Local AI on your Mac: Ollama, LM Studio, and what 7B models can really do — companion videos

Tech With Tim

A tight, no-nonsense Ollama walkthrough — install, pull a model, chat, then poke at the local HTTP API from Python and create a custom model with a Modelfile. Covers exactly the workflow the article describes for daily use on a Mac, including how to think about model size vs. your machine's RAM.

What you should get from this: Install a local model runner, pull a small model and understand the privacy/performance tradeoff before using it for real work.

Watch or know first: Comfort with a terminal and basic awareness that local models vary heavily by size, quantization and hardware.

Kevin Stratvert

Same workflow as Ollama but in a GUI: download LM Studio, pull a Llama or Gemma model, chat, drop a PDF in and ask questions about it. Good for readers who'd rather not live in the terminal — also useful for getting a feel for how a 1B–3B model actually performs against a heavier one.

What you should get from this: Try local AI through a GUI and compare small-model behavior with hosted frontier models.

Watch or know first: Know why you want local execution: privacy, offline use, cost control or experimentation.