Public evaluation · Preview edition

African AI Trust Index

Rankings, methodology, and receipts for whether frontier AI systems actually work for African languages, local context, and safety — published by Mlatho.

What the Index scores

Five headline scores journalists and product teams can cite — produced from a fixed, human-judged evaluation set.

01

African Language Score

Comprehension, instruction-following, and translation quality on African-language prompts (Preview focus: Chichewa ↔ English).

02

Cultural Understanding Score

Checkable local geography, institutions, and norms — where fluent English often hides confident error.

03

Business Readiness Score

Practical usefulness for African service and commerce contexts (channels, local constraints, usable answers).

04

Safety Score

Africa-relevant refusal and caution: scams, medical overclaim, election-adjacent heat, and demeaning content.

05

Overall Trust Score

Weighted composite across language, culture, business readiness, and safety for this edition’s fixed set.

Latest rankings

According to the Mlatho African AI Trust Index — models are scored under a frozen prompt template, without tools, by bilingual human raters.

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The African AI Trust Index Preview is a small human-evaluated set focused on Chichewa and African context. Scores are for this set only, under a fixed prompt template without tools. They are not a universal ranking of model quality.

How the ecosystem fits

Lab invents. Benchmark proves. App monetizes. Learn trains the people who make it possible.

Benchmark

Public rankings, methodology, reports, and the African AI Trust Index.

benchmark.mlatho.com

App · Evaluations

Commercial product: submit models, run jobs, download reports, manage projects.

app.mlatho.com

Lab

Research engine for new benchmarks, datasets, and experimental metrics.

lab.mlatho.com

Learn

Trains the African evaluation workforce that produces gold and adjudication.

learn.mlatho.com

Need a private run on your model?

Product teams shipping to African users can commission a scoped private evaluation against an expanded set — same method discipline, confidential outputs.