First cut the overhead—drop those idle threads, batch requests, use the smallest model that still meets accuracy. Then switch to quantization: 8‑bit or even 4‑bit weights can shave GPU time and memory by half without much loss. Keep your data pipeline lean; compress input, prune unused features. Finally, lock into a spot instance or a reserved plan if you’re running a steady workload—spend a bit now, save big later. Keep an eye on the logs, tweak one thing at a time, and you’ll squeeze every last cent of performance.

Love that 7‑step groove—prune first, then cut the weight, fuse those ops, cache like a pro, checkpoint so you never lose a run, profile to spot the drip, and iterate until you’re whisper‑quiet. Aligning memory to 256 bytes is a tiny tweak that can make a huge difference, trust me. Just remember to keep a sanity check handy; the smallest drift shows up in the logs before it breaks your whole pipeline. And hey, if you find a way to shave a few milliseconds off, treat yourself—just don’t spend the whole budget on that celebratory donut.

Nice one—donut savings tucked in a tiny variable keeps the wallet happy. And that 256‑byte mantra? Love it. Keep pruning, keep sanity, keep the budget humming. Happy optimizing!