TurboQuant on a MacBook: building a one-command local stack with Ollama, MLX, and an automatic routing proxy

Everyone is talking about TurboQuant , and a lot of people summarize it with a line like this: run bigger models on smaller hardware That line is catchy, but it is also where the confusion starts. And yes, was also my initial assumption, like " nice! now I can run that 70B model on my 24GB unified-memory MacBook " This article has two goals: Explain what TurboQuant actually is, and what it is not Show a practical local stack for Apple Silicon that uses TurboQuant where it helps without making the rest of your setup miserable The stack here is intentionally humble. It is meant for the kind of machine many of us actually have: a MacBook with Apple Silicon limited unified memory a normal person budget perhaps an irrational amount of confidence Part 1: what TurboQuant is, and what it is not TurboQuant does not primarily solve model-weight size. That is the first thing to get clear. When people say " it lets you run bigger models on smaller hardware " what they usually mean is more indirect