FACTS Search
Models answer information-seeking questions with a web search tool (the Brave Search API) and must combine what they find correctly.
890 public and 994 private questions. Part of the FACTS Benchmark Suite. Kaggle later replaced this board with FACTS Search V2.
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 .
- Level
- University Undergraduates and entry-level professionals
- Scored
- Graded by a model A language model scores each response, usually against a rubric.
- Answers
- Short answer A number, word or short string matched to a key.
Gemini 3.1 Pro leads with 85.6% among models released by May 2026
Best score per model from the benchmark's own leaderboard, read on 2 Nov 2026. Where a model ran with several settings or harnesses, we keep its best.
The newest model with a score here came out in May 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- GPT-6 Astra
- Claude Opus 5.5
- GPT-6.1 Terra
- GPT-6.1 Sol
- and 14 more
- 85.6
Gemini 3.1 Pro
- 85.0 GPT-5.5
- 81.0
Gemini 3 Flash
- 80.3 Claude Opus 4.8
- 78.8 Claude Opus 4.7
- 77.7 GPT-5
- 77.4 Grok 4.1 Fast
- 76.7 Claude Opus 4.6
- 76.4 Claude Sonnet 4.6
- 75.3 Grok 4
- 74.8 o3
- 73.3 Claude Opus 4.5
- 72.2 GPT-5.2
- 69.8 Claude Sonnet 4.5
- 68.9
Gemma 4 31B IT
- 67.9 GPT-5 mini
- 67.3 Grok 4 Fast
- 66.8
Gemini 3.1 Flash-Lite
- 66.3 Claude Sonnet 4
- 66.2 o4-mini
- 65.0 Claude Opus 4.1
- 64.6 GPT-4.1
- 63.9
Gemini 2.5 Pro
- 62.6
Gemini 3.5 Flash
- 62.4 GPT-5.1
- 60.0
Gemini 2.5 Flash
- 56.8 GPT-4o
- 56.7
Gemma 4 26B A4B
- 44.5 gpt-oss-120b
- 41.4
Gemma 3 27B
- 34.8 gpt-oss-20b
- 1
Gemini 3.1 Pro 85.6%
- 2 GPT-5.5 85%
- 3
Gemini 3 Flash 81%
- 4 Claude Opus 4.8 80.3%
- 5 Claude Opus 4.7 78.8%
- 6 GPT-5 77.7%
- 7 Grok 4.1 Fast reasoning 77.4%
- 8 Claude Opus 4.6 76.7%
- 9 Claude Sonnet 4.6 76.4%
- 10 Grok 4 75.3%
- 11 o3 74.8%
- 12 Claude Opus 4.5 73.3%
- 13 GPT-5.2 72.2%
- 14 Claude Sonnet 4.5 thinking 69.8%
- 15
Gemma 4 31B IT 68.9%
- 16 GPT-5 mini 67.9%
- 17 Grok 4 Fast reasoning 67.3%
- 18
Gemini 3.1 Flash-Lite 66.8%
- 19 Claude Sonnet 4 66.3%
- 20 o4-mini 66.2%
- 21 Claude Opus 4.1 65%
- 22 GPT-4.1 64.6%
- 23
Gemini 2.5 Pro Jun 2025 63.9%
- 24
Gemini 3.5 Flash 62.6%
- 25 GPT-5.1 62.4%
- 26
Gemini 2.5 Flash Sep 2025 60%
- 27 GPT-4o Mar 2025 56.8%
- 28
Gemma 4 26B A4B 56.7%
- 29 gpt-oss-120b 44.5%
- 30
Gemma 3 27B 41.4%
- 31 gpt-oss-20b 34.8%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 85.6% | Feb 2026 | Official leaderboard | |
| 2 | GPT-5.5 | 85% | Apr 2026 | Official leaderboard | |
| 3 | | 81% | Dec 2025 | Official leaderboard | |
| 4 | Claude Opus 4.8 | 80.3% | May 2026 | Official leaderboard | |
| 5 | Claude Opus 4.7 | 78.8% | Apr 2026 | Official leaderboard | |
| 6 | GPT-5 | 77.7% | Aug 2025 | Official leaderboard | |
| 7 | Grok 4.1 Fast | 77.4% | reasoning | Nov 2025 | Official leaderboard |
| 8 | Claude Opus 4.6 | 76.7% | Feb 2026 | Official leaderboard | |
| 9 | Claude Sonnet 4.6 | 76.4% | Feb 2026 | Official leaderboard | |
| 10 | Grok 4 | 75.3% | Jul 2025 | Official leaderboard | |
| 11 | o3 | 74.8% | Apr 2025 | Official leaderboard | |
| 12 | Claude Opus 4.5 | 73.3% | Nov 2025 | Official leaderboard | |
| 13 | GPT-5.2 | 72.2% | Dec 2025 | Official leaderboard | |
| 14 | Claude Sonnet 4.5 | 69.8% | thinking | Sep 2025 | Official leaderboard |
| 15 | | 68.9% | Apr 2026 | Official leaderboard | |
| 16 | GPT-5 mini | 67.9% | Aug 2025 | Official leaderboard | |
| 17 | Grok 4 Fast | 67.3% | reasoning | Sep 2025 | Official leaderboard |
| 18 | | 66.8% | Mar 2026 | Official leaderboard | |
| 19 | Claude Sonnet 4 | 66.3% | May 2025 | Official leaderboard | |
| 20 | o4-mini | 66.2% | Apr 2025 | Official leaderboard | |
| 21 | Claude Opus 4.1 | 65% | Aug 2025 | Official leaderboard | |
| 22 | GPT-4.1 | 64.6% | Apr 2025 | Official leaderboard | |
| 23 | | 63.9% | Jun 2025 | Official leaderboard | |
| 24 | | 62.6% | May 2026 | Official leaderboard | |
| 25 | GPT-5.1 | 62.4% | Nov 2025 | Official leaderboard | |
| 26 | | 60% | Sep 2025 | Official leaderboard | |
| 27 | GPT-4o Mar 2025 | 56.8% | Mar 2025 | Official leaderboard | |
| 28 | | 56.7% | Apr 2026 | Official leaderboard | |
| 29 | gpt-oss-120b | 44.5% | Aug 2025 | Official leaderboard | |
| 30 | | 41.4% | Mar 2025 | Official leaderboard | |
| 31 | gpt-oss-20b | 34.8% | Aug 2025 | Official leaderboard |
3 models have held number one since its release in Dec 2025
Lab claims count from the day the card came out, independent runs from the model’s release.
The best score passed 85% in Feb 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
No lab model card reports it yet
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.
Versions
We switch the top row to each new version when it comes out. Open it for one row per version. An old version stays in play while people still test it, so whoever first takes it past 85% gets credit for closing it out.
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%
- GaRAGe In use Models write long-form RAG answers to 2,366 questions with human-annotated grounding passages. Scoring checks whether answers use the relevant passages.
Nemotron 3.5 Bolt E4B 40.7%
- 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. Kimi K3.1 Pro 8.30%
- RAGTruth In use A word-level annotated corpus of hallucinations in retrieval-augmented generation answers. It is used to train and evaluate hallucination detection and RAG faithfulness.
Nemotron 3.5 Bolt E4B 77.9%