Q10 — AWS AIF-C01 Ch.2

Question 10 of 100 | ← Chapter 2

A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to understand how much information a prompt can contain. On which factor will the company’s decision be based?

• A. Temperature
• B. Context window ✓
• C. Batch size
• D. Model size

Correct Answer: B. Context window

Explanation

When using an LLM on Amazon Bedrock for sentiment analysis, the amount of information a prompt can contain is constrained by the model’s context window—the maximum number of tokens the model can process in a single input-output sequence. This includes both the prompt and the generated response. A larger context window allows more detailed instructions, longer input texts, or richer contextual cues, directly impacting sentiment analysis accuracy—especially for nuanced or document-level analysis. Temperature controls randomness in output, batch size relates to parallel inference throughput, and model size affects capacity but not prompt length limits. Therefore, the context window is the key factor governing prompt information capacity.