# Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

arXiv: https://arxiv.org/abs/2510.24081 · HTML: https://mlsanity.com/paper/2510.24081/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning.
- Builds on 27 of its 109 references that are in the map.
- First posted on arXiv 28 Oct 2025.

## Placed in

- LLM reasoning / [Reasoning benchmarks and evaluation](https://mlsanity.com/lr/reasoning-benchmarks-and-evaluation/)

## Builds on (most cited first, 27 of 27)

- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [Qwen2.5 Technical Report](https://mlsanity.com/paper/2412.15115/) (2024)
- [Gemma 2: Improving Open Language Models at a Practical Size](https://mlsanity.com/paper/2408.00118/) (2024)
- [BLOOM: A 176B-Parameter Open-Access Multilingual Language Model](https://mlsanity.com/paper/2211.05100/) (2022)
- [Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone](https://mlsanity.com/paper/2404.14219/) (2024)
- [Gemma 3 Technical Report](https://mlsanity.com/paper/2503.19786/) (2025)
- [Mixtral of Experts](https://mlsanity.com/paper/2401.04088/) (2024)
- [gpt-oss-120b & gpt-oss-20b Model Card](https://mlsanity.com/paper/2508.10925/) (2025)
- [Phi-4 Technical Report](https://mlsanity.com/paper/2412.08905/) (2024)
- [The Falcon Series of Open Language Models](https://mlsanity.com/paper/2311.16867/) (2023)
- [Few-shot Learning with Multilingual Language Models](https://mlsanity.com/paper/2112.10668/) (2021)
- [Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier](https://mlsanity.com/paper/2412.04261/) (2024)
- [MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation](https://mlsanity.com/paper/2503.10497/) (2025)
- [Command A: An Enterprise-Ready Large Language Model](https://mlsanity.com/paper/2504.00698/) (2025)
- [The Bitter Lesson Learned from 2,000+ Multilingual Benchmarks](https://mlsanity.com/paper/2504.15521/) (2025)
- [Towards Multilingual LLM Evaluation for European Languages](https://mlsanity.com/paper/2410.08928/) (2024)
- [MultiLoKo: a multilingual local knowledge benchmark for LLMs spanning 31 languages](https://mlsanity.com/paper/2504.10356/) (2025)
- [Kanana: Compute-efficient Bilingual Language Models](https://mlsanity.com/paper/2502.18934/) (2025)
- [HyperCLOVA X Technical Report](https://mlsanity.com/paper/2404.01954/) (2024)
- [InkubaLM: A small language model for low-resource African languages](https://mlsanity.com/paper/2408.17024/) (2024)
- [Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs](https://mlsanity.com/paper/2502.12982/) (2025)
- [EuroLLM-9B: Technical Report](https://mlsanity.com/paper/2506.04079/) (2025)
- [Babel: Open Multilingual Large Language Models Serving Over 90% of Global Speakers](https://mlsanity.com/paper/2503.00865/) (2025)
- [Tucano: Advancing Neural Text Generation for Portuguese](https://mlsanity.com/paper/2411.07854/) (2024)
- [Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://mlsanity.com/paper/2509.14233/) (2025)
- [VinaLLaMA: LLaMA-based Vietnamese Foundation Model](https://mlsanity.com/paper/2312.11011/) (2023)
- [Komodo: A Linguistic Expedition into Indonesia's Regional Languages](https://mlsanity.com/paper/2403.09362/) (2024)

## Built on by (most cited first, 10 of 10)

- [Marco-MoE: Open Multilingual Mixture-of-Expert Language Models with Efficient Upcycling](https://mlsanity.com/paper/2604.25578/) (2026)
- [Think Multilingual, Not Harder: A Data-Efficient Framework for Teaching Reasoning Models to Code-Switch](https://mlsanity.com/paper/2604.15490/) (2026)
- [Rethinking the Multilingual Reasoning Gap with Layer Swap](https://mlsanity.com/paper/2605.26735/) (2026)
- [Maistros: A Greek Large Language Model Adapted Through Knowledge Distillation From Large Reasoning Models](https://mlsanity.com/paper/2605.01870/) (2026)
- [ADAGE: A Language-Agnostic Pipeline for Analogical Reasoning Evaluation](https://mlsanity.com/paper/2607.23058/) (2026)
- [Building Multilingual Bridges: Data Mixing as the Pillar of Generalization for In-Language Reasoning](https://mlsanity.com/paper/2609.10445/) (2026)
- [Data-Efficient Language Modeling: From Frontier Advancement to Principle-Guided Model Improvement](https://mlsanity.com/paper/2609.10702/) (2026)
- [GYROval: A Robust Benchmark for Cultural Value Orientation in Large Language Models](https://mlsanity.com/paper/2609.18384/) (2026)
- [Large-scale factor analysis shows machine intelligence is only partially interpretable](https://mlsanity.com/paper/2609.36515/) (2026)
- [Cross-Lingual Alignment for Decoder-Only Models using MoE Routers](https://mlsanity.com/paper/2610.01921/) (2026)

## Abstract (arXiv)

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.