Knowledge Base · Local AI

Can I run local AI without a GPU?

Updated October 2026. No affiliate links on this page. What runs well on a plain processor, what doesn't, and when a graphics card is worth buying.

Yes. Local AI runs fine on just a processor and system RAM, with no graphics card at all. Ollama and LM Studio both fall back to the processor automatically, and small models (1B to 8B) are perfectly usable that way.

The cost is speed. A processor writes text several times slower than a graphics card, so big models get too slow to use. For casual use and small models, you don't need a graphics card.

Words you'll see in this guide

CPU: the processor, the main chip that runs everything. It can run AI models too, just slower than a graphics card.
GPU: the graphics card. It does the heavy math for AI models much faster than a processor.
RAM: your computer's main working memory. More RAM lets it run more apps at once. AI models can run from it too, just slower than from VRAM.
Parameters (1B, 8B, 70B): a rough measure of a model's size. "8B" means 8 billion. Bigger models are usually smarter and need more memory.
Integrated graphics: the basic graphics built into many processors, as opposed to a separate graphics card. It shares system RAM.

See the full glossary

How it works without a graphics card

A model has to sit in memory, and something has to do the math. A graphics card is the fastest at that math, but a processor can do it too. It reads the model from your regular system RAM and writes out the answer.

Two separate questions decide how it goes:

Does it fit? That depends on how much RAM you have. See how much RAM you need.
Is it fast? That depends on whether a graphics card is doing the work.

Without a graphics card, the model still fits and still runs. It's just slower.

What runs well on a processor alone

Model size	Processor-only experience
1B to 3B	Quick. Fine for chat, summaries, and small tasks.
7B to 8B	Usable. A few words per second, fine for casual use.
13B to 14B	Slow. It works, but you'll wait. OK once in a while.
34B and up	Painful. It runs if it fits in RAM, but it's too slow for real work.
70B	Not practical on a processor alone.

Speed on a processor depends mostly on memory speed and core count. A modern desktop with fast RAM does noticeably better than an old laptop.

Start here: if you mainly want to try local AI, chat casually, or use small models, a processor is enough. Start with what you have and spend nothing. Add a graphics card when slowness starts getting in your way, or when you want bigger models regularly.

Macs are the exception

"Without a GPU" usually means a Windows or Linux PC leaning on its processor. Apple Silicon Macs work differently. They don't have a separate graphics card, but their built-in graphics share fast unified memory, so they run local models much faster than a processor-only PC. If you have an M-series Mac, you already have good AI hardware.

What about integrated graphics?

The built-in graphics on most Intel and AMD laptops and mini PCs only help a little. They share the same slow system RAM and have limited software support, so in practice you end up close to processor speed. The real jump is a separate graphics card with its own fast VRAM.

When a graphics card is worth it

Get one when:

The slow speed is costing you time.
You want to run 13B models and up comfortably.
You want to generate images, which leans on a graphics card far more than text does.

A separate card with plenty of VRAM is a big step up. See the best GPU for local AI under $500 for value picks, and check what any machine can run, with a speed estimate, in the Server Calculator.

New to all this? Start with can my laptop run local AI.
No spare computer? You can run your own LLM in the cloud on a small rented server or a rented graphics card.

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