FACTS Grounding

A benchmark evaluating language models' ability to generate factually accurate and well-grounded responses based on long-form input context, comprising 1,719 examples with documents up to 32k tokens requiring detailed responses that are fully grounded in provided documents

Gemini 2.5 Pro Preview 06-05 from Google currently leads the FACTS Grounding leaderboard with a score of 0.878 across 13 evaluated AI models.

About this benchmark

What FACTS Grounding measures

FACTS Grounding is a text benchmark that evaluates large language models on factuality, grounding, and reasoning tasks. LLM Stats tracks 13 models on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.7, with the leader reaching 0.9.

Compare leaders on the best AI for factuality, best AI for grounding and best AI for reasoning leaderboards.

Publication

Paper
The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input
Authors
Alon Jacovi, Andrew Wang, Chris Alberti, Connie Tao, and 22 others
Published

Abstract

We introduce FACTS Grounding, an online leaderboard and associated benchmark that evaluates language models' ability to generate text that is factually accurate with respect to given context in the user prompt. In our benchmark, each prompt includes a user request and a full document, with a maximum length of 32k tokens, requiring long-form responses. The long-form responses are required to be fully grounded in the provided context document while fulfilling the user request. Models are evaluated using automated judge models in two phases: (1) responses are disqualified if they do not fulfill the user request; (2) they are judged as accurate if the response is fully grounded in the provided document. The automated judge models were comprehensively evaluated against a held-out test-set to pick the best prompt template, and the final factuality score is an aggregate of multiple judge models to mitigate evaluation bias. The FACTS Grounding leaderboard will be actively maintained over time, and contains both public and private splits to allow for external participation while guarding the integrity of the leaderboard. It can be found at https://www.kaggle.com/facts-leaderboard.

GoogleGemini 2.5 Pro Preview 06-05 leads with 87.8%, followed by GoogleGemini 2.5 Flash at 85.3% and GoogleGemini 2.5 Flash-Lite at 84.1%.

Progress Over Time

Interactive timeline showing model performance evolution on FACTS Grounding

State-of-the-art frontier
Open
Proprietary

FACTS Grounding Leaderboard

13 models
ContextCostLicense
1
21.0M$0.30 / $2.50
3
4
4
612B
727B
8
94B
101.0M$0.50 / $3.00
11
Zhipu AI
Zhipu AI
121.0M$0.25 / $1.50
131B
Notice missing or incorrect data?

FAQ

Common questions about FACTS Grounding.

What is the FACTS Grounding benchmark?

A benchmark evaluating language models' ability to generate factually accurate and well-grounded responses based on long-form input context, comprising 1,719 examples with documents up to 32k tokens requiring detailed responses that are fully grounded in provided documents

What is the FACTS Grounding leaderboard?

The FACTS Grounding leaderboard ranks 13 AI models based on their performance on this benchmark. Currently, Gemini 2.5 Pro Preview 06-05 by Google leads with a score of 0.878. The average score across all models is 0.702.

What is the highest FACTS Grounding score?

The highest FACTS Grounding score is 0.878, achieved by Gemini 2.5 Pro Preview 06-05 from Google.

How many models are evaluated on FACTS Grounding?

13 models have been evaluated on the FACTS Grounding benchmark, with 0 verified results and 13 self-reported results.

Where can I find the FACTS Grounding paper?

The FACTS Grounding paper is available at https://arxiv.org/abs/2501.03200. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does FACTS Grounding cover?

FACTS Grounding is categorized under factuality, grounding, and reasoning. The benchmark evaluates text models.

What is the best open-source model on FACTS Grounding?

Gemini 2.5 Flash-Lite by Google is the top-ranked open-source model on FACTS Grounding, with a score of 0.841 (rank #3).

Which model offers the best value on FACTS Grounding?

Among models scoring within 10% of the leader, Gemini 2.5 Flash from Google is the cheapest, at $0.30 per million input tokens with a score of 0.853.

How is FACTS Grounding scored?

FACTS Grounding is scored using accuracy, reported on a 0–1 scale. Lower is better only when explicitly noted; on this leaderboard, higher scores indicate better performance.

How recent are the FACTS Grounding leaderboard results?

The FACTS Grounding leaderboard was last updated in June 2026 and currently includes 13 evaluated models.

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