FACTS Multimodal
Models answer questions about input images and must combine what they see with world knowledge. A judge checks coverage and contradictions.
711 public and 811 private prompts. Part of the FACTS Benchmark Suite. Scores were the lowest of the four parts at launch.
- Made by
- Google DeepMind + Google Research + Kaggle
- Released
- December 2025
- Kind
- Short factual questions
- 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 .
Gemini 4 Carbon leads with 60.2%
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.
- 60.2
Gemini 4 Carbon
- 57.6
Gemini 3.8 Flash
- 56.4 Claude Opus 5.5
- 55.2 GPT-6 Astra
- 54.2
Gemini 4 Argon
- 53.7
Gemini 3.6 Flash
- 52.6 GPT-6.1 Sol
- 51.5
Qwen 3.8 Max
- 50.4
Gemini 3.1 Pro
- 50.4 Claude Sonnet 5.5
- 49.7
Gemini 3 Flash
- 48.8 GPT-6.1 Terra
- 46.4 GPT-5.6 Sol
- 43.9 GPT-6 Sol
- 42.3
Gemma 4 31B IT
- 40.9 Grok 4.7
- 39.9 GPT-5.6 Terra
- 39.5
Gemma 4 26B A4B
- 39.3 Grok 4.6
- 38.9 Claude Haiku 5.5
- 38.7 GPT-6 Luna
- 37.4 GPT-5.6 Luna
- 36.1
Gemini 3.5 Flash-Lite
- 1
Gemini 4 Carbon 60.2%
- 2
Gemini 3.8 Flash 57.6%
- 3 Claude Opus 5.5 56.4%
- 4 GPT-6 Astra 55.2%
- 5
Gemini 4 Argon 54.2%
- 6
Gemini 3.6 Flash 53.7%
- 7 GPT-6.1 Sol 52.6%
- 8
Qwen 3.8 Max 51.5%
- 9
Gemini 3.1 Pro 50.4%
- 10 Claude Sonnet 5.5 50.4%
- 11
Gemini 3 Flash 49.7%
- 12 GPT-6.1 Terra 48.8%
- 13 GPT-5.6 Sol 46.4%
- 14 GPT-6 Sol 43.9%
- 15
Gemma 4 31B IT 42.3%
- 16 Grok 4.7 40.9%
- 17 GPT-5.6 Terra 39.9%
- 18
Gemma 4 26B A4B 39.5%
- 19 Grok 4.6 39.3%
- 20 Claude Haiku 5.5 38.9%
- 21 GPT-6 Luna 38.7%
- 22 GPT-5.6 Luna 37.4%
- 23
Gemini 3.5 Flash-Lite 36.1%
Source: Official FACTS Multimodal leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 60.2% | Oct 2026 | Official leaderboard | |
| 2 | | 57.6% | Sep 2026 | Official leaderboard | |
| 3 | Claude Opus 5.5 | 56.4% | Sep 2026 | Official leaderboard | |
| 4 | GPT-6 Astra | 55.2% | Sep 2026 | Official leaderboard | |
| 5 | | 54.2% | Sep 2026 | Official leaderboard | |
| 6 | | 53.7% | Jul 2026 | Official leaderboard | |
| 7 | GPT-6.1 Sol | 52.6% | Sep 2026 | Official leaderboard | |
| 8 | | 51.5% | Aug 2026 | Official leaderboard | |
| 9 | | 50.4% | Feb 2026 | Official leaderboard | |
| 10 | Claude Sonnet 5.5 | 50.4% | Sep 2026 | Official leaderboard | |
| 11 | | 49.7% | Dec 2025 | Official leaderboard | |
| 12 | GPT-6.1 Terra | 48.8% | Oct 2026 | Official leaderboard | |
| 13 | GPT-5.6 Sol | 46.4% | Jul 2026 | Official leaderboard | |
| 14 | GPT-6 Sol | 43.9% | Sep 2026 | Official leaderboard | |
| 15 | | 42.3% | Apr 2026 | Official leaderboard | |
| 16 | Grok 4.7 | 40.9% | Sep 2026 | Official leaderboard | |
| 17 | GPT-5.6 Terra | 39.9% | Jul 2026 | Official leaderboard | |
| 18 | | 39.5% | Apr 2026 | Official leaderboard | |
| 19 | Grok 4.6 | 39.3% | Aug 2026 | Official leaderboard | |
| 20 | Claude Haiku 5.5 | 38.9% | Oct 2026 | Official leaderboard | |
| 21 | GPT-6 Luna | 38.7% | Sep 2026 | Official leaderboard | |
| 22 | GPT-5.6 Luna | 37.4% | Jul 2026 | Official leaderboard | |
| 23 | | 36.1% | Jul 2026 | Official leaderboard |
5 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 Multimodal 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 Multimodal 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.
More in Factuality
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Qwen3.7-Plus 81.7%
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- SimpleQA Verified In use 1,000 human-verified, de-duplicated short-answer factual questions measuring parametric knowledge.
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- 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%
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