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Best AI coding corner

A budget build for local AI code completion with a 14B model, plus dev environments.

The request
  • Code assistant (local LLM)
  • Dev environments
  • Docker
Edit request
Overview · Unified-memory build€2,012

Requirements vs this build

need · used
CPU threads1547%OK
RAM64 GB100%Full
Storage3 TB99%Full
GPUAI-capable

Power

Usage
24/7
Idle
13 W
Typical
20 W
Peak
38 W
Energy / year
≈ €44
Over 3 years
≈ €133

Score

Overall72
Performance76
Efficiency93
Value73

Why this variant

Choose it if

Balances your priorities with a 2012€ price tag and a 13W idle draw.

It sacrifices
  • Not specialized: it does not push any single dimension (value, silence, expansion) to the extreme.
How the parts were chosen
  • GMKtec EVO-X2 — AMD Ryzen AI Max+ 395 (64GB): 32 threads, 64GB RAM, 12W idle — a complete, efficient prebuilt for this workload.
  • Turnkey: no assembly, smaller footprint, lower energy than a custom build.
  • Unified memory: the integrated GPU can use up to ~48 GB of the 64 GB as graphics memory, so the model fits without a dedicated card. Decode speed follows the 256 GB/s memory bus — several times slower than a high-end card, but a fraction of its price and power.
Why not the others
  • Unified-memory build — the model in shared RAM, no card beats "Smart build — best all-round" on performance -14, value +6, efficiency +37, expandability -75, longevity +16 — that is why it is recommended for your priorities.

Before you buy

3 critical
Critical
Check the balance
This build may struggle with the workload.
Critical
No storage redundancy
1 drive(s) with no mirror or parity for the data you plan to store.
Critical
RAM is nearly exhausted
The workload needs 100% of available RAM — swapping will hurt.
Keep going

Beyond this build