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Moderation models screen text for unsafe, harmful, or policy-sensitive content before it reaches your application or model workflow. Call the dedicated Moderations API (POST /v1/moderations) — a moderation model is routable only on this endpoint and returns OpenAI’s native moderations envelope, so it drops into any pipeline written against omni-moderation-latest.

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zlm-v1-moderation-edge

ZeroGPU’s moderation model screens text for unsafe, harmful, or policy-sensitive content and returns the complete OpenAI 13-category taxonomy (a flagged verdict, per-category booleans, and calibrated category_scores), so it drops into any pipeline written against omni-moderation-latest. Under the hood it’s an 86M-parameter DeBERTa encoder with a shared trunk feeding one binary safe/unsafe head and 13 category heads, with per-category thresholds calibrated on held-out validation data. In head-to-head benchmarks against OpenAI omni-moderation it wins the binary safe/unsafe decision (0.899 vs 0.853 F1) and 9 of 13 harm categories, with the largest gains on graphic violence, illicit content, and self-harm, while returning verdicts 1.2–1.8× faster at the median on production-range inputs, because inference is co-located at the edge instead of a round trip to a central API. Moderation sits inline in front of every response your app serves; this is the model that’s fast and accurate enough to live there.
References: Moderation benchmark • Terms • Privacy Send the text to classify as input — a string, an array of strings (one verdict per element), or an array of { "type": "text", "text": "…" } content parts.
Moderations API
The response is OpenAI’s native moderations envelope — an id, the resolved model, and a results array (one entry per input). Each result carries a flagged verdict, per-category categories booleans, category_scores in [0, 1], and category_applied_input_types (always ["text"] for this text-only model), with all 13 categories present in OpenAI’s order:
Response