Our updated Preparedness Framework

We’re releasing an update to our Preparedness Framework, our process for tracking and preparing for advanced AI capabilities that could introduce new risks of severe harm. As our models continue to get more capable⁠, safety will increasingly depend on having the right real-world safeguards in place.

This update introduces a sharper focus on the specific risks that matter most, stronger requirements for what it means to “sufficiently minimize” those risks in practice, and clearer operational guidance on how we evaluate, govern, and disclose our safeguards. Additionally, we introduce future-facing research categories that allow us to remain at the forefront of understanding emerging capabilities to keep pace with where the technology is headed. We will continue investing deeply in this process by making our preparedness work more actionable, rigorous, and transparent as the technology advances.

We’ve learned a great deal from our own testing, insights from external experts, and lessons from the field. This update reflects that progress. In line with our core safety principles⁠, it makes targeted improvements that include:

We’ll continue to publish our Preparedness findings with each frontier model release, just as we’ve done for GPT‑4o⁠, OpenAI o1⁠, Operator⁠, o3‑mini⁠, deep research⁠, and GPT‑4.5⁠, and share new benchmarks to support broader safety efforts across the field.

We’re deeply grateful to internal teams, external researchers and industry peers who’ve contributed invaluable insights to this latest update. The Preparedness Framework remains a living document, and we expect to continue updating it as we learn more.