Crucial Exams

AWS Certified AI Practitioner AIF-C01 Practice Question

A startup needs to adapt a large language model to its highly specialized vocabulary. They are comparing full fine-tuning, parameter-efficient fine-tuning (PEFT), and a retrieval-augmented generation (RAG) approach. Which statement BEST describes the cost profile of full fine-tuning?

  • Its storage cost is negligible because only lightweight weight deltas are saved.

  • It usually has the highest overall cost because every model parameter must be updated and a full new set of weights must be stored.

  • Its cost is comparable to PEFT because both methods adjust only a small subset of parameters.

  • It is cheaper than RAG because it removes the need for an external vector database.

AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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