The correct option is Large context window to accommodate the entire document in one pass.

A large context window determines how much input the model can process in a single request, which is crucial when loan agreements are 80 to 160 pages long. With a sufficiently large context window the model can read the entire contract without aggressive chunking, which helps preserve cross references and context so the summaries are more accurate and coherent. This directly addresses the advisor’s point that some models cannot handle the full agreement in one go while others can.

Tailored fine tuning for financial and legal vocabulary can improve domain specificity and tone, yet it does not expand how much text the model can accept at once, so it does not solve the core requirement to process the entire agreement in one pass.

Knowledge cutoff date of the model is less relevant because the task is to summarize content that is provided in the prompt, and summarization relies on the ability to attend to the supplied text rather than recalling external facts.

Temperature settings to adjust creativity versus determinism influence randomness and consistency of outputs, but they do not affect the amount of text the model can ingest, so they are not the limiting factor for this workload.

Full AWS Practitioner Certification Question