OpenAI Model Spec Explained: How AI Models Are Designed to Behave Safely and Helpfully

OpenAI has made public its Model Spec, a detailed framework describing how the AI models powering its products and API platform are intended to behave. By sharing this document, the company aims to deepen the public conversation about AI model behavior and invite scrutiny from researchers, developers, and the broader public. The Model Spec does not capture every technical detail, and OpenAI acknowledges that its production models do not yet fully reflect it. Nonetheless, the company is actively training its systems toward these principles and refining them over time.

The Model Spec is built around a central mission: ensuring that artificial general intelligence benefits all of humanity. To pursue this, OpenAI identifies three interrelated goals. The first is to iteratively deploy models that empower developers and users. The second is to prevent models from causing serious harm to users or third parties. The third is to maintain OpenAI's license to operate by protecting the organization from legal and reputational damage. These goals can sometimes conflict, and the Model Spec provides a structured way to navigate those trade-offs.

Three principles shape the document. Maximizing helpfulness and freedom means treating the AI assistant as a tool that empowers users, giving them as much autonomy and customization as safety and feasibility allow. Minimizing harm acknowledges that a system serving hundreds of millions of people carries real risks, and that some rules exist specifically to reduce them, though model behavior alone cannot eliminate AI risk. Choosing sensible defaults recognizes that many behaviors are reasonable starting points that not every user or context will want, so these defaults can be adjusted by users or developers where appropriate.

The Model Spec groups AI risks into three categories, each with its own mitigations. Misaligned goals occur when the assistant pursues the wrong objective, either by misunderstanding a task or by being manipulated by a third party such as malicious instructions hidden on a website; mitigations include careful adherence to the chain of command and asking clarifying questions. Execution errors occur when the assistant understands the task but performs it incorrectly, such as giving inaccurate medical dosages; these are reduced by avoiding factual and reasoning mistakes, expressing uncertainty, and giving users the information they need to decide for themselves. Harmful instructions arise when following a user or developer request would cause harm, such as providing self-harm guidance; these cases require weighing empowerment against harm prevention and are governed by specific refusal and caution rules.

To reconcile competing instructions, the Model Spec assigns each instruction a level of authority. Platform-level rules cannot be overridden by developers or users and are mostly prohibitive, covering catastrophic risks, direct physical harm, illegal activity, and undermining the chain of command; when two platform rules conflict, the model defaults to inaction. Developer-level instructions, given through the API, should be followed unless they conflict with platform rules, and OpenAI generally grants developers broad latitude. User-level instructions from end users should be honored unless they conflict with developer or platform instructions. Guideline-level instructions are defaults that can be implicitly overridden by context, background knowledge, or user history; for example, a request to speak like a realistic pirate implicitly overrides a guideline against swearing. Placing many behaviors at this level avoids paternalism while preserving predictability.

The Model Spec defines the vocabulary used throughout. The assistant is the entity that users and developers interact with. Inputs take the form of conversations made up of messages, each with a role (system, developer, user, assistant, or tool), optional recipient fields for function or tool calls, content, and optional settings such as maximum token limits. Tools are external programs, such as code execution or web retrieval, that the assistant can invoke. Some models also produce hidden chain-of-thought reasoning that guides behavior but is not usually exposed. Tokens are the units of text the model processes and set length limits. Developers build applications on the API, while users interact with products, often without seeing developer or system messages.

The Model Spec is only one component of OpenAI's approach to responsible AI deployment. It works alongside usage policies that set expectations for how people may use the API and ChatGPT, and safety protocols that include testing, monitoring, and mitigation of potential issues. Together, these layers reflect the recognition that model behavior alone cannot resolve every risk.

OpenAI presents the Model Spec as a living document. It will be revised based on feedback and lessons learned from serving users worldwide. To encourage broad adoption and collaboration, the document is dedicated to the public domain under the Creative Commons CC0 1.0 deed, allowing anyone to use, adapt, and build upon it freely.

The OpenAI Model Spec offers a transparent look at how a leading AI developer intends its models to think, prioritize, and act. By articulating its goals, risk categories, and chain of command openly, OpenAI invites public discussion on how AI systems should balance helpfulness, safety, and accountability. As AI becomes a foundational technology, frameworks like this will play a central role in shaping whether its benefits are widely shared.