OpenAI has launched gpt-oss-safeguard, a pair of open-weight safety reasoning models capable of classifying content based on developer-specified policies.
Available in 120B and 20B parameter sizes under the permissive Apache 2.0 license, the models are downloadable, modifiable, and deployable by anyone via Hugging Face.
Instead of relying on pre-trained, static policies, developers can supply their own policies at inference time, making moderation more flexible and better suited to evolving risks.
The models produce explainable outputs with visible chain-of-thought reasoning to help teams understand why content has been classified in a certain way.
gpt-oss-safeguard is especially useful for platforms that are dealing with new threats, subtle domains, or limited quantities of training data.
By separating safety policy from model weights, developers can iterate rapidly without needing to retrain classifiers, an approach that OpenAI already employs internally with its “Safety Reasoner” system.
While high-volume production workloads may continue to require faster, specialized classifiers, these models enable deeper, more interpretable moderation when accuracy matters most.
OpenAI will continue to develop the models in partnership with the ROOST community to support safety researchers, platforms, and builders who want to keep online spaces safe with open tooling.
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