A technical exploration of AI performance on local hardware. No clouds, no APIs—just raw compute and honest benchmarks.
Every test uses the same prompt and the same hardware rig to ensure an apples-to-apples comparison.
Only one variable is changed per test, isolating the impact of the specific modification being measured.
The model is completely reloaded before every single run to prevent cache contamination and state leak.
Every prompt used and every result file generated is published openly for community verification.
PC Magik Lab is a dedicated series focused on the practical reality of running Large Language Models (LLMs) on consumer-grade hardware. By avoiding cloud abstractions and API limits, the lab explores how different quantizations, backends, and configurations affect actual performance on real, local GPUs.