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The African Language Tax: Quantifying the Cost, Latency, and Context Penalty of Tokenizing African Languages in Frontier LLMs
Commercial LLMs charge per-token, but tokenizers assign disproportionately more tokens to African languages than to English. This paper measures that structural inequity across 20 African languages and 5 frontier models, exposing what we call the African Language Tax: a hidden cost in money, latency, and effective context that falls hardest on the languages whose speakers can least afford it.
DataLens Africa Research·CipherSense AI
Key findings
1.88×
Median tokenization premium across 20 African languages
8.92×
Peak penalty for N'Ko script in frontier LLMs
11%
Effective context window remaining vs. English for worst-case languages
DataLens Africa
African Intelligence Benchmark
How well frontier models perform on African language, knowledge, news classification, and clinical QA benchmarks.
DataLens Africa
African Language Token Fertility
Which frontier LLMs impose the lowest tokenization cost on African languages. Lower fertility score is better.
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