OpenAI Moderation API vs GPT-4o-mini Chat Completions: JSON Schema Moderation (and Cost)

Description and use

<p>TL;DR: For an edtech system scoring candidates against a job rubric, use a dedicated moderation API when it exists and its taxonomy fits. When no native moderation endpoint exists, a cheap chat model with strict JSON Schema is the practical fallback. The deciding constraint is structured correctness: every response must be parsed, validated, retried, or escalated without turning a safety decision into prose.</p> <p>I would accept a candidate only after the moderation result passes schema validation. An invalid result is a review-queue event, not a safe result. That rule makes the architectu

Problem

<p>TL;DR: For an edtech system scoring candidates against a job rubric, use a dedicated moderation API when it exists and its taxonomy fits. When no native moderation endpoint exists, a cheap chat model with strict JSON Schema is the practical fallback. The deciding constraint is structured correctness: every response must be parsed, validated, retried, or escalated without turning a safety decision into prose.</p> <p>I would accept a candidate only after the moderation result passes schema validation. An invalid result is a review-queue event, not a safe result. That rule makes the architectu

Outcome

<p>TL;DR: For an edtech system scoring candidates against a job rubric, use a dedicated moderation API when it exists and its taxonomy fits. When no native moderation endpoint exists, a cheap chat model with strict JSON Schema is the practical fallback. The deciding constraint is structured correctness: every response must be parsed, validated, retried, or escalated without turning a safety decision into prose.</p> <p>I would accept a candidate only after the moderation result passes schema validation. An invalid result is a review-queue event, not a safe result. That rule makes the architectu

Evidence

OpenAI Moderation API vs GPT-4o-mini Chat Completions: JSON Schema Moderation (and Cost)

Source