Question

A retail company is building a customer-facing chatbot on Amazon Bedrock that handles thousands of concurrent short conversational turns during peak shopping hours. Product leadership requires sub-second response latency and the lowest possible per-request cost, while accepting that answers do not require the deepest reasoning capability. The team has benchmarked several Anthropic Claude models available in Bedrock. Which approach best meets these requirements?

Accepted Answer

Select a smaller, faster Claude model (such as a Haiku-class model) after benchmarking that it meets quality thresholds for the conversational use case.

Answer

Route all traffic to the largest, most capable Claude model to guarantee answer quality regardless of latency or cost.

Answer

Use Provisioned Throughput with the most capable model and cap the max token output to reduce latency.

Answer

Fine-tune the largest Claude model on chat transcripts to make it respond faster at inference time.