A lab notebook for speeding up one decision model, H2O Lightning 4B, served through llama.cpp on an RTX 3060 Ti. Each request takes 2.13 to 2.45 times its roofline floor. The first measured change, a llama.cpp pull request, cut latency by 1.94% with bit-for-bit identical answers; the bigger gains in its list of 15 targets are labelled predictions.