Large Language Models (LLMs) face a trade-off between inference quality and computational cost.Existing serving strategies lack dynamic adaptation to user requests and system performance changes.SpecRouter introduces a framework for adaptive routing in LLM inference through multi-level speculative decoding.It includes mechanisms for adaptive model chain scheduling, multi-level collaborative verification, and synchronized state management.