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.

As an Amazon Associate we earn from qualifying purchases. Prices change often, so we link to Amazon instead of listing them.

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.

Powerful laptops

Gaming laptops with NVIDIA GPUs and MacBook Pros that run local models on the go.

Compare at a glance

DeviceTypeMemoryUsableBudgetShop
RTX 4070 12 GBGraphics cards12 GB VRAM~10.8 GBMidCheck price
RTX 3090 24 GBGraphics cards24 GB VRAM~21.6 GBMidCheck price
MacBook Air with 24 GBMacs24 GB unified memory~16.8 GBMidCheck price
MacBook Air with 32 GBMacs32 GB unified memory~22.4 GBMidCheck price
RTX 4070 Laptop 8 GBPowerful laptops8 GB VRAM~7.2 GBMidCheck price
MacBook Pro M4 Pro with 24 GBPowerful laptops24 GB unified memory~16.8 GBMidCheck 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.

As an Amazon Associate we earn from qualifying purchases.

Already have hardware? Find a model for it →