How to Build a Local AI PC
Running AI models on your own PC gives you privacy, offline access and no per-use fees. Here's how to plan a local AI build.
Step 1: Decide which models you want to run
Your target model size drives everything else. Estimate memory needs using our VRAM guide.
Step 2: Choose the GPU
Pick the card with enough VRAM for your models within budget. For the widest software support, many people choose NVIDIA; check compatibility for AMD or Intel options. See Which GPU Do You Need for AI?
Step 3: Choose the CPU and motherboard
For one GPU, a modern mainstream desktop CPU is usually fine. For two or more GPUs, look at platforms with more PCIe lanes and correctly spaced slots.
Step 4: System memory
Aim for at least as much system RAM as your total VRAM, and more if you'll process large datasets or offload model layers to RAM.
Step 5: Storage
Models can be tens of gigabytes each. A fast NVMe SSD of 2TB or more is a sensible starting point.
Step 6: Power supply and cooling
Choose a quality PSU with headroom above your peak draw and the right GPU connectors. Prioritise airflow — AI workloads keep components at full load for long periods.
Step 7: Software
- Install up-to-date GPU drivers
- Choose a local AI runtime or framework suited to your models
- Download models from reputable sources and check their licences
- Keep the system updated and backed up