TAO Joint Scheduling for Efficient LLM Agentic Serving
October 26, 2026
TAO is a scheduling framework that optimizes agentic serving by accounting for tool-return readiness and node-specific cache credits. It reduces latency by up to 26.8% and improves mean time to first token across various model-workload configurations.
HOW THIS AFFECTS YOU
●
builderYou can reduce inference costs and latency when deploying agents that use external tools.
●
founderThis improves the unit economics of agent-based service architectures.