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IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models

Paper · 2025 · David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime et al.

Summary

Large language models are usually tested in English and a few other well-resourced languages. When African languages are tested at all, it is mostly on simple classification, so we know little about how well models reason or recall knowledge in them. The authors built IrokoBench to fill this gap. Professional translators rendered subsets of three established English benchmarks into 17 African languages from West, East, Southern and Central Africa. The languages come from the Niger-Congo, Afro-Asiatic and Mande families. The resulting sets are AfriXNLI (inference), AfriMGSM (grade-school math) and AfriMMLU (multiple-choice knowledge QA).

The authors used these sets to test 10 open and six proprietary LLMs. They compared three settings: zero-shot, few-shot, and translate-test, in which the test set is first machine-translated into English. Scores fell sharply in every African language compared with English and French. Closed models clearly beat open ones. Translating inputs into English helped large English-centric models. The work offers a harder and more trustworthy way to measure, and later improve, LLM support for African languages.

Key points

  • Scale of the performance drop: African languages trailed high-resource languages by about 45% on average across all models.
    • Swahili did best among the African languages.
    • Ewe, Lingala, Luganda, Twi and Wolof did worst. Each has under 50 million characters of web data.
  • Open vs. closed models: The strongest open model, Gemma 2 27B, reached only about 63% of GPT-4o's performance.
  • Task difficulty: AfriMGSM was the hardest task, followed by AfriMMLU and then AfriXNLI.
  • Fine-tuned encoder vs. prompting: For NLI, a smaller Africa-centric encoder, AfroXLMR-76L, outperformed LLM prompting on average. It was fine-tuned on about 400k English examples and then applied directly to the other languages.
  • Release: Each AfriXNLI language has 450 dev and 600 test items. The benchmark is available on GitHub and HuggingFace under CC BY-SA 4.0.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🏢MicrosoftRedmond · United States240 works · 123,537 citations🎓Princeton UniversityPrinceton · United States61 works · 36,471 citations🎓Saarland UniversitySaarbrücken · Germany102 works · 17,447 citations🎓University College LondonLondon · United Kingdom59 works · 16,463 citations🎓McGill UniversityMontreal · Canada51 works · 10,476 citations🎓Imperial College LondonLondon · United Kingdom24 works · 8,272 citations🔬Canadian Institute for Advanced ResearchToronto · Canada17 works · 16,274 citations🎓Ontario Tech UniversityOshawa · Canada4 works · 1,490 citations🎓Makerere UniversityKampala · Uganda6 works · 885 citations🎓Haramaya UniversityDire Dawa · Ethiopia2 works · 150 citations

📚 Shelves 4 Computer Science · 9,086 works Artificial Intelligence · 8,889 works Arts and Humanities · 9,296 works Language and Linguistics · 9,206 works

🧭 Topics 2 Language models & pretraining · 1,343 works Evaluation & benchmarks · 685 works

Cite

Cite as David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, Jian Yun Zhuang, Jesujoba Oluwadara Alabi, Xuanli He, Millicent Ochieng, Sara Hooker, Andiswa Bukula, En-Shiun Annie Lee, Chiamaka Ijeoma Chukwuneke, Happy Buzaaba, Blessing Kudzaishe Sibanda, Godson Koffi Kalipe, Jonathan Mukiibi, Salomon Kabongo Kabenamualu, Foutse Yuehgoh, Mmasibidi Setaka, Lolwethu Ndolela, Nkiruka Odu, Rooweither Mabuya, Salomey Osei, Shamsuddeen Hassan Muhammad, Sokhar Samb, Tadesse Kebede Guge, Tombekai Vangoni Sherman and Pontus Stenetorp. 2025. IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2025.naacl-long.139

@inproceedings{adelani2025irokobench,
  title = {{IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models}},
  author = {David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, Jian Yun Zhuang, Jesujoba Oluwadara Alabi, Xuanli He, Millicent Ochieng, Sara Hooker, Andiswa Bukula, En-Shiun Annie Lee, Chiamaka Ijeoma Chukwuneke, Happy Buzaaba, Blessing Kudzaishe Sibanda, Godson Koffi Kalipe, Jonathan Mukiibi, Salomon Kabongo Kabenamualu, Foutse Yuehgoh, Mmasibidi Setaka, Lolwethu Ndolela, Nkiruka Odu, Rooweither Mabuya, Salomey Osei, Shamsuddeen Hassan Muhammad, Sokhar Samb, Tadesse Kebede Guge, Tombekai Vangoni Sherman and Pontus Stenetorp},
  booktitle = {Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)},
  year = {2025},
  doi = {10.18653/v1/2025.naacl-long.139},
  url = {https://doi.org/10.18653/v1/2025.naacl-long.139}
}

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