Local AI on a €2,960 box
A structured, pre-registered benchmark of what one 128 GB mini-PC can actually do - chat, coding, transcription, speech, images, documents - measured, sourced, and clearly framed.
The actual box - Alastair McDermott with the GMKtec EVO-X2 this runs on. Watch the 2-minute intro on LinkedIn →
Bottom line: capable AI on your own desk, with no data leaving the building - fast enough for everyday work, hundreds of times cheaper per word than a top cloud AI, and clear about where it doesn't match frontier models. Everything here is the measured evidence; every number traces to a raw file. GMKtec EVO-X2 · Ryzen AI Max+ 395 · 128GB · llama.cpp/Vulkan + ROCm 7.2.4 · benchmarked 2026-07-03→06.
See it in action
🎬 90-second explainer video
A narrated chart walkthrough - script by the local model, voiced by Piper, assembled with ffmpeg, all on the box.
🎙️ Two-minute audio overview
A two-voice conversation, voiced on the box by Chatterbox TTS. Good, but not cloud-studio grade - see the audio quality verdict. Hear the earlier Piper version.
Both were generated by the box itself - how, and who did what.

What would it save you?
A rough guide, and only if your work fits what the box does well (see the limits). Assumes the box at €2,960 plus about €8 a month electricity, over three years. It does not price in data-sovereignty value, which for many buyers is the whole point.
Reports
Findings & evidence
Capabilities & visuals
See if it fits your practice
A 25-minute call, no obligation - we'll talk through whether an on-prem box like this makes sense for the work you do.
Raw data & sources
Self-contained - no separate data download needed. data/raw/ holds every raw llama-bench table and serve_bench JSON behind the numbers; data/report-sources/ holds the editable Markdown of every report; data/eval-pilot/ and data/eval-suites/ hold the eval outputs and definitions. Full annotated index: data index.