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TranslateGemma

AI Platforms Open Source
This page covers a version or sub-product of Gemma 4. View Gemma 4 overview →

Lightweight open-source translation model Google released on 2026/9/15, trained from Gemini, supporting 55 languages and able to run offline; Google says its language technology now covers more than 300 languages reaching roughly 86% of the world population

TranslationOpen SourceMultilingualOfflineGemma
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Overview

TranslateGemma is a lightweight open-source translation model Google released on September 15, 2026, trained from Gemini, supporting 55 languages and able to run offline. It was announced alongside a batch of Google language technology results; Google says its language technology now covers more than 300 languages, reaching roughly 86% of the world's population.

Its role is to close a gap that large-model translation leaves open. General models translate well, but calls require a network connection, are billed by volume and involve sending data outside. A dedicated translation model can run on a local device, which suits documents that must stay confidential, unstable networks, or simply a wish to bring the cost of bulk translation down. The 55 languages cover the major ones, forming a division of labour with the 300-plus language reach that depends more on online services.

Within Google's open model line-up TranslateGemma sits under the Gemma family, sharing origins with general multimodal models such as Gemma 4 but aiming elsewhere: Gemma 4 handles general reasoning and multimodality, while TranslateGemma focuses on translation and tries to do that one job small and well.

Key Features

Use Cases

Pros

Pricing

Open source and free, with weights available for download. The running cost is local hardware usage, with no metered billing.

Summary

TranslateGemma is the lightweight open-source translation model Google released on September 15, 2026, trained from Gemini, supporting 55 languages and able to run offline. It pulls translation out of the networked large-model call and hands it to a dedicated small model that runs on a local device, which suits confidential documents, privacy-sensitive material and constrained networks. As a member of the Gemma family it shares origins with Gemma 4, so existing local deployment experience carries over directly.

Category
AI Platforms
Pricing
Open Source
Tags
Translation · Open Source · Multilingual
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