SimpleQA Verified: A Reliable Factuality Benchmark to Measure Parametric Knowledge

• URL: http://arxiv.org/abs/2509.07968v1
• Date: Tue, 09 Sep 2025 17:53:58 GMT
• Title: SimpleQA Verified: A Reliable Factuality Benchmark to Measure Parametric Knowledge
• Authors: Lukas Haas, Gal Yona, Giovanni D'Antonio, Sasha Goldshtein, Dipanjan Das,
• Abstract summary: We introduce SimpleQA Verified, a 1,000-prompt benchmark for evaluating Large Language Model (LLM) short-form factuality based on OpenAI's SimpleQA.<n>It addresses critical limitations in OpenAI's benchmark, including noisy and incorrect labels, topical biases, and question redundancy.<n>On this new benchmark, Gemini 2.5 Pro achieves a state-of-the-art F1-score of 55.6, outperforming other frontier models.
• Score: 7.655956608192742
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce SimpleQA Verified, a 1,000-prompt benchmark for evaluating Large Language Model (LLM) short-form factuality based on OpenAI's SimpleQA. It addresses critical limitations in OpenAI's benchmark, including noisy and incorrect labels, topical biases, and question redundancy. SimpleQA Verified was created through a rigorous multi-stage filtering process involving de-duplication, topic balancing, and source reconciliation to produce a more reliable and challenging evaluation set, alongside improvements in the autorater prompt. On this new benchmark, Gemini 2.5 Pro achieves a state-of-the-art F1-score of 55.6, outperforming other frontier models, including GPT-5. This work provides the research community with a higher-fidelity tool to track genuine progress in parametric model factuality and to mitigate hallucinations. The benchmark dataset, evaluation code, and leaderboard are available at: https://www.kaggle.com/benchmarks/deepmind/simpleqa-verified.

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