AWS Launches Prefix-Aware Routing in SageMaker – Reducing LLM Latency by 77%
AWS has launched prefix-aware routing for Amazon SageMaker Inference. This new feature reduces language model response times by reusing the KV cache for similar requests.
What happened?
Amazon Web Services (AWS) has introduced prefix-aware routing for its Amazon SageMaker Inference service. The service routes incoming requests with the same prompt prefix to the same compute instance. This allows the model’s key-value (KV) cache to be reused, eliminating the need to reprocess recurring context and instructions.
Key facts
| Minskning P50 TTFT | Upp till 77 % |
|---|---|
| KV-cache träffsäkerhet | Ökning från ca 25 % till över 80 % |
| Testad modell | Llama 3.1 70B |
| Plattform | Amazon SageMaker Inference |
Why it matters
Performance tests on Llama 3.1 70B demonstrate that prefix-aware routing reduces the median time to first token (P50) by up to 77 percent. Simultaneously, the KV cache hit rate increased from approximately 25 percent to over 80 percent. This results in lower latency and more efficient resource utilisation when deploying large language models.
Who is affected?
This development is relevant to AI developers, data engineers, and enterprises deploying large language models (LLMs) in production. Organizations managing applications with long system prompts, document analysis, or repetitive agent instructions will particularly benefit from this optimisation.
Impact on the EU
The feature is part of Amazon SageMaker Inference and is available in all AWS regions where the service is offered, including the AWS Stockholm region (eu-north-1).
What else you should know
The service requires no additional fees beyond standard pricing for SageMaker instances; however, it requires the application to use suitable backend engines such as vLLM or TensorRT-LLM for optimal KV cache management.
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