23 October 2026
vLLM's new KV transfer method roughly triples how fast answers begin
First reported
Deep Learning Weekly ran this on .
- vLLM, an open-source system for running AI models quickly, changed how it moves intermediate model data between machines.
- The change, called push-based KV transfer, sends that data ahead of time instead of waiting for it, which cuts the delay before a reply starts.
- Reported time to first token drops roughly 3x, and the time to produce each later word improves by up to 30%.
How it was covered
Deep Learning WeeklyEditorial team
Push-based KV transfer design, time-to-first-token and time-per-output-token improvements