A new benchmark called Nsanku has been developed to evaluate the zero-shot translation capabilities of 19 large language models across 43 Ghanaian languages. The study found that while Gemini 2.5 Flash performed best among proprietary models, and Kimi-K2-Instruct-0905 led open-weight models, no LLM achieved both high performance and high consistency. This indicates that current models are not yet reliable for large-scale translation of these low-resource languages. AI
Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →
IMPACT Highlights the significant gap in LLM translation capabilities for low-resource African languages, necessitating further research and development.
RANK_REASON This is a research paper presenting a new benchmark for evaluating LLM translation performance on low-resource languages.