Reduce LLM latency with prefix-aware routing on Amazon SageMaker Inference
77% faster first-token latency. Amazon SageMaker's new prefix-aware routing keeps KV cache warm by routing similar requests to the same instance.
Why it matters
A practical inference optimization that practitioners deploying LLMs on AWS can adopt immediately to reduce latency in production — especially valuable for multi-user or high-volume inference workloads where cache efficiency directly impacts user experience.
The key facts
9 to knowAmazon SageMaker Inference feature: prefix-aware routing
P50 time-to-first-token reduced up to 77% on Llama 3.1 70B
KV cache hit rates improved from ~25% to over 80%
Routes requests with same prompt prefix to same instance for cache reuse
Prefix-aware routing routes requests with shared prompt prefixes to same instance
P50 time-to-first-token reduced up to 77% on Llama 3.1 70B benchmark
KV cache hit rates improved from ~25% to >80%
Feature now available on Amazon SageMaker Inference
Targets inference latency and cost efficiency for production deployments
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: Amazon SageMaker Inference now offers prefix-aware routing, a routing strategy that sends requests sharing the same prompt prefix to the same instance so the KV cache stays warm. In benchmarks on Llama 3.1 70B, it reduced P50 time-to-first-token by up to 77% and raised KV cache hit rates from about…