Another inference engine? So TokenSpeed is trending on GitHub this week, billing itself as a "speed-of-light LLM inference engine." I clicked through expecting either a vLLM clone or another Rust rewrite of llama.cpp. I haven't run it in production yet — the repo is fresh and I want to be honest about that up front — but the framing alone is worth talking about, because it points at a shift I've been watching for a while. The last two years of inference work have been a sprint. PagedAttention landed in vLLM. Continuous batching went from research paper to default behavior. FlashAttention-2 and -3 showed up everywhere. We've gone from "can you even serve a 13B model" to "can you saturate your H100s." TokenSpeed is part of a wave that's stopped trying to invent new tricks and started trying to make the existing ones cheap, predictable, and operable. That's a less exciting story than "we made inference 10x faster," but it's the one that actually matters if you're shipping.…