Safety is foundational to our approach to open models. They present a different risk profile than proprietary models: Once they are released, determined attackers could fine-tune them to bypass safety refusals or directly optimize for harm without the possibility for OpenAI to implement additional mitigations or to revoke access.

In some contexts, developers and enterprises will need to implement extra safeguards in order to replicate the system-level protections built into models served through our API and products. We’re terming this document a model card, rather than a system card, because the gpt-oss models will be used as part of a wide range of systems, created and maintained by a wide range of stakeholders. While the models are designed to follow OpenAI’s safety policies by default, other stakeholders will also make and implement their own decisions about how to keep those systems safe.

We ran scalable capability evaluations on gpt-oss-120b, and confirmed that the default model does not reach our indicative thresholds for High capability in any of the three Tracked Categories of our Preparedness Framework (Biological and Chemical capability, Cyber capability, and AI Self-Improvement). We also investigated two additional questions:

As part of this launch, OpenAI is reaffirming its commitment to advancing beneficial AI and raising safety standards across the ecosystem.