Africa's AI moment has arrived — this 1.5B model built from scratch for 12 African languages beats Google, Meta, and Alibaba while being 8x smaller
Africa built its own language model from scratch
by https://www.techradar.com/author/efosa-udinmwen · TechRadarNews By Efosa Udinmwen Published 23 September 2026 3 min read
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- MORENA beat 26 tested models despite having only 1.5 billion parameters
- The model from Vambo AI was built specifically around African languages from scratch
- MORENA uses fewer tokens to represent African text than major rivals
Vambo AI has released MORENA, a 1.5B parameter language model covering 12 languages spoken across Africa, plus English, French and code.
The developers say it beats models from Google, Meta, Alibaba and HuggingFace on African language modelling and translation while being up to 8x smaller.
On a key benchmark, this LLM scored 1.408 bpb — the best of 26 models tested — beating its closest rival, which carried over five times as many parameters yet still scored only 1.423 bpb.
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Training without a borrowed foundation
The model covers Nigerian Pidgin, Igbo, Yoruba, Hausa, Kiswahili, ChiShona, isiZulu, isiXhosa, Kinyarwanda, Setswana, Afrikaans, and isiNdebele.
Most projects serving these languages continue training an existing Llama variant, which forces them to keep a vocabulary meant for English and programming text.
Vambo AI instead fixed the tokenizer, the data mixture, and the language list before training began, after comparing several vocabulary sizes for cost and efficiency.
MORENA's vocabulary encodes African text with 1.39 times fewer tokens than Gemma 3 and 1.53 times fewer than Llama 3.2 on identical passages.
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