No, you don't need an expensive dedicated GPU for local AI. Modern CPUs and Apple Silicon machines with enough memory (RAM) run these engines well. Memory is what matters most — more RAM runs bigger, smarter engines. A purpose-built box comes sized to run them well out of the crate.
The idea that you need a costly graphics card to run AI is one of the most common myths about local AI — and it stops a lot of small businesses before they start. The reality is simpler: for the kind of AI a business actually uses, a capable modern computer with enough memory runs these engines just fine, no separate GPU required.
Big graphics cards became famous for training AI models from scratch — a massive, one-time job done in data centers with thousands of cards. But running a finished model to answer your questions is a much lighter task. Ordinary modern computer memory and processors, or an Apple Silicon chip with its unified memory, handle it comfortably. The training happened once, far away; you just run the result.
The single most important thing for running local AI is memory (RAM). A model has to fit in memory to run, so the amount you have decides which engines you can use. This is why we describe our engines by the memory they want, not by any graphics card:
| Engine | Memory needed | What it's good for |
|---|---|---|
| Swift | 8GB or more | Fast, everyday text — drafting, summarizing, quick answers |
| Balanced | 16GB or more | Stronger reasoning on text for more demanding work |
| Maximum | 24GB or more (32GB recommended) | Deepest reasoning, and reads images, screenshots, and scans |
Notice there's no graphics card in that table. What moves you up the list is more memory — not a pricier GPU.
You need a reasonably modern machine with a capable processor and enough RAM for the engine you want. A recent Mac with Apple Silicon, or a modern PC with generous memory, does the job well. Very old or low-memory computers will struggle with the bigger engines — but the fix is more memory, not an expensive graphics card.
If you'd rather not think about specs at all, that's the point of the PrivateOfficeAI Box. It's sized to run its engines well out of the crate, with all three preloaded. The standard Box handles a team of up to about 15 people; the Box Pro doubles the memory to run the largest engines for busier offices. You plug it in and it just works — see the documentation for details.
On the Software edition, your own computer's memory decides which engines run. 16GB runs Swift well; 32GB or more unlocks the bigger engines. The larger engines download the first time you use them, then run locally on your machine's memory and processor — again, no dedicated GPU needed.
No. A modern CPU or an Apple Silicon machine with enough memory runs these engines well. Running a finished model is far lighter than training one, so an expensive dedicated GPU is not required.
It depends on the engine. The fast Swift engine wants 8GB or more, the stronger Balanced engine 16GB or more, and the Maximum engine 24GB or more, with 32GB recommended for the best experience.
Apple Silicon uses unified memory that the chip can draw on directly, so a capable Mac runs these engines well without a separate graphics card. Enough memory is what matters most.
Yes. The Box is sized to run its engines well out of the crate, with all three preloaded. The Box Pro doubles the memory for the largest engines and busier offices. Neither relies on a separate expensive graphics card.