Native desktop app for better performance

In short:

I experience severe performance issues/lags when chats exceed a certain length, making the app painfully slow or impossible to use at that point. If this problem is shared by others and due to limitations of a PWA-style app, I would strongly recommend moving towards a native desktop (macOS) app.

Problem:

Unlike a similar post, I do not experience the problem as one of the number of chats rather than of chat length:

As soon as a chat’s context exceeds ~20.000-30.000 Tokens and this particular chat is opened, every new action (clicking on this chat, scrolling within the chat, formulating a new question, querying an answer) will cause a ~10-20 second delay/freeze of the app.

Unlike that other post, too, this is not accompanied by a huge CPU or memory usage (percentage-wise) of the app.

Context:

Your support bot attributes this to limitations of both the browser / the PWA using the browser’s local storage (IndexedDB), which I think is convincing. However, because I see no other complaints like this in this forum, I will share some additional context information to rule out other causes:

  • Account: Typing Mind Premium Plan; Web application, locally stored data (no cloud).

  • App: Typing Mind PWA operating on Safari 26.5

  • System: Mac OS Sequoia on a 3,2 GHz 6-Core Intel Core i7 (outdated, but usually not a problem; see also low CPU and memory usage)

  • Internet: 300Mbit/s Download and 150Mbit/s Upload

Closing comment:

I really enjoy Typing Mind’s idea, UI, and possibilities. It is simply that bumper that makes the application so hard to use in the long term. I would be delighted to have a smooth performance without constantly splitting up chats (losing their context, too) or switching to the cloud – be it through a native desktop application or another workaround. Thank you!

Please authenticate to join the conversation.

Upvoters
Status

Open

Board
💡

Feature Request

Date

3 days ago

Subscribe to post

Get notified by email when there are changes.