- A
Use a higher temperature setting to generate fewer tokens
Why wrong: Temperature does not affect token count; it affects randomness.
- B
Increase the max tokens to allow longer responses
Why wrong: Longer responses cost more because Bedrock charges per token processed and generated.
- C
Use provisioned throughput for high-volume, predictable workloads
Provisioned throughput offers a discounted hourly rate compared to on-demand per-request pricing.
- D
Cache frequently used responses in Amazon ElastiCache
Why wrong: Bedrock does not provide built-in caching, and caching is not a direct cost reduction strategy for the Bedrock service itself.
- E
Select a smaller foundation model variant
Smaller models have lower computational requirements, reducing cost per inference.
AIF-C01 Fundamentals of Generative AI Practice Question
This AIF-C01 practice question tests your understanding of fundamentals of generative ai. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO strategies can help reduce inference costs when using Amazon Bedrock? (Select TWO.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use provisioned throughput for high-volume, predictable workloads
Option C is correct because provisioned throughput allows you to reserve capacity for a specific foundation model, ensuring predictable performance and cost savings for high-volume workloads compared to on-demand pricing. By committing to a certain throughput level, you avoid per-token charges that can accumulate with variable usage, reducing overall inference costs.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a higher temperature setting to generate fewer tokens
Why it's wrong here
Temperature does not affect token count; it affects randomness.
- ✗
Increase the max tokens to allow longer responses
Why it's wrong here
Longer responses cost more because Bedrock charges per token processed and generated.
- ✓
Use provisioned throughput for high-volume, predictable workloads
Why this is correct
Provisioned throughput offers a discounted hourly rate compared to on-demand per-request pricing.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Cache frequently used responses in Amazon ElastiCache
Why it's wrong here
Bedrock does not provide built-in caching, and caching is not a direct cost reduction strategy for the Bedrock service itself.
- ✓
Select a smaller foundation model variant
Why this is correct
Smaller models have lower computational requirements, reducing cost per inference.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates may mistakenly believe that caching responses in Amazon ElastiCache reduces inference costs, but this is not a built-in feature of Bedrock and would require custom implementation, still incurring costs for cache misses. Similarly, adjusting temperature or max tokens does not directly reduce per-token costs. The correct strategies are using provisioned throughput for high-volume predictable workloads and selecting a smaller foundation model variant.
Detailed technical explanation
How to think about this question
Provisioned throughput in Amazon Bedrock allocates dedicated model units (e.g., 1 model unit = 1,000 tokens per minute) for a specific foundation model, guaranteeing latency and throughput. This is cost-effective for steady-state workloads because you pay a fixed hourly rate per model unit, avoiding the higher per-token cost of on-demand inference. In contrast, on-demand pricing charges per input and output token, which can become expensive for high-volume or predictable usage patterns.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AIF-C01 question test?
Fundamentals of Generative AI — This question tests Fundamentals of Generative AI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use provisioned throughput for high-volume, predictable workloads — Option C is correct because provisioned throughput allows you to reserve capacity for a specific foundation model, ensuring predictable performance and cost savings for high-volume workloads compared to on-demand pricing. By committing to a certain throughput level, you avoid per-token charges that can accumulate with variable usage, reducing overall inference costs.
What should I do if I get this AIF-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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