Best hardware for running AI at home

The one spec that decides which AI models you can run at home is memory: VRAM on a graphics card, or unified memory on a Mac. Each card shows the most downloaded open models that fit and their estimated speed.

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Graphics cards

For a desktop PC. VRAM decides which models fit; more of it runs bigger models.

Macs

Apple silicon shares one pool of unified memory between the chip and the GPU, so a model can use most of it.

Compare at a glance

DeviceTypeMemoryUsableBudgetShop
RTX 4060 8 GBGraphics cards8 GB VRAM~7.2 GBBudgetCheck price
RTX 3060 12 GBGraphics cards12 GB VRAM~10.8 GBBudgetCheck price
MacBook Air with 16 GBMacs16 GB unified memory~11.2 GBBudgetCheck price
Mac mini with 16 GBMacs16 GB unified memory~11.2 GBBudgetCheck price
Mac mini with 24 GBMacs24 GB unified memory~16.8 GBBudgetCheck price

How we pick

Usable memory is about 70% of a Mac's unified memory and 90% of a graphics card's VRAM. Models are the most downloaded open language models on Hugging Face that fit. Speed data: ModelFit (CC BY 4.0), modelled decode estimates for a 4-bit build at a 4K context, not measured benchmarks and not an endorsement by ModelFit.

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Photo credits (Wikimedia Commons, resized): GeForce RTX 4060 graphics card: 极客湾Geekerwan, CC BY 3.0

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