# FACTS Search V2 > FACTS Search V2 measures factual answering with a shared Brave Search tool. Overall, public, private, hedging, search-count, attempted-accuracy, and F1 measurements remain distinct. Canonical page: https://benchlm.ai/benchmarks/facts-search - Category: [Agentic](/agentic) - Last updated: October 9, 2026 Evaluation results published by [Google DeepMind, Google Research, and Kaggle](https://www.kaggle.com/benchmarks/google/facts-search). undefined Kaggle labels this benchmark Apache 2.0. We retain aggregate measurements with attribution and source links. That declaration does not establish rights to third-party documents, videos, or other underlying task material; no task contents are included. [Original article terms](https://www.apache.org/licenses/LICENSE-2.0). The current FACTS Search route serves version 2. The model can use Brave Search for up to seven agent turns, and a Gemini 3.5 Flash grader compares its answer with the question and reference answer. This board retains version 2 separately from older Search results. The source describes an F1 factuality measure, while its download supplies separate Score and F1 fields. We display Score as published and keep every supplied metric rather than treating those fields as interchangeable. The benchmark depends on its search tool and automated grader; it does not measure every research workflow. The complete official download includes models hidden by the source page's default filters. Source names and task versions stay separate from canonical model profiles; these results do not enter overall or category rankings. These are published source configurations. Compare the task version and disclosed settings before treating a score difference as a model difference. - [Official Kaggle leaderboard](https://www.kaggle.com/benchmarks/google/facts-search) - [Official leaderboard JSON](https://www.kaggle.com/api/v1/benchmarks/google/facts-search/leaderboard) - [Evaluation method](https://www.kaggle.com/code/aminmohamedmohami/facts-v2-search-on-implementation) - [Benchmark-page Apache 2.0 declaration](https://www.apache.org/licenses/LICENSE-2.0) - [FACTS suite introduction](https://deepmind.google/blog/facts-benchmark-suite-systematically-evaluating-the-factuality-of-large-language-models/) ## About FACTS Search V2 - Year: 2025 - Tasks: Search-assisted factual questions; public and held-out sets - Format: Tool-assisted answering with an automated grader - Paper: [FACTS Search V2 methodology](https://www.kaggle.com/code/aminmohamedmohami/facts-v2-search-on-implementation) The current FACTS Search route serves version 2. The model can use Brave Search for up to seven agent turns, and a Gemini 3.5 Flash grader compares its answer with the question and reference answer. This board retains version 2 separately from older Search results. The source describes an F1 factuality measure, while its download supplies separate Score and F1 fields. We display Score as published and keep every supplied metric rather than treating those fields as interchangeable. The benchmark depends on its search tool and automated grader; it does not measure every research workflow. The complete official download includes models hidden by the source page's default filters. Source names and task versions stay separate from canonical model profiles; these results do not enter overall or category rankings. FACTS Search V2 is currently displayed on BenchLM for reference, but it is excluded from the weighted scoring formula. ## Leaderboard (22 source rows) | Rank | Model | Configuration | Creator | Score | |------|-------|---------------|---------|-------| | 1 | [GPT-6 Astra](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-09-15 | — | 89.9% | | 2 | [GPT-5.6 Sol](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-24 | — | 88.5% | | 3 | [GPT-6.1 Sol](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-10-05 | — | 88.2% | | 4 | [Claude Opus 5.5](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-09-24 | — | 86.5% | | 5 | [GPT-6 Sol](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-09-29 | — | 86.1% | | 6 | [Claude Opus 5](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-27 | — | 85.3% | | 7 | [Gemini 4 Argon](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-10-09 | — | 84.0% | | 8 | [Gemini 3.1 Pro Preview](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-25 | — | 83.7% | | 9 | [GPT-5.6 Terra](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-23 | — | 81.7% | | 10 | [GPT-6 Luna](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-09-29 | — | 81.4% | | 11 | [Gemini 3 Flash Preview](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-18 | — | 80.9% | | 12 | [Gemini 3.7 Flash](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-08-18 | — | 80.9% | | 13 | [Claude Opus 4.8](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-24 | — | 79.6% | | 14 | [Grok 4.5](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-23 | — | 79.4% | | 15 | [GPT-5.6 Luna](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-24 | — | 79.4% | | 16 | [Claude Haiku 5.5](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-10-09 | — | 77.5% | | 17 | [Gemini 3.8 Flash](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-09-03 | — | 76.3% | | 18 | [Gemini 3.6 Flash](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-23 | — | 68.2% | | 19 | [Gemini 3.5 Flash](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-23 | — | 64.3% | | 20 | [Gemini 3.5 Flash-Lite](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-23 | — | 63.4% | | 21 | [Gemma 4 26B A4B](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-28 | — | 60.3% | | 22 | [Qwen 3 235B A22B Instruct 2506](https://www.kaggle.com/benchmarks/google/facts-search) | Kaggle benchmark v2; task revision 6; Evaluated 2026-07-27 | — | 53.4% | ## FAQ ### What does FACTS Search V2 measure? FACTS Search V2 measures factual answering with a shared Brave Search tool. Overall, public, private, hedging, search-count, attempted-accuracy, and F1 measurements remain distinct. ### Which source row has the highest reported FACTS Search V2 value? GPT-6 Astra has the highest reported FACTS Search V2 value at 89.9%. These are published source configurations. Compare the task version and disclosed settings before treating a score difference as a model difference. ### How many models are evaluated on FACTS Search V2? The October 9, 2026 contains 22 AI models. ### Does FACTS Search V2 affect BenchLM's overall score? Not directly. FACTS Search V2 is still displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.