I’m using it through Kagi which doesn’t use Deepseek’s official API [1]. That limitation from the docs seems to be everywhere.

In practice I don’t think anyone can economically host the whole model plus the kv cache for the entire context size of 128k (and I’m skeptical of Deepseek’s claims now anyway).

Edit: a Kagi team member just said on Discord that they’ll be increasing max tokens next release

[1] https://help.kagi.com/kagi/ai/llms-privacy.html

But you should also be very wary of these kind of anecdotes, and this thread highlights exactly why. That commenter says in another comment (https://news.ycombinator.com/item?id=42866350) that the token limitation that he is complaining about has actually nothing to do with DeepSeek's model or their API, but is a consequence of an artificial limit that Kagi imposes. In other words, his conclusion about DeepSeek is completely unwarranted.