are built differently — they combine compute and memory into one unified structure — and MLX is the tool Apple made to squeeze the most speed out of that unified design.

Thanks to this, tasks once thought to require large cloud servers — training a model from scratch, or fine-tuning one — can now be attempted on a single Mac. More recently, apps have started putting a graphical interface on top of MLX so users don't have to touch the engine directly. You just click buttons and drag sliders, and MLX runs underneath without you ever noticing it, giving you a local AI training experience.

MLX isn't limited to Apple's ecosystem alone. As more tools add support for MLX alongside the quantized file formats commonly used on Windows and Linux, MLX is becoming a gateway for Mac users to join the local AI workflow.

Articles use phrases like "a setup that runs computations through Apple's MLX framework" or "MLX is a machine learning framework tailored to Apple Silicon." One thing that's easy to mix up: MLX isn't the name of a specific AI model — it refers to the underlying software layer used to train and run models. It's not the chatbot itself, but the foundational tool that lets that chatbot run on a Mac.