There are more than 2000 living languages in Africa, most of which have been bypassed by advances in language technology. Current leading LLMs exhibit strong performance on a number of the most common languages (e.g. Swahili or Yoruba), but prioritise support for the languages with the most speakers first, resulting in piecemeal ability across disparate languages. We contend that a regionally focussed approach is more efficient, and present a case study for Uganda, a country with high linguistic diversity. We describe the development of Sunflower 14B and 32B, a pair of models based on Qwen 3 with state of the art comprehension in the majority of all Ugandan languages. These models are open source and can be used to reduce language barriers in a number of important practical applications.
@article{arxiv.2510.07203,
title = {Sunflower: A New Approach To Expanding Coverage of African Languages in Large Language Models},
author = {Benjamin Akera and Evelyn Nafula Ouma and Gilbert Yiga and Patrick Walukagga and Phionah Natukunda and Trevor Saaka and Solomon Nsumba and Lilian Teddy Nabukeera and Joel Muhanguzi and Imran Sekalala and Nimpamya Janat Namara and Engineer Bainomugisha and Ernest Mwebaze and John Quinn},
journal= {arXiv preprint arXiv:2510.07203},
year = {2025}
}