Which mini PC actually runs your model?
The buyer's authority on mini PCs & unified-memory boxes for local AI — DGX Spark, Strix Halo, Mac Studio. Real specs, real prices, and the one number that decides token speed: memory bandwidth.
NVIDIA DGX Spark (GB10 Grace Blackwell)
$4,699+
GMKtec EVO-X2 (Ryzen AI Max+ 395, 128GB)
$3,399 – $3,499
Apple Mac Studio M3 Ultra
$3,999 (96GB)
Why run AI locally
Own Your AI Compute
Cloud APIs charge per token and see every prompt. Local hardware gives you privacy, speed, and unlimited usage — on your terms.
Full Data Privacy
Your prompts, code, and data never leave your machine. No API logs, no third-party access, no compliance headaches.
Zero Latency, No Rate Limits
Run inference at hardware speed — no API queues, no throttling, no waiting. Your models respond as fast as your box's memory bandwidth allows.
One-Time Cost, Unlimited Use
API bills compound monthly. Local hardware pays for itself. After the upfront investment, every inference is essentially free.
The shift is happening
AI Is Moving to the Edge
A new class of hardware is shipping built around unified memory. AMD's Ryzen AI Max+ 395 and NVIDIA's GB10 pack 128GB into a box you can hold; Apple's M-series runs 70B models with zero fan noise. Models that needed a multi-GPU rig now fit on a desk.
The hardware is ready. Open models like Llama, Qwen, and DeepSeek are closing the gap with cloud APIs, and Ollama and llama.cpp make local deployment trivial. The question isn't whether to run AI locally — it's which box to buy.
That's where we come in. We test, compare, and rank the best mini PCs and unified-memory boxes for every budget — from a $230 always-on agent host to a DGX Spark running 200B-parameter models, judged on the spec that decides token speed: memory bandwidth.
128GB
Unified memory in a box you can hold
70B
Models run locally on a mini PC
$0
Per-token cost with local inference
256GB/s
Memory bandwidth — the spec that sets token speed
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Find Your Setup
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