The State of Large Language Models for African Languages: Progress and Challenges

Hussen, Kedir Yassin, Sewunetie, Walelign Tewabe, Ayele, Abinew Ali, Imam, Sukairaj Hafiz, Muhammad, Shamsuddeen Hassan, Yimam, Seid Muhie

arXiv.org Artificial Intelligence 

The rapid progress of Large Language Models (LLMs) has transformed the field of Natural Language Processing (NLP). However, these advancements have primarily concentrated on high-resource languages, leaving many low-resource languages, particularly African languages, largely overlooked. Africa has over 2,000 languages [Ethnologue, 2025], the majority of which face significant challenges such as a lack of data, limited computational resources, insufficient NLP tools, and the absence of standardized benchmarks. This study presents a three-stage review to evaluate LLMs' current status, challenges, and prospects for African languages. The first stage investigates both commercial and open-source LLMs models with more than 7 billion parameters regarding their support for African languages [Wang et al., 2024]. The second stage examines foundational multilingual models that have significantly influenced NLP research and development.

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