Multilingual Benchmark

ECLeKTic

ECLeKTic - multilingual knowledge translation benchmark.

Category

Multilingual

Score type

percent

Scale

100%

higher is better

Models tested

4

What is ECLeKTic?

ECLeKTIC is a multilingual knowledge benchmark: the same obscure knowledge items are asked in twelve languages. The result shows how unequally knowledge is distributed within a model across languages — the gap between best and worst language is telling.

What does it test?

ECLeKTic measures performance in languages other than english. In detail, it checks:

  • closed-book knowledge in twelve different languages
  • equality of knowledge across languages
  • cultural and linguistic long-tail knowledge
  • no silent fallback 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.

Frequently asked questions

What is the ECLeKTic benchmark?

ECLeKTIC is a multilingual knowledge benchmark: the same obscure knowledge items are asked in twelve languages. The result shows how unequally knowledge is distributed within a model across languages — the gap between best and worst language is telling.

What does ECLeKTic test?

ECLeKTic mainly measures performance in languages other than English. Concretely, it checks: closed-book knowledge in twelve different languages; equality of knowledge across languages; cultural and linguistic long-tail knowledge.

How is the ECLeKTic 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 ECLeKTic data and scores?

The official source is https://arxiv.org/abs/2502.21228. 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/eclektic/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 4 models tested

Reset
# Model Score Date Source Verified
1 Gemma 3 27B PT
Google DeepMind
24.4%
27.02.2025 Report Verified
2 Gemma 3 12B PT
Google DeepMind
17.2%
27.02.2025 Report Verified
3 Gemma 3 4B PT
Google DeepMind
11%
27.02.2025 Report Verified
4 Gemma 3 1B PT
Google DeepMind
4.69%
27.02.2025 Report Verified

What now?

You've seen how models score on ECLeKTic — here's what to do next.