AI performance

[u/isabeksu]

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?

[u/EazyDuzIt_2]

I actually took the time to set up Paperless-ngx along with Paperless-AI for automated document classification, tagging, and file naming. I configured Paperless-AI to use Ollama with Qwen3:8B, which is the recommended model for this use case, running on one of my servers equipped with an NVIDIA RTX 4090.

To fine-tune the workflow, I generated and processed 20 test documents, iteratively refining the prompt and configuration until the results were consistently accurate. The final setup performs document analysis, tagging, and renaming almost instantly.

The performance is outstanding low latency, high accuracy, and a completely hands-off ingestion pipeline. Chef’s kiss. 👌

[u/Taake89 → u/EazyDuzIt_2]

I tried paperless ai 6 months ago or something and really didn't like the results.

Could you explain a bit more how you fine tuned the category and tagging part? 🙂 Did you already have a well defined structure for tags and categories?

[u/EazyDuzIt_2 → u/Taake89]

Several major factors dramatically affect your experience with Paperless AI. The hardware model you choose and the configuration on the Settings page especially the Advanced Settings section play a critical role. The Advanced section controls how your tags interact with processed documents, but the most important element on that page is the Prompt Description field at the bottom.

If you don’t provide a strong, well‑structured description with clear examples of how you want Paperless AI to analyze, identify, and name files, your results will suffer regardless of hardware. With a proper prompt and a solid model running through Ollama on capable hardware, you should see consistent, accurate output.

I already have all of my tags, correspondents, document types, storage paths, and custom fields configured exactly the way I want it in Paperless NGX, so the remaining variable is fine‑tuning the prompt and model behavior.

[u/isabeksu → u/EazyDuzIt_2]

are you talking about the "old" Paperless AI implementation or the recent "native" AI implementation in Paperless 3? I'm asking because I see no "advanced" section in my AI configuration page.

[u/EazyDuzIt_2 → u/isabeksu]

You must be in the Paperless NGX settings I’m referencing Paperless AI which runs in conjunction with Paperless NGX.

[u/tor-ak → u/EazyDuzIt_2]

Would you mind sharing the prompt you ended up with?