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AIF-C01 Practice Question 27: Foundation Model Selection Criteria

AWS Certified AI Practitioner (AIF-C01) · Test 3 · question 7 of 10

Applications of Foundation Modelseasy

A team must pick one Amazon Bedrock foundation model for a mobile help assistant. The input is always short plain text, the answers must come back fast enough to feel instant, the app will handle several million requests a day, and images and video are explicitly out of scope. Which selection is best justified by those constraints?

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Answer:

  • A. A small text-only model chosen for its low latency and low cost per token

Model selection is driven by the requirements in front of you: modality (what the model must accept and produce), context window (how much text must fit in one request), latency, and cost. Here the modality is text only, the prompts are short so a huge context window buys nothing, and the two binding constraints are response speed and per-request cost at millions of calls a day. A small text-only model (Amazon Nova Micro, for example, is described as the text-only option delivering the lowest latency at very low cost) matches all four (option A).

- B is wrong because the largest multimodal model is typically the slowest and most expensive per token. Benchmark leadership on tasks this app never performs is not worth paying for on every one of millions of daily requests. - C is wrong because context window matters only when prompts are long: big documents, long chat histories, retrieved passages. With short prompts the extra capacity sits unused while the larger model still costs more and responds more slowly. - D is wrong because it optimizes for a requirement that the stem rules out. Since Bedrock lets you swap models through the same API, paying now for a modality you do not use is premature.

Reference: What is Amazon Nova?

Practice Test 3 ›

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