SAN FRANCISCO — January 2026 — OpenAI has introduced Prism, a new framework designed to evaluate, measure, and better understand how AI systems behave across a wide range of real-world scenarios.

Prism is built to help researchers, developers, and policymakers move beyond surface-level benchmarks by providing a more structured view of model behavior. OpenAI said the system is intended to make AI evaluation clearer, more comparable, and more actionable as models become more capable and widely deployed.

Rather than focusing on a single score, Prism evaluates models across multiple dimensions, including reasoning, reliability, safety-related behavior, and how performance shifts under different conditions. The goal is to surface strengths, weaknesses, and tradeoffs in a way that supports better deployment decisions and more transparent communication about model capabilities.

OpenAI positioned Prism as part of its broader safety and governance efforts. As AI systems are used in higher-stakes settings, the company said understanding how models behave across contexts is just as important as improving raw performance. Prism helps highlight where models are robust, where they are brittle, and where additional safeguards may be needed.

The system is also designed to evolve. OpenAI said Prism will be updated as new risks, use cases, and evaluation methods emerge, allowing it to remain relevant as models and deployment environments change.

Prism is being used internally at OpenAI and shared with partners and researchers as part of ongoing work to improve AI transparency and accountability. The company said it plans to continue expanding how Prism is applied, with the aim of creating a common language for discussing AI behavior and risk.

With the introduction of Prism, OpenAI is signaling a shift toward deeper, more nuanced evaluation as a foundation for responsible AI development and deployment.