Improve TTFT for multi-turn agentic workloads with bi-directional KV transfer in vLLM
AWS Machine Learning Blog ·
Summary: 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.
Read the full story on AWS Machine Learning BlogExplore more: Today in AI · Research papers · AI tools · Learn AI
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