Which of the three translation problems do you have?
Understanding something in another language is the commonest and the easiest. DeepL handles it better than anything else in this category, and the free tier covers it.
Producing something correct in another language is harder, and a raw machine translation is not enough — you need to know whether a phrase is idiomatic, formal enough, or used that way at all. That is what Linguee, PONS and Reverso are for: not translating your sentence but showing how the phrase appears in real bilingual texts, with conjugations, register and context.
Translating professionally at volume is a third problem entirely. Trados is a CAT tool built around translation memory: every segment you translate is stored, so the next time a similar sentence appears it is proposed automatically. For a translator working on a 200-page manual with repeated boilerplate, that is the difference between viable and not.
Buying across the split is the usual waste. A company buying Trados to translate its website once has bought a professional workshop for a single job; a translation agency using only DeepL is discarding the memory that makes the second project cheaper than the first.
Why is DeepL better on European languages, and by how much?
The difference is most visible in the languages where grammar carries meaning that word-order translation destroys. German compound nouns and separable verbs, French register and agreement, Dutch word order — these are where Google Translate produces something comprehensible and clearly machine-made, and DeepL produces something a native speaker might have written.
The practical test is register rather than accuracy. Both engines will get the meaning across; DeepL is far more likely to preserve whether the original was formal or casual, which is what makes the output usable in a business email without rewriting.
DeepL also offers a glossary, which is what turns it from a tool into infrastructure for a company: define that your product name is never translated and that a specific term always renders a specific way, and it holds across every document. For consistent terminology in a regulated or technical field, that is essential rather than convenient.
DeepL Write extends the same engine to improving text in one language rather than moving between two, which competes with Grammarly from a German company under GDPR.
What happens to the text you paste in?
This is the question almost nobody asks, and it should be the first one. People paste employment contracts, medical letters, legal correspondence and unreleased product documentation into translation boxes without considering that the text is being transmitted to a third party and possibly retained.
DeepL's paid plans commit to not retaining text after translation is complete, which is the specific clause a company needs before its staff put anything confidential through an API. The free tier does not carry the same commitment — a distinction worth communicating internally, because staff will use the free version otherwise.
ModernMT is Italian with an open-source foundation, which allows inspection of what the system does rather than trusting a description of it.
For a European organisation the jurisdiction argument is straightforward: DeepL, Linguee and PONS in Germany, Reverso in France and ModernMT in Italy all mean intra-EEA processing with no transfer analysis. That is a materially simpler position than sending contract text to a US-established service, and it is the reason many European legal and medical teams standardise on DeepL specifically.
What does translation memory actually save?
Money on the second project, and consistency across all of them. A translation memory stores every source segment with its approved translation, so when a similar sentence appears again — in the next version of the manual, the next contract from the same client, the next release notes — it is proposed rather than retranslated.
For repetitive technical content that is the entire economics of professional translation. A 200-page manual updated annually is perhaps 15% new text; without a memory it is 100% billable work every year. Trados has been building this since 1984 and is the industry standard for exactly this reason.
Terminology management is the companion feature: an agreed glossary ensures the same term renders the same way across a project and across translators, which matters enormously in regulated content where a wrong word is a compliance problem rather than a stylistic one.
Trados Studio runs on the desktop with the memory local, and Trados Go provides a browser-based CAT tool for working elsewhere. From about €155 per year it is aimed at professionals; for a company translating occasionally it is the wrong purchase.
How do you check whether a translation is actually right?
By looking at how the phrase is used rather than at what the engine produced, and this is where the reference tools earn their place.
Linguee searches a corpus of real bilingual documents — official EU texts, company websites, published translations — and shows how a phrase was actually rendered by human translators in context, with the source visible. That answers "is this how people say it" rather than "is this a valid translation", which is a different and more useful question.
PONS brings the authority of a dictionary publisher operating since 1978, with bilingual dictionaries across 36 languages, audio pronunciations and a vocabulary trainer — reference rather than a corpus, and correspondingly more reliable on the core meaning and less useful on idiom.
Reverso combines both approaches with Reverso Context showing real-world usage examples, plus conjugation tables, a grammar checker and a writing assistant. For a language learner or someone writing in a second language, that combination is more practical than a pure translator.
The workflow that works: DeepL to draft, Linguee or Reverso Context to verify the phrases you are unsure about, PONS for the word you do not know at all.
