Large language models can be considered safety models in two main ways

Large language models can be considered safety models in two main ways:

- Fine-tuned safety models start as general reasoning models (like gpt-oss) and are trained to respond safely within user interactions.
- Prebaked safety models (like ShieldGemma, LlamaGuard, RoGuard, etc) come with built-in definitions of what counts as “unsafe” and fixed policy taxonomies.

gpt-oss-safeguard was purpose-built for Trust & Safety workflows and is a policy-following model that can reliably interpret and enforce **your own written standards and tell you why it made the decision it made**. The reasoning behind the model makes it well-suited for integration with a larger safety system that is rooted in auditability and customization.