Compare foundation-model specifications.
Do not confuse learned scale with the length of one request.
Choose two correct statements.
Parameters are learned internal weights, while a context limit constrains tokens processed in one inference request.
Detailed explanation
They represent learned values used during computation.
It is separate from the number of learned parameters.
Training data volume and per-request context are different.
Scale does not automatically optimize price or speed.
Check official documentation
Compare the following points with the official documentation.
Amazon Bedrock公式モデル仕様とAIF-C01 Domain 2.1・2.2を確認する。
Official references
What to confirm
モデル規模と入力長制約の違いを説明できる。
Key points
- Parameters
- Context
- Specification
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Compare the definition with the AIF-C01 objective and the service documentation before applying it.
- Keep the concept separate from a particular answer choice or implementation step.
Foundation review
Model parameter
A learned internal weight used by a model to transform inputs into outputs.
Context limit
The maximum input, history, retrieved material, and output tokens handled in one request.