OpenAI o1 System Card

OpenAI o3-mini System Card

This report outlines the safety work carried out for the OpenAI o3-mini model, including safety evaluations, external red teaming, and Preparedness Framework evaluations.

Introducing OpenAI o1

Operator System Card

Drawing from OpenAI’s established safety frameworks, this document highlights our multi-layered approach, including model and product mitigations we’ve implemented to protect against prompt engineering and jailbreaks, protect privacy and security, as well as details our external red teaming efforts, safety evaluations, and ongoing work to further refine these safeguards.

OpenAI Red Teaming Network

We’re announcing an open call for the OpenAI Red Teaming Network and invite domain experts interested in improving the safety of OpenAI’s models to join our efforts.

OpenAI and Los Alamos National Laboratory announce research partnership

OpenAI and Los Alamos National Laboratory are working to develop safety evaluations to assess and measure biological capabilities and risks associated with frontier models.

Deep research System Card

This report outlines the safety work carried out prior to releasing deep research including external red teaming, frontier risk evaluations according to our Preparedness Framework, and an overview of the mitigations we built in to address key risk areas.

OpenAI Board Forms Safety and Security Committee

Addendum to OpenAI o3 and o4-mini system card: OpenAI o3 Operator

We are replacing the existing GPT-4o-based model for Operator with a version based on OpenAI o3. The API version will remain based on 4o.

OpenAI GPT-4.5 System Card

We’re releasing a research preview of OpenAI GPT‑4. 5, our largest and most knowledgeable model yet.

Announcing the OpenAI Safety Fellowship

A pilot program to support independent safety and alignment research and develop the next generation of talent

OpenAI o3-mini

Safety and alignment in an era of long-horizon models

OpenAI shares lessons from deploying long-running AI models, highlighting new safety risks, observed failures, and improved safeguards through iterative deployment.