Question

A media analytics company needs to generate summaries for a backlog of 4 million archived news articles using Amazon Bedrock. There is no user-facing latency requirement — the job can run overnight or over several days. The team wants to minimize cost per token while processing this large, static dataset. Which approach best meets these requirements?

Accepted Answer

Use the Bedrock batch inference (CreateModelInvocationJob) feature, providing input records in Amazon S3 and retrieving results from S3 after the job completes.

Answer

Invoke the InvokeModel API in a parallelized loop with hundreds of concurrent threads to process articles as fast as possible.

Answer

Purchase Provisioned Throughput with a long-term commitment and stream each article through the model in real time.

Answer

Use the InvokeModelWithResponseStream API so results return incrementally, reducing the total tokens billed.