[pil0u]

As an individual, I still go to DeepL while actively using LLMs. I think the main reason is that the translations are very good, with alternatives in one click, without having to type "translate xxxx into yyyy".

My previous company ran tests on translations, for their specific use case, DeepL API was overall better that OpenAI or Claude.

[tkgally]

That’s interesting. In my tests of translation of formal speeches from Japanese to English, the latest versions of ChatGPT, Claude, and Gemini were all better than DeepL. While DeepL’s output wasn’t bad, the fact that the LLMs could be prompted in detail about the purpose of the translation and had sufficient context windows to maintain pronoun reference and other forms of cohesion made a significant difference.

[pil0u]

You could add context to DeepL as well as easily, with the "context" parameter of the translation.

[tkgally]

Thanks for that clarification. I don't think that feature was available when I did my comparison tests a few months ago.

[Rinzler89]

Exactly this. LLMs are more context aware than DeepL.

[Rinzler89]

Are you paying for DeepL?

[pil0u]

Not personally, my company was. Why?

[Rinzler89]

Because my question was how was DeepL planning to survive monetarily? It doesn't help if people are praising it but if nobody's paying for it. Google, Microsoft, et-al can subsidize their AI offerings longer than DeepL can stay solvent.