I've been running llama.cpp on a plain CPU-only box for local work for over a year now, and the thing that keeps surprising me is how often an upgrade is just free performance. Same model, same hardware, noticeably faster prompt processing — jacquesm's 4:22 to 3:59 matches what I've seen on my own machine. The other underrated part is that the codebase is small enough to actually read. When something is slow I can usually find the hot loop myself instead of treating the inference engine as a black box, which is not something I can say about most of the GPU stacks I've used.