Benchmark Almanac

FACTS Multimodal

Gemini 4 Carbon 60.2% leads since October 2026
Not in model cards

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.

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 .

Abstract of The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality (arXiv:2512.10791, CC0)
23
Models scored on its own leaderboard

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.

  1. 1 Gemini 4 Carbon 60.2%
  2. 2 Gemini 3.8 Flash 57.6%
  3. 3 Claude Opus 5.5 56.4%
  4. 4 GPT-6 Astra 55.2%
  5. 5 Gemini 4 Argon 54.2%
  6. 6 Gemini 3.6 Flash 53.7%
  7. 7 GPT-6.1 Sol 52.6%
  8. 8 Qwen 3.8 Max 51.5%
  9. 9 Gemini 3.1 Pro 50.4%
  10. 10 Claude Sonnet 5.5 50.4%
  11. 11 Gemini 3 Flash 49.7%
  12. 12 GPT-6.1 Terra 48.8%
  13. 13 GPT-5.6 Sol 46.4%
  14. 14 GPT-6 Sol 43.9%
  15. 15 Gemma 4 31B IT 42.3%
  16. 16 Grok 4.7 40.9%
  17. 17 GPT-5.6 Terra 39.9%
  18. 18 Gemma 4 26B A4B 39.5%
  19. 19 Grok 4.6 39.3%
  20. 20 Claude Haiku 5.5 38.9%
  21. 21 GPT-6 Luna 38.7%
  22. 22 GPT-5.6 Luna 37.4%
  23. 23 Gemini 3.5 Flash-Lite 36.1%

Source: Official FACTS Multimodal leaderboard

#ModelScoreSettingDateSource
1 Gemini 4 Carbon 60.2% Oct 2026 Official leaderboard
2 Gemini 3.8 Flash 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 Gemini 4 Argon 54.2% Sep 2026 Official leaderboard
6 Gemini 3.6 Flash 53.7% Jul 2026 Official leaderboard
7 GPT-6.1 Sol 52.6% Sep 2026 Official leaderboard
8 Qwen 3.8 Max 51.5% Aug 2026 Official leaderboard
9 Gemini 3.1 Pro 50.4% Feb 2026 Official leaderboard
10 Claude Sonnet 5.5 50.4% Sep 2026 Official leaderboard
11 Gemini 3 Flash 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 Gemma 4 31B IT 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 Gemma 4 26B A4B 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 Gemini 3.5 Flash-Lite 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.

Google DeepMind
Own leaderboard 5 leaders

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.

On the benchmark’s own leaderboard Best so far
0% 20% 40% 60% 80% 100% 2026 2027 Near the ceiling (85%) Gemini 4 Carbon Gemini 3.6 Flash Gemini 3.1 Pro 0% 20% 40% 60% 80% 100% 2026 2027 Near the ceiling (85%) Gemini 4 Carbon Gemini 3.6 Flash

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

All 74 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