How to run AI models on your own computer, for free

What "running locally" means

Running a model locally means the model file lives on your own computer and does the work on your own hardware. Nothing you type is sent to a server. That is the whole appeal: complete privacy, no usage limits, no monthly fee, and it keeps working with the internet switched off.

This is possible because of open-weight models — models whose trained parameters are published for anyone to download and run. You will not get the very largest frontier models this way, but the open-weight options have become genuinely useful for everyday drafting, coding help, and question-answering.

What you actually need

The main constraint is memory. Models are sized by their number of parameters — often written like 7B or 13B, meaning billions — and a rough rule is that a model needs a few gigabytes of RAM for every billion parameters, depending on how heavily it has been compressed.

In practice:

• 8 GB of RAM: small models (up to roughly 7–8B) run, slowly but usably.
• 16 GB: comfortable for small-to-mid models; the sweet spot for most people.
• 32 GB or a recent GPU: mid-to-large models at a genuinely pleasant speed.
• A dedicated GPU helps enormously but is not required — modern Apple Silicon and recent laptops handle small models fine on the CPU.

The easiest way to start

You do not need to touch a command line or understand the internals. A handful of free tools have turned local models into roughly a two-step process: install the app, pick a model to download. From there it behaves much like any chat window, except everything happens on your machine.

Start with the smallest model the app recommends for your hardware. Get it working, see how the speed feels, and only then reach for something larger. A small model that responds quickly beats a large one that makes your laptop's fans scream for every reply.

The honest trade-offs

Local models are not a free copy of the big cloud assistants. The gap is real and worth knowing before you invest an evening:

• Quality: the best cloud models are still noticeably sharper on hard tasks.
• Speed: depends entirely on your hardware; it can be slower than you expect.
• Setup: easier than ever, but still a step beyond opening a website.
• In exchange: total privacy, no limits, no cost, and it works offline.

Who it is really for

Running AI locally makes the most sense if privacy is non-negotiable — sensitive documents, confidential code, work you simply cannot send to a third party — or if you want to tinker and learn how these models actually behave. For casual, occasional use, a good free cloud tier is simpler and often produces better results.

The good news is that it is not either-or. Plenty of people keep a cloud assistant for heavy lifting and a local model for anything private. Trying the local route costs nothing but an evening, and you will understand the whole field much better for having done it.