Evals & Safety
A factuality benchmark from OpenAI that tests whether a model can answer short, fact-seeking questions that each have one indisputable answer.
A factuality benchmark from OpenAI that tests whether a model can answer short, fact-seeking questions that each have one indisputable answer. The questions were collected adversarially against GPT-4, and every response is graded as correct, incorrect, or not attempted. The scoring rewards a model that knows what it knows: the ideal model answers the questions it is sure of and declines the rest instead of guessing. Model cards often report it as a hallucination signal.
Primary source: arxiv.org
Example
In practice, developers reach for SimpleQA when they need the capability described above as part of an AI feature or workflow.
Hands-on guides, comparisons, and tutorials that cover Evals & Safety.
FAQ
A factuality benchmark from OpenAI that tests whether a model can answer short, fact-seeking questions that each have one indisputable answer.
SimpleQA sits in the Evals & Safety part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Developers Digest publishes tutorials and videos that cover Evals & Safety topics including SimpleQA. Check the blog and YouTube channel for hands-on walkthroughs.
Related
A system card is a detailed safety and capability report that a frontier lab publishes with a model release, extending the model card idea from the model to the whole deployed system.
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A multimodal benchmark of 2,500 expert-written questions across dozens of subjects, including mathematics, the humanities, and the natural sciences.

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