Knowledge Base · Local AI

Is a Mac good for running local AI?

By Tiny · how I pick

Updated October 2026. No affiliate links on this page. The short version: yes, and one design choice explains why.

Yes. Apple Silicon Macs are one of the best ways to run local AI, because of unified memory. The processor and graphics share one fast pool of memory, so a Mac's RAM works like a graphics card's VRAM.

A 32 GB Mac runs models that would need an expensive graphics card on a PC. A 64 GB Mac can run 70B models. Both stay silent and use very little power.

Words you'll see in this guide
  • Unified memory: Apple's design where the processor and graphics share one fast pool of memory, so a Mac's RAM works like VRAM.
  • VRAM: the memory on your graphics card. AI models load into it, so more VRAM means you can run bigger models.
  • Tokens per second: how fast a model writes. A token is roughly three-quarters of a word.
  • Parameters (13B, 70B): a rough measure of a model's size. "8B" means 8 billion. Bigger models are usually smarter and need more memory.

See the full glossary

Why unified memory makes the difference

On a typical Windows or Linux PC, a model has to fit in the graphics card's VRAM to run fast. Most consumer cards top out at 24 GB, and even the flagship RTX 5090 has 32 GB.

Apple Silicon has no separate VRAM. The graphics can use almost all of the system memory, so a 64 GB Mac can load a model of about 48 GB that no single consumer graphics card could hold. When you buy a Mac for local AI, you're really buying a large pool of fast memory the graphics can use.

Mac vs Nvidia PC

Apple Silicon MacNvidia PC
Big modelsExcellent, thanks to the large memory poolLimited by the card's VRAM (24 to 32 GB per card)
Speed, if the model fitsGoodFaster. Top cards lead on tokens per second
Image generationWorks, but slowerMuch faster
Noise and powerSilent, very low powerLoud and power-hungry while working
Upgrading laterNot possible. Memory is fixed when you buy itYes. Add or swap graphics cards
Which to choose: for chatting with large text models quietly on one machine, a Mac with plenty of memory is hard to beat. For top speed, image generation, or a machine you'll upgrade over time, a PC with a big Nvidia card wins.
Buy the memory up front. You can't add RAM to an Apple Silicon Mac later, because it's built into the chip. If local AI matters to you, buy enough for the models you'll want: 32 GB for 13B models, 64 GB for 70B.

Where to go next

Quick answers

Is a Mac good for running local AI?

Yes. Apple Silicon Macs share memory between the processor and graphics, so the Mac's memory works like VRAM. A 32 GB Mac runs models that would need a costly graphics card on a PC, and a 64 GB Mac can run 70B models, quietly and at low power.

Is a Mac or NVIDIA PC better for local AI?

A Mac wins on memory for the money and simplicity, holding very large models while staying quiet. An NVIDIA PC wins on raw speed for models that fit in its VRAM, and on image generation.

How much memory should a Mac have for local AI?

16 GB runs 7B to 8B models, 32 GB runs 13B to 14B comfortably, and 64 GB or more is needed for 70B models. You can't upgrade a Mac's memory later, so buy as much as you can afford upfront.

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