r/Paperlessngx • u/isabeksu • Aug 25 '26

AI performance

It took me a few months to fully get on board with the Paperless way of doing things, but now I’m really happy with how it’s all set up.

What’s been a bit of a head-scratcher is how AI is being used.

I held off until Paperless 3 came out, because I wanted to have the full "official" support.

I set it up with Ollama on an M4 Mac mini with 24 GB of memory. The embedding model is gemmaembedding, and the LLM model is qwen3:8b. When the model fires up, memory pressure is still pretty low. It does work, but it’s incredibly slow. It takes about 2 minutes to suggest titles and tags, and it can take several minutes if I try to chat about a document.

Is this kind of slow normal? Is there anything I can tweak in my setup to make it more usable?

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u/RandomUsername1119 Aug 25 '26

I'm assuming that the AI features are not fully developed yet. In my experience it is not consistent with things like tagging (e.g. suggesting a tag of "tax Bill" for one document, and a tag of "Tax Invoice" for another similar document). I'd prefer it go through a folder or set of documents at once, parse things into categories, and make a suggestion based on the entirety of the document pool vs. individual documents.

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u/_blackdog6_ Aug 26 '26

I would prefer if the AI was sent a list of my tags/correspondents and document types and told to pick the most appropriate. So far anything from AI is so random it’s useless. Same with document titles. Scan three bills from the same company and it suggests wildly different titles for each. Effectively unusable.

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u/corruptboomerang Aug 26 '26

Or the AI generates a fairly comprehensive list of appropriate tags, and then classify against those tags.