The Best Mini-PC for Local AI in 2026 (Unified Memory, Honestly)

The short version

Unified memory trades bandwidth for capacity. One big pool of RAM shared by CPU and GPU lets these boxes *hold* models a consumer GPU can't — but it's slower per token than a fat-VRAM GPU on models…

The short version

The value pick: AMD Strix Halo (Ryzen AI Max+ 395). ~128GB unified memory (much of it usable for AI) in a ~$1,999 mini-PC that runs 30B–120B models locally.

The short version

The premium/scale pick: Apple Mac Studio. Scales to far more unified memory than anything else (up to 512GB on the top config), with excellent efficiency — but you pay for it.

The short version

The CUDA pick with a caveat: NVIDIA DGX Spark. Native CUDA ecosystem, but it costs roughly 2.4× a Strix Halo and barely out-runs it on tokens — buy it for the software stack, not the value.

The short version

When NOT to: if your models fit in a GPU's VRAM and you want maximum speed, a discrete GPU still wins. Unified memory is about *fitting* big models, not out-running GPUs.

For running big local models in a small, quiet, affordable box, a Ryzen AI Max+ 395 ("Strix Halo") mini-PC is the pick — it holds models a $2,000 graphics card can't, for around $1,999. Step up to a…