A YouTube series

Running AI models on real, local GPUs — no clouds, no hype.

Local models, real GPUs.

PC Magik Lab is a hands-on series about what modern language models can actually do on hardware sitting in your own room — measured with a strict, repeatable method.

One variable changed per test Same prompt, same rig Every result published
The method

How the series measures things

Comparisons are only meaningful when everything else is held constant. That is the whole point of the series — a controlled way to compare local models on real hardware.

01

Same prompt

Every test uses the same prompt, so the model — not the question — is what is being compared.

02

Same rig

One machine, one GPU. The hardware never changes between tests — only the model does.

03

One variable per test

Exactly one variable is changed at a time, so any difference can be attributed to it.

04

Model reloaded before every run

The model is reloaded before every run, so no run inherits state from the previous one.

05

Everything published

Every prompt and every result file is published, so anyone can inspect and reproduce the tests.

The rig

One machine. No exceptions.

Every model in the series runs on the same local setup, so results are always comparable with each other.

NVIDIA RTX 3090

24 GB of VRAM, running locally

The only GPU in the series is an NVIDIA RTX 3090 with 24 GB. It sits in one dedicated rig, and every model being evaluated runs on it — locally, on real silicon.

gpu: nvidia rtx 3090 · vram: 24 gb

LM Studio

Model server

LM Studio acts as the model server for the rig. It loads each model and serves the prompts, with the model reloaded before every run to keep the conditions identical.

server: lm studio (local)
About

Who is behind the lab

PC Magik Lab is a one-person operation: real hardware, a strict method, and everything published for you to check.

PC Magik — Mateusz Piekut

PC Magik (Mateusz Piekut) is a computer service and homelab operator from Poland. The series comes straight out of that everyday work: real machines, real GPUs, and local models that have to earn their place in the rack. No cloud, no marketing numbers — just what the hardware in the room actually does.