Tether AI Research has released three open-source machine translation models: QVAC TranslatePsy-AfriSLM, QVAC TranslatePsy-AfriNano, and QVAC TranslatePsy-EuroNano. They cover 19 African languages, 8 African languages, and 9 European languages, respectively, and can run locally on phones and laptops. No internet connection is required, so user data stays on the device. The 800-million-parameter AfriSLM beat Qwen3.5-122B-A10B, TranslateGemma-27B, and NLLB-3.3B on the FLORES-200, BOUQuET, and SMOL benchmarks. EuroNano handles 90 translation directions between 9 European languages. Its smallest deployment requires only 36MB of storage, roughly 94 percent less than Firefox's comparable offline translation configuration. AfriSLM is now available on Hugging Face, and the related paper has been accepted at EMNLP 2026.
Tether AI Research, the artificial intelligence unit of Tether, has introduced three open-source translation models — QVAC TranslatePsy-AfriSLM, QVAC TranslatePsy-AfriNano and QVAC TranslatePsy-EuroNano. According to Tether News, the models support 19 African languages, 8 African languages and 9 European languages, respectively. Designed to run directly on mobile phones and laptops, they perform translation without an internet connection. This on-device setup keeps user data within the device rather than sending it elsewhere.
On benchmarks, the 800-million-parameter TranslatePsy-AfriSLM outscored Qwen3.5-122B-A10B, TranslateGemma-27B and NLLB-3.3B on FLORES-200, BOUQuET and SMOL. The European-focused model, TranslatePsy-EuroNano, supports 90 translation directions among 9 European languages. Its smallest deployment version takes up just 36MB of storage — around 94% less than an equivalent Firefox offline translation configuration.
TranslatePsy-AfriSLM can now be downloaded from Hugging Face. Research tied to the models has been accepted at EMNLP 2026.
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