AI Translator handles text translation, text polishing, and image translation across 20 languages. You can run multiple AI models side by side and compare their output, which is most useful when wording precision matters — legal text, marketing copy, technical documentation. Single text submissions are capped at 50,000 characters.
When running multiple models side by side actually helps
Different models handle the same sentence with noticeably different phrasing, sentence structure, and term choices. For routine content — emails, summaries, short announcements — one model is usually enough. Running two or three models in parallel pays off for passages where a single awkward phrase would matter: contracts, product descriptions, medical instructions. Combine multi-model output with back-translation to decide which result is closest to the original meaning.
Back-translation: what it tells you and what it does not
Enabling back-translation re-translates the output back into the source language so you can compare it against the original. When the back-translated text is close to the original, semantic content was usually preserved. The back-translation will never be identical to the original — two translation passes both introduce natural language variation. Use it as a rough semantic check, not as proof of correctness. Back-translation is only available in text translation mode.
Glossary: when it is worth setting up
A glossary forces specific term-to-term mappings across the whole translation. It pays off when:
- A brand name must never be translated (or must always use a specific local form)
- A technical abbreviation has an agreed translation in your organization
- A legal term must match the wording in another document
Each glossary entry has source term, target term, and an optional context note. The context note is worth filling in when a word is ambiguous — for example, "here model means business model, not machine learning model" — because the model will use it to resolve ambiguous cases.
Image translation: when recognition fails
Image translation identifies text in an image and translates it. The following conditions tend to cause recognition errors:
Good recognition conditions
- Printed typefaces, clear font rendering
- Dark text on light background
- Straight-on photo, no perspective distortion
- High contrast between text and background
Poor recognition conditions
- Handwriting or artistic lettering
- Curved, rotated, or shadowed text
- Text color close to background color
- Low-resolution source image
Image translation consumes more credits than text translation. If recognition is inaccurate, copy the extracted text manually and switch to text translation mode for a more controlled result.
Choosing a translation style
Style affects tone and vocabulary, not meaning. Technical style prioritizes industry-standard terms and avoids decorative phrasing. Formal style suits official documents and academic abstracts. Business style fits emails and commercial reports. Casual style approximates natural spoken language. Creative style gives the model more rewriting latitude and works well for marketing copy.