Moderator
On-device NSFW detection that flags nudity before upload, trained only on licensed and synthetic data, safe to ship commercially.
Flag nudity before upload or display.
Questionable uploads never reach your servers, your CDN or a moderator's queue. Five separate detections (exposed nipples, genitals, buttocks, nudity and sexual activity) feed the score, and your policy decides which of them count.
Every image Moderator trained on is licensed or synthetic, so it goes into a commercial product with no copyright exposure. The whole model is 9.7MB on Apple and 9.2MB elsewhere, so the check runs on the phone before the upload starts.
Catches 87.8% of NSFW images.
Catches 87.8% of NSFW images and passes 93.7% of safe ones at a 6.3% false-block rate, about half NudeNet's, from a 9.7MB on-device model.
Internal evaluation on a proprietary held-out set, not a published benchmark. The headline numbers are the 8-crop pass, which is the one to run on a single image; for video, one crop per frame is cheaper and more precise per frame, and sampling across frames recovers the recall.
Use cases
Flag nudity before upload or display.
Pre-upload filtering
Screen a user's image on the phone before it uploads. Nothing questionable reaches your servers, and no one on your team has to look at the image to find out.
A policy you control
The .standard policy counts all five detections. .allowTopless leaves exposed nipples out of the score, for platforms whose rules permit them.
Warn at the picker, not after the post
Score an image the moment a user picks it, and warn them on the spot. An hour-later takedown costs you a support thread.
What the model does
- Trained only on permissively licensed and synthetic images, with nothing scraped.
- Scores any image or video frame for nudity on the device, before upload.
- Five detection heads: exposed nipples, genitals, buttocks, nudity, and sexual activity.
- A policy decides what counts toward the NSFW score, from
.standard(all five) to.allowTopless(excludes exposed nipples).
Getting started
Add content moderation to your iOS or macOS, Android or web app in a few lines of code. Moderator docs.
// Swift Package Manager
.package(url: "https://github.com/Desert-Ant-Labs/desert-ant-core", from: "3.5.0")
// target dependency
.product(name: "Moderator", package: "desert-ant-core")Add Moderator from Desert Ant Labs to this Swift project (iOS, macOS). What it does: On-device NSFW and Nudity Detection for Images and Video. SDK: Swift (iOS, macOS) Repo: https://github.com/Desert-Ant-Labs/desert-ant-core#readme // Swift Package Manager .package(url: "https://github.com/Desert-Ant-Labs/desert-ant-core", from: "3.5.0") // target dependency .product(name: "Moderator", package: "desert-ant-core") Reference: - Model page: https://desertant.com/models/moderator/ - Full catalog and other models: https://desertant.com/llms.txt Add the SDK, then follow its README for the exact API and current version. Do not invent API names or method signatures; confirm them against the README.
// build.gradle.kts (Maven Central)
implementation("ai.desertant:moderator:3.5.0")Add Moderator from Desert Ant Labs to this Kotlin project (Android).
What it does: On-device NSFW and Nudity Detection for Images and Video.
SDK:
Kotlin (Android)
Repo: https://github.com/Desert-Ant-Labs/desert-ant-core#readme
// build.gradle.kts (Maven Central)
implementation("ai.desertant:moderator:3.5.0")
Reference:
- Model page: https://desertant.com/models/moderator/
- Full catalog and other models: https://desertant.com/llms.txt
Add the SDK, then follow its README for the exact API and current version. Do not invent API names or method signatures; confirm them against the README.
npm i @desert-ant-labs/moderator @litertjs/coreAdd Moderator from Desert Ant Labs to this JavaScript / TypeScript project (Web, Node.js). What it does: On-device NSFW and Nudity Detection for Images and Video. SDK: JavaScript / TypeScript (Web, Node.js) Repo: https://github.com/Desert-Ant-Labs/desert-ant-core#readme npm i @desert-ant-labs/moderator @litertjs/core Reference: - Model page: https://desertant.com/models/moderator/ - Full catalog and other models: https://desertant.com/llms.txt Add the SDK, then follow its README for the exact API and current version. Do not invent API names or method signatures; confirm them against the README.
Specs
- Accuracy
- Recall 87.8%, specificity 93.7% at threshold 0.50
- Model
- On-device image classifier
- On-device size
- 9.7MB on Apple (Core ML), 9.2MB elsewhere (LiteRT)
- Platforms
- iOS, macOS, tvOS, visionOS, Android, Linux, Windows, browser, and Node
Moderator is a moderation aid, not a legal determination. Send every flag to a human reviewer before anything is blocked.
Moderator covers adult content only. Minors are out of scope by design and excluded from the training set.
FAQ
What is Moderator?
On-device NSFW detection that flags nudity before upload, trained only on licensed and synthetic data, safe to ship commercially.
Does Moderator run on device?
Yes. Moderator runs on the device, with no server call, so the data stays with the user.
Which platforms does Moderator support?
Moderator ships as a native on-device SDK for Swift, Kotlin, JavaScript / TypeScript.
How much does Moderator cost?
Each model is free up to 100k monthly active devices. Inference is unlimited. Contact us for custom licenses.
How accurate or fast is Moderator?
Catches 87.8% of NSFW images and passes 93.7% of safe ones at a 6.3% false-block rate, about half NudeNet's, from a 9.7MB on-device model.