Amazon Bedrock Model Distillation: Boost function calling accuracy while reducing cost and latency

Amazon Bedrock Model Distillation is generally available, and it addresses the fundamental challenge many organizations face when deploying generative AI: how to maintain high performance while reducing costs and latency. This technique transfers knowledge from larger, more capable foundation models (FMs) that act as teachers to smaller, more efficient models (students), creating specialized models that excel at specific tasks. In this post, we highlight the advanced data augmentation techniques and performance improvements in Amazon Bedrock Model Distillation with Meta’s Llama model family.

Agent function calling represents a critical capability for modern AI applications, allowing models to interact with external tools, databases, and APIs by accurately determining when and how to invoke specific functions. Although larger models typically excel at identifying the appropriate functions to call and constructing proper parameters, they come with higher costs and latency. Amazon Bedrock Model Distillation now enables smaller models to achieve comparable function calling ...