TL;DR: to select a text summarization API model in Node.js, route moderation reports through a small, typed decision layer that can choose a fast or careful summarizer, then send uncertain cases to human review. The useful optimization is not a universal model winner. It is knowing when a shorter wait is worth a lower-confidence summary.

A moderation summary is a review aid, not the moderation decision. That distinction changes the design. The system should preserve the original report, label the summary as machine-generated, and make it cheap to reject or regenerate a poor result.

For a solo builder, I start with a fixed evaluation set and a narrow output contract. I do not begin by wiring one model directly into a request handler. That shortcut hides the two failures that matter here: a plausible summary can omit the detail a reviewer needs, and a slow call can make the review queue feel broken.…