Benchmark Almanac

Global PIQA

Gemini 3 Pro 93.4% leads since Nov 2025 Fading

Models pick the correct solution to everyday commonsense prompts in over 100 languages, many about local foods and customs. Scoring is accuracy.

The license forbids training AI systems on it or on synthetic data seeded from it. The record covers the non-parallel split of over 100 languages, released in 2025-10. A parallel split of culturally agnostic questions in 131 language varieties followed in 2026-04, and its scores are a different test.

In the authors’ words

To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we present Global PIQA, a participatory commonsense reasoning benchmark for over 100 languages, constructed by hand by over 350 researchers from over 65 countries around the world. The 141 language varieties in Global PIQA cover five continents, 19 language families, and 24 writing systems. In the non-parallel split of Global PIQA, over 50% of examples reference local foods, customs, traditions, or other culturally-specific elements. In the parallel split, we translate more "culturally agnostic" commonsense reasoning questions into 131 language varieties, for direct cross-lingual comparisons. In both splits, all examples have been verified by native speakers of the languages. We find that state-of-the-art LLMs perform well on Global PIQA in aggregate, but they exhibit weaker performance in lower-resource languages (e.g. up to a 68% accuracy gap between languages in the parallel split). Global PIQA highlights that in many languages and cultures, everyday knowledge remains an area for improvement in LLMs, alongside more widely-discussed capabilities such as complex reasoning and expert knowledge. Beyond its uses for LLM evaluation, Global PIQA provides a glimpse into the wide diversity of cultures in which human language is embedded.

Abstract of Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures (arXiv:2510.24081, CC0)
Made by MRL Benchmarks (over 350 researchers) Released Oct 2025 Reasoning in many languages All tasks public Last in a launch post Jun 2026 , dropped after it saturated Last model added Jun 2026
Level
Everyday Most adults, without training
Scored
Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
Answers
Multiple choice
8
Models scored in lab cards
8
Launch posts list it, from 3 labs
1
System card reports it, from 1 lab

Gemini 3 Pro leads with 93.4% among models released by Jun 2026

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

The newest model with a score here came out in Jun 2026, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:

  1. 1 Gemini 3 Pro 93.4%
  2. 2 Gemini 3 Flash 92.8%
  3. 3 Seed2.0 Pro 92.3%
  4. 4 Qwen3.7-Max 91.4%
  5. 5 Qwen3.7-Plus 90.3%
  6. 6 Qwen3.5 397B-A17B 89.8%
  7. 7 Qwen 3.6 Plus 89.8%
  8. 8 Qwen3.5-122B-A10B 88.4%
#ModelScoreSettingDateSource
1 Gemini 3 Pro 93.4% Nov 2025 Model card
2 Gemini 3 Flash 92.8% Dec 2025 Model card
3 Seed2.0 Pro 92.3% Feb 2026 Model card
4 Qwen3.7-Max 91.4% May 2026 Model card
5 Qwen3.7-Plus 90.3% Jun 2026 Model card
6 Qwen3.5 397B-A17B 89.8% Feb 2026 Model card
7 Qwen 3.6 Plus 89.8% Apr 2026 Model card
8 Qwen3.5-122B-A10B 88.4% Feb 2026 Model card

Number one over time

Lab claims count from the day the card came out, independent runs from the model’s release.

Google DeepMind
Lab claims Passed 85% in Nov 2025, by Gemini 3 Pro
Gemini 3 Pro 93.4%

The best score passed 85% in Nov 2025

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Gemini 3 Pro 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Gemini 3 Pro

Labs headline it less often now, last in Jun 2026

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

Google DeepMind
ByteDance Seed
Qwen
DateLaunch postScoreAs the post writes it
1 Jun 2026 Qwen3.7-Plus 90.3 Global PIQA
20 May 2026 Qwen3.7-Max 91.4 Global PIQA
2 Apr 2026 Qwen 3.6 Plus 89.8 Global PIQA
24 Feb 2026 Qwen3.5-122B-A10B 88.4 Global PIQA
16 Feb 2026 Qwen3.5 397B-A17B 89.8 Global PIQA
14 Feb 2026 Seed2.0 Pro 92.3 Global PIQA
17 Dec 2025 Gemini 3 Flash 92.8 Global PIQA
18 Nov 2025 Gemini 3 Pro 93.4 Global PIQA

One system card reports it

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
14 Feb 2026 Seed2.0 Pro model card 92.3 Global PIQA (Table 3) Capabilities

More in Multilingual

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  • WMT24++ In use English-to-55-language translation of WMT24 test data. Scored with automatic metrics such as MetricX or xCOMET. K-EXAONE 90.5%
  • MMLU-ProX In use MMLU-Pro translated into up to 29 languages with expert review. Multiple-choice accuracy per language. Qwen3.7-Max 87%
  • CLIcK In use Models answer 1,995 multiple-choice questions on Korean language and culture. Questions come from official Korean exams and textbooks in eleven categories. Solar Open 2 90.7%
  • Global MMLU Lite 3.0 In use Models answer 400 human-translated MMLU questions per language in 23 languages. Version 3.0 adds Czech, Hungarian, Oriya, Slovak and Tajik and updates Italian. Accuracy. Inkling 88.7%
  • MMMB In use Models answer multiple-choice questions about images in six languages across 15 categories. The set has about 12,000 questions. LFM2.5-VL-3B 83%