Improve TTFT for multi-turn agentic workloads with bi-directional KV transfer in vLLM
Multi-turn agentic workloads reprocess growing conversation context each turn, driving up latency. See how bi-directional KV cache transfer lets prefill and decode nodes reuse previously computed context across turns, cutting time to first token by up to 1.6x for Qwen3-32B and 3.3x for GLM-5-FP8 on Amazon EC2 P5en instances with EFA.
First seen by Oriel on .
Aliases
| Source | External ID | URL |
|---|---|---|
| AWS Machine Learning Blog | 02a1dd975b2fff9f32ce315def712a434de65bee | https://aws.amazon.com/blogs/machine-learning/improve-ttft-for-multi-turn-agentic-workloads-with-bi-directional-kv-transfer-in-vllm/ |