XQuAD
Cross-lingual Question Answering Dataset - QA in 10+ languages.
Category
Multilingual
Score type
percent
Scale
100%
higher is better
Models tested
4
What is XQuAD?
XQuAD is a benchmark for performance in languages other than English. The official description says: "Cross-lingual Question Answering Dataset - QA in 10+ languages". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
XQuAD measures performance in languages other than english. In detail, it checks:
- understanding and answering in many different languages
- translation quality between language pairs
- keeping math and reasoning quality when the question is not in English
- treating low-resource languages fairly instead of defaulting to English
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Official methodology note: Cross-lingual Question Answering Dataset - QA in 10+ languages.
Frequently asked questions
What is the XQuAD benchmark?
XQuAD is a benchmark for performance in languages other than English. The official description says: 'Cross-lingual Question Answering Dataset - QA in 10+ languages'. Below we describe in simple words what benchmarks of this type generally examine.
What does XQuAD test?
XQuAD mainly measures performance in languages other than English. Concretely, it checks: understanding and answering in many different languages; translation quality between language pairs; keeping math and reasoning quality when the question is not in English.
How is the XQuAD score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get XQuAD data and scores?
The official source is https://arxiv.org/abs/1910.11856. The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/xquad/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Official benchmark page / paper
The benchmark maintainer's website, paper or leaderboard
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 4 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Gemma 3 27B PT
Google DeepMind
|
76.8%
|
27.02.2025 | Report | Verified |
| 2 |
Gemma 3 12B PT
Google DeepMind
|
74.5%
|
27.02.2025 | Report | Verified |
| 3 |
Gemma 3 4B PT
Google DeepMind
|
68%
|
27.02.2025 | Report | Verified |
| 4 |
Gemma 3 1B PT
Google DeepMind
|
43.9%
|
27.02.2025 | Report | Verified |