Natural Questions

Natural Questions is a question answering dataset featuring real anonymized queries issued to Google search engine. It contains 307,373 training examples where annotators provide long answers (passages) and short answers (entities) from Wikipedia pages, or mark them as unanswerable.

Gemma 2 27B from Google currently leads the Natural Questions leaderboard with a score of 0.345 across 7 evaluated AI models.

Paper
About this benchmark

What Natural Questions measures

Natural Questions is a text benchmark that evaluates large language models on general, reasoning, and search tasks. LLM Stats tracks 7 models on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.2, with the leader reaching 0.3.

Compare leaders on the best AI for general, best AI for reasoning and best AI for search leaderboards.

Publication

Paper
A BERT Baseline for the Natural Questions
Authors
Chris Alberti, Kenton Lee, Michael Collins
Published

Abstract

This technical note describes a new baseline for the Natural Questions. Our model is based on BERT and reduces the gap between the model F1 scores reported in the original dataset paper and the human upper bound by 30% and 50% relative for the long and short answer tasks respectively. This baseline has been submitted to the official NQ leaderboard at ai.google.com/research/NaturalQuestions. Code, preprocessed data and pretrained model are available at https://github.com/google-research/language/tree/master/language/question_answering/bert_joint.

GoogleGemma 2 27B leads with 34.5%, followed by Mistral AIMistral NeMo Instruct at 31.2% and GoogleGemma 2 9B at 29.2%.

Progress Over Time

Interactive timeline showing model performance evolution on Natural Questions

State-of-the-art frontier
Open
Proprietary

Natural Questions Leaderboard

7 models
ContextCostLicense
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Notice missing or incorrect data?

FAQ

Common questions about Natural Questions.

What is the Natural Questions benchmark?

Natural Questions is a question answering dataset featuring real anonymized queries issued to Google search engine. It contains 307,373 training examples where annotators provide long answers (passages) and short answers (entities) from Wikipedia pages, or mark them as unanswerable.

What is the Natural Questions leaderboard?

The Natural Questions leaderboard ranks 7 AI models based on their performance on this benchmark. Currently, Gemma 2 27B by Google leads with a score of 0.345. The average score across all models is 0.240.

What is the highest Natural Questions score?

The highest Natural Questions score is 0.345, achieved by Gemma 2 27B from Google.

How many models are evaluated on Natural Questions?

7 models have been evaluated on the Natural Questions benchmark, with 0 verified results and 7 self-reported results.

Where can I find the Natural Questions paper?

The Natural Questions paper is available at https://arxiv.org/abs/1901.08634. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does Natural Questions cover?

Natural Questions is categorized under general, reasoning, and search. The benchmark evaluates text models.

What is the best open-source model on Natural Questions?

Gemma 2 27B by Google is the top-ranked open-source model on Natural Questions, with a score of 0.345 (rank #1).

How recent are the Natural Questions leaderboard results?

The Natural Questions leaderboard was last updated in May 2026 and currently includes 7 evaluated models.

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