FACTS Grounding v2
Models write long answers from a supplied document of up to 32k tokens. Judge models check that each answer stays faithful to the document.
The FACTS paper says v2 uses much improved judge models, so scores do not compare with the January 2025 FACTS Grounding. It is the Grounding part of the FACTS Benchmark Suite. Kaggle published a third board version on October 23rd, 2026 with 15 models, with no changelog.
- Made by
- Google DeepMind + Google Research + Kaggle
- Released
- December 2025
- Kind
- Faithful to sources
- Level
- University
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- Public, plus a private test set
- Strongest model tested
-
Gemini 4 Carbon #2 on the capability index
- Last model added
- October 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
We introduce The FACTS Leaderboard, an online leaderboard suite and associated set of benchmarks that comprehensively evaluates the ability of language models to generate factually accurate text across diverse scenarios. The suite provides a holistic measure of factuality by aggregating the performance of models on four distinct sub-leaderboards: (1) FACTS Multimodal, which measures the factuality of responses to image-based questions; (2) FACTS Parametric, which assesses models' world knowledge by answering closed-book factoid questions from internal parameters; (3) FACTS Search, which evaluates factuality in information-seeking scenarios, where the model must use a search API; and (4) FACTS Grounding (v2), which evaluates whether long-form responses are grounded in provided documents, featuring significantly improved judge models. Each sub-leaderboard employs automated judge models to score model responses, and the final suite score is an average of the four components, designed to provide a robust and balanced assessment of a model's overall factuality. The FACTS Leaderboard Suite will be actively maintained, containing both public and private splits to allow for external participation while guarding its integrity. It can be found at https://www.kaggle.com/benchmarks/google/facts .
GPT-6.1 Terra leads with 84.2%
Best score per model from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best.
- 84.2 GPT-6.1 Terra
- 83.3 GPT-6 Sol
- 80.1 GPT-6 Astra
- 78.0 GPT-6.1 Sol
- 77.8
Gemma 4 26B A4B
- 77.2
Gemini 4 Carbon
- 76.7 GPT-6 Luna
- 75.8
Gemma 4 31B IT
- 73.8
Qwen 3.8 Max
- 73.3
Gemini 4 Argon
- 68.6 Grok 4.7
- 68.2
Gemini 3.8 Flash
- 66.6
Gemini 3.6 Flash
- 66.5 Grok 4.6
- 66.0
Gemini 3.5 Flash-Lite
- 62.5 Claude Sonnet 5.5
- 62.5 Claude Opus 5.5
- 61.9 GPT-5.6 Sol
- 60.5 GPT-5.6 Terra
- 57.0 Claude Haiku 5.5
- 56.6
Gemini 3.1 Pro
- 56.1 GLM-5.3-Flash
- 52.5 GPT-5.6 Luna
- 48.6
Gemini 3 Flash
- 20.1 gpt-oss-120b
- 1 GPT-6.1 Terra 84.2%
- 2 GPT-6 Sol 83.3%
- 3 GPT-6 Astra 80.1%
- 4 GPT-6.1 Sol 78%
- 5
Gemma 4 26B A4B 77.8%
- 6
Gemini 4 Carbon 77.2%
- 7 GPT-6 Luna 76.7%
- 8
Gemma 4 31B IT 75.8%
- 9
Qwen 3.8 Max 73.8%
- 10
Gemini 4 Argon 73.3%
- 11 Grok 4.7 68.6%
- 12
Gemini 3.8 Flash 68.2%
- 13
Gemini 3.6 Flash 66.6%
- 14 Grok 4.6 66.5%
- 15
Gemini 3.5 Flash-Lite 66%
- 16 Claude Sonnet 5.5 62.5%
- 17 Claude Opus 5.5 62.5%
- 18 GPT-5.6 Sol 61.9%
- 19 GPT-5.6 Terra 60.5%
- 20 Claude Haiku 5.5 57%
- 21
Gemini 3.1 Pro 56.6%
- 22 GLM-5.3-Flash 56.1%
- 23 GPT-5.6 Luna 52.5%
- 24
Gemini 3 Flash 48.6%
- 25 gpt-oss-120b 20.1%
Source: Official FACTS Grounding v2 leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-6.1 Terra | 84.2% | Oct 2026 | Official leaderboard | |
| 2 | GPT-6 Sol | 83.3% | Sep 2026 | Official leaderboard | |
| 3 | GPT-6 Astra | 80.1% | Sep 2026 | Official leaderboard | |
| 4 | GPT-6.1 Sol | 78% | Sep 2026 | Official leaderboard | |
| 5 | | 77.8% | Apr 2026 | Official leaderboard | |
| 6 | | 77.2% | Oct 2026 | Official leaderboard | |
| 7 | GPT-6 Luna | 76.7% | Sep 2026 | Official leaderboard | |
| 8 | | 75.8% | Apr 2026 | Official leaderboard | |
| 9 | | 73.8% | Aug 2026 | Official leaderboard | |
| 10 | | 73.3% | Sep 2026 | Official leaderboard | |
| 11 | Grok 4.7 | 68.6% | Sep 2026 | Official leaderboard | |
| 12 | | 68.2% | Sep 2026 | Official leaderboard | |
| 13 | | 66.6% | Jul 2026 | Official leaderboard | |
| 14 | Grok 4.6 | 66.5% | Aug 2026 | Official leaderboard | |
| 15 | | 66% | Jul 2026 | Official leaderboard | |
| 16 | Claude Sonnet 5.5 | 62.5% | Sep 2026 | Official leaderboard | |
| 17 | Claude Opus 5.5 | 62.5% | Sep 2026 | Official leaderboard | |
| 18 | GPT-5.6 Sol | 61.9% | Jul 2026 | Official leaderboard | |
| 19 | GPT-5.6 Terra | 60.5% | Jul 2026 | Official leaderboard | |
| 20 | Claude Haiku 5.5 | 57% | Oct 2026 | Official leaderboard | |
| 21 | | 56.6% | Feb 2026 | Official leaderboard | |
| 22 | GLM-5.3-Flash | 56.1% | Aug 2026 | Official leaderboard | |
| 23 | GPT-5.6 Luna | 52.5% | Jul 2026 | Official leaderboard | |
| 24 | | 48.6% | Dec 2025 | Official leaderboard | |
| 25 | gpt-oss-120b | 20.1% | Aug 2025 | Official leaderboard |
7 models have held number one on the official leaderboard since its release in December 2025
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Official FACTS Grounding v2 leaderboard
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Official FACTS Grounding v2 leaderboard
No lab model card reports it yet
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.
Versions
More in Factuality
- SimpleVQA In use Models answer 2,025 short factual questions about images across 9 tasks and 9 topics. An LLM judge grades answers against fixed references.
Qwen3.7-Plus 81.7%
- HallusionBench In use Models answer 1,129 yes or no questions about 346 images, built in pairs to expose language hallucination and visual illusion. Scored by accuracy.
Keye-VL-2.0-30B-A3B 73.5%
- SimpleQA Verified In use 1,000 human-verified, de-duplicated short-answer factual questions measuring parametric knowledge.
Gemini 3.1 Pro 77.5%
- Kimi Hallu Bench In use Models answer hard prompts drawn from practical work tasks. Fact-checking agents score the share of claims that are hallucinated. GPT-6 Astra 4.20%
- Internal adversarially-designed factuality evaluations In use Models answer adversarial questions in nine categories such as history, math and code. Scored on agreement with human ideal responses. GPT-6 Luna 7.60%
- AA-Omniscience v1.1 In use Models answer 3,000 knowledge questions in six domains without tools and may abstain. The index adds correct answers and subtracts wrong ones.
Inkling 2 Small 16.1