AI Translator
Translate text between English and 10 languages. Each pair is a small Helsinki-NLP model that runs in your browser.
Why a Translator That Runs in Your Browser
Online translators have an obvious privacy problem: every sentence you translate goes through someone else's server. For confidential documents, contracts, private correspondence, or anything else you would not publish, that round-trip is a real concern. This tool uses Helsinki-NLP's opus-mt models, ported to ONNX for browser execution by Xenova. Each language pair is its own small model — typically 30-45 MB — and downloads only when you actually pick that pair. So translating an English document to Spanish downloads about 40 MB once; switching to French downloads another 40 MB. Nothing more. The opus-mt models are released under the Apache 2.0 license, which permits commercial use with no attribution requirement (we credit Helsinki-NLP anyway because the work deserves it). Coverage at launch is 10 languages, both directions: Spanish, French, German, Italian, Portuguese, Russian, Chinese (Simplified), Japanese, Arabic, and Dutch. More pairs may be added in future batches based on demand. Quality on common pairs (en-es, en-fr, en-de) is strong; smaller pairs (en-ar, en-jap) are usable but rougher.
How the Translator Works
Pick a source language and a target language from the two dropdowns. The tool checks whether the matching opus-mt model is already cached in your browser; if not, it downloads it (about 30-45 MB, one-time per pair). Once loaded, paste your text and click Translate. The model processes the text sentence-by-sentence and produces a translation in the output panel with a copy button. For text longer than about 200 words per pass, the tool automatically chunks at sentence boundaries and stitches the chunks back together. Unlike massive multilingual models, opus-mt is bilingual — one model per direction. That makes individual downloads small and translations fast (typically 1-3 seconds per paragraph after the model loads), but it means each language pair is a separate download. The English source models follow the naming pattern Xenova/opus-mt-en-{xx}; the English target models follow Xenova/opus-mt-{xx}-en. The tool loads the appropriate one based on the source/target you pick. Currently the tool only supports English as the pivot — translating between two non-English languages requires using English as an intermediate step (which can compound errors).
Frequently Asked Questions
Which translation model family is used?+
The Helsinki-NLP opus-mt family of models, ported to ONNX for browser execution by Xenova. Each language pair is its own model — for example, Xenova/opus-mt-en-es for English-to-Spanish, Xenova/opus-mt-es-en for the reverse. Each pair is approximately 30-45 MB compressed.
Which languages are supported at launch?+
Ten languages, both directions to and from English: Spanish, French, German, Italian, Portuguese, Russian, Chinese (Simplified), Japanese, Arabic, and Dutch. That is 20 individual models total, downloaded on demand only when you actually pick a pair. We may add more pairs in future batches based on demand.
Why not one giant model that covers everything?+
The big multilingual models that cover hundreds of languages in one model (NLLB-200, M2M-100) are released under non-commercial licenses, which our site cannot use. The Helsinki-NLP opus-mt models are Apache 2.0 and commercial-friendly. Trade-off: one model per pair instead of one model for everything. Upside: each download is much smaller, so you only fetch the languages you actually use.
Is the text I translate sent to any server?+
No. After the model for your chosen pair downloads on first use, every translation runs entirely in your browser. The text you input never leaves your machine and is not sent to any server, including ours.
How good are the translations compared to Google Translate or DeepL?+
For common pairs (English-Spanish, English-French, English-German) the quality is solid for general prose — accurate, fluent, occasionally awkward on idioms. For smaller pairs (English-Arabic, English-Japanese) the quality is usable but rougher. Google Translate and DeepL are noticeably better for nuanced or domain-specific text. The trade-off is that this tool sends nothing to a server.
Can I translate between two non-English languages, like Spanish to French?+
Not directly. The opus-mt models we use are English-pivot — translating Spanish to French requires translating Spanish to English first, then English to French. The tool can do this in two steps; quality suffers from compounding errors. For direct non-English pairs, hosted services are currently a better fit.
Are there text length limits on a single translation?+
The model processes about 512 tokens per pass (roughly 400 words). For longer inputs the tool chunks at sentence boundaries and stitches the results. There is no hard upper limit, but very long inputs take proportionally longer.
Why are the model files licensed Apache 2.0 rather than something else?+
The Helsinki-NLP team trained their models on OPUS, a large open corpus of translation data, and released the models under Apache 2.0 — meaning commercial use is permitted with no attribution requirement (though we credit Helsinki-NLP on this page anyway). The alternative multilingual models (Meta's NLLB-200, Facebook's M2M-100) are released under CC-BY-NC, which forbids commercial use, so they were not options for this tool.
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