Meta, in collaboration with Data Science Africa, has launched the Llama Impact Grant to support startups and researchers across Sub-Saharan Africa.
This initiative is designed to fund innovative projects using Meta’s open-source Llama AI models, which address the region’s unique challenges.
The grant, part of Meta’s global Llama Impact Grants programme, offers a $20,000 prize to the best proposal demonstrating a compelling use of Llama technology in solving real-world issues in Africa.
Startups and researchers are invited to submit their proposals through the online application portal, with a deadline of April 18, 2025.
The project’s potential impact, feasibility, ethical considerations, and team expertise will be evaluated.
Meta’s Llama models, including the widely used Llama 3.3, have already played a crucial role in developing AI solutions for sectors such as agriculture, healthcare, and education, particularly in underserved communities.
Meta’s Llama models are open-source, enabling organisations to use and adapt them freely, bypassing the restrictions often associated with commercial AI tools.
The programme aims to empower innovators to develop scalable AI solutions that drive sustainable growth across Africa.
Meta’s Public Policy Director for Sub-Saharan Africa, Balkissa Ide Siddo, emphasised that the programme aims to foster impactful AI-driven solutions that address Africa’s pressing social and economic issues.
The Llama Impact Grant is part of Meta’s broader commitment to advancing AI technology and supporting the growth of the African tech ecosystem.
Since its launch in October 2023, the programme has attracted over 800 applications from over 90 countries.
Notable projects from the global programme include a multilingual chatbot providing agricultural advice in Sub-Saharan Africa and a digital health tool supporting maternal health in Kenya and Ghana.
This grant presents a significant opportunity for African innovators to contribute to the global AI landscape while solving critical challenges within their communities.

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