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AfroLM vs Lugha-Llama

A verified, side-by-side comparison. Both records are status-checked by Wycord, so you are comparing what each actually offers today, not a stale listing.

AfroLMLugha-Llama
Category
AI Resources
AI Resources
Type
LLM
LLM
Country
🌍 Pan-African
🌍 Pan-African
Docs status
Docs live
Docs live
Licensing
Pricing
Free / open weights
Open weights (Llama 3.1 community license)
Verified
Verified
Unverified
Last verified
10 Oct 2026
10 Oct 2026
Tags
nlp, african-languages, masked-language-model, active-learning, data-efficient
african-languages, swahili, low-resource, wura-corpus, llama-3.1
Links
Website Docs GitHub
Website Docs
Summary
A multilingual masked language model pretrained from scratch on 23 African languages using a self-active learning framework, outperforming AfriBERTa, mBERT and XLMR-base on NER and sentiment tasks. Created by Bonaventure Dossou and collaborators, published at SustaiNLP/EMNLP 2022.
Lugha-Llama is a Llama-3.1-8B model continually pretrained on the WURA African-language corpus to lift performance on low-resource African languages. It ships in three variants (wura, wura_edu, wura_math) and reaches leading results among similarly sized models on the IrokoBench and AfriQA African-language benchmarks. It was built by researchers at Princeton University.

AfroLM vs Lugha-Llama at a glance

AfroLM and Lugha-Llama are both listed under LLM in Wycord's AI Resources index.

Both are based in Pan-African.

Both currently show the status "Docs live".

On access, both are marked "No approval needed".

Over the last 30 days Wycord's probes measured 100% uptime for AfroLM (36 checks) and 100% for Lugha-Llama (36 checks).

Average response time on live probes was 338 ms for AfroLM and 152 ms for Lugha-Llama.

Uptime and latency come from Wycord's own probes of each resource's website, documentation and repository, run every six hours.

How they differ

  • Pricing: AfroLM, Free / open weights; Lugha-Llama, Open weights (Llama 3.1 community license).
  • Verification: AfroLM, Verified; Lugha-Llama, Unverified.
  • Average latency: AfroLM, 338 ms; Lugha-Llama, 152 ms.

Topics

Both are tagged: african-languages.

Only AfroLM: nlp, masked-language-model, active-learning, data-efficient.

Only Lugha-Llama: swahili, low-resource, wura-corpus, llama-3.1.

Common questions

Which has better uptime, AfroLM or Lugha-Llama?
They are level at 100% over the last 30 days.
Do AfroLM or Lugha-Llama need approval before use?
Both are marked "No approval needed".
Is the documentation for AfroLM and Lugha-Llama working?
Both show "Docs live" at the last check.
Where are AfroLM and Lugha-Llama based?
Both are based in Pan-African.

More comparisons

Full details: AfroLMFull details: Lugha-Llama