Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 179 discussion

Exam question from Amazon's AWS Certified AI Practitioner AIF-C01

Question #: 179
Topic #: 1

[All AWS Certified AI Practitioner AIF-C01 Questions]

A company has created a custom model by fine-tuning an existing large language model (LLM) from Amazon Bedrock. The company wants to deploy the model to production and use the model to handle a steady rate of requests each minute.

Which solution meets these requirements MOST cost-effectively?

A. Deploy the model by using an Amazon EC2 compute optimized instance.
B. Use the model with on-demand throughput on Amazon Bedrock.
C. Store the model in Amazon S3 and host the model by using AWS Lambda.
D. Purchase Provisioned Throughput for the model on Amazon Bedrock.

Show Suggested Answer

Suggested Answer: D 🗳️

by Zangi at July 16, 2025, 3:27 p.m.

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a6558c7

2 weeks, 3 days ago

Selected Answer: D

D. For custom (fine-tuned) models on Amazon Bedrock, deploying to production requires purchasing Provisioned Throughput; on-demand mode is not available for most custom models. Provisioned Throughput reserves dedicated model units and provides a guaranteed, predictable capacity for a steady (not bursty) workload, with discounted pricing over pay-as-you-go options. Option B (on-demand throughput) is best for unpredictable or low-volume workloads, as it charges per token and may be unavailable for custom fine-tuned models, which commonly require Provisioned Throughput for production deployment

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