{"slug": "openai-o1-system-card-2024", "title": "OpenAI o1 System Card (2024)", "summary": "OpenAI released the system card for its o1 and o1-mini models on December 21, 2024, detailing safety evaluations, external red teaming, and Preparedness Framework assessments. The models, trained with large-scale reinforcement learning to reason using chain of thought, achieve state-of-the-art performance on benchmarks for risks such as generating illicit advice, stereotyped responses, and jailbreaks, while also introducing heightened risks from increased intelligence.", "body_md": "# Computer Science > Artificial Intelligence\n\n[Submitted on 21 Dec 2024 (\n\n[v1](https://arxiv.org/abs/2412.16720v1)), last revised 30 Apr 2026 (this version, v2)]# Title:OpenAI o1 System Card\n\n[View PDF](/pdf/2412.16720)\n\n[HTML (experimental)](https://arxiv.org/html/2412.16720v2)\n\nAbstract:The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provide new avenues for improving the safety and robustness of our models. In particular, our models can reason about our safety policies in context when responding to potentially unsafe prompts, through deliberative alignment. This leads to state-of-the-art performance on certain benchmarks for risks such as generating illicit advice, choosing stereotyped responses, and succumbing to known jailbreaks. Training models to incorporate a chain of thought before answering has the potential to unlock substantial benefits, while also increasing potential risks that stem from heightened intelligence. Our results underscore the need for building robust alignment methods, extensively stress-testing their efficacy, and maintaining meticulous risk management protocols. This report outlines the safety work carried out for the OpenAI o1 and OpenAI o1-mini models, including safety evaluations, external red teaming, and Preparedness Framework evaluations.\n\n## Submission history\n\nFrom: Lama Ahmad [[view email](/show-email/7a3f9798/2412.16720)]\n\n**Sat, 21 Dec 2024 18:04:31 UTC (15,258 KB)**\n\n[[v1]](/abs/2412.16720v1)**[v2]** Thu, 30 Apr 2026 02:46:40 UTC (15,260 KB)\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/openai-o1-system-card-2024", "canonical_source": "https://arxiv.org/abs/2412.16720", "published_at": "2026-08-17 13:58:52+00:00", "updated_at": "2026-08-17 14:11:06.082052+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-safety", "ai-research", "large-language-models", "ai-policy"], "entities": ["OpenAI", "OpenAI o1", "OpenAI o1-mini", "arXiv", "Preparedness Framework"], "alternates": {"html": "https://wpnews.pro/news/openai-o1-system-card-2024", "markdown": "https://wpnews.pro/news/openai-o1-system-card-2024.md", "text": "https://wpnews.pro/news/openai-o1-system-card-2024.txt", "jsonld": "https://wpnews.pro/news/openai-o1-system-card-2024.jsonld"}}