Optimizing TTFT for multi-turn agentic workloads with bidirectional KV transfer in vLLM
In brief
- Bidirectional KV transfer reduces context recalculation in multi-turn conversations.
- TTFT improved by up to 1.6x for Qwen3-32B and 3.3x for GLM-5-FP8 on AWS EC2 P5en.
- Tested with EFA for enhanced performance on cloud instances.
Multi-turn agentic workloads reprocess growing conversation context each turn, increasing latency. A new bidirectional KV cache transfer method in vLLM reuses prior computations, cutting time to first token by up to 1.6x for Qwen3-32B and 3.3x for GLM-5-FP8 on AWS EC2 P5en instances.
What it changes for you
- CybersecurityCybersecurity solutions leveraging multi-turn AI agents see reduced latency, enhancing the responsiveness of detection and response systems.
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