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For a non-technical audience, it's hard to grasp the value of open models. Or should we say private models?
The best way of demonstrating value is to start with a very practical use case. That's what we presented on one of our latest demos. Extracting structured information from invoices. That's a problem a lot of companies have - right?
For this quick demo we went with a super straightforward task. 5 invoices, and a single goal: Extract structured information from them. We put Qwen 3.5 0.8B vs. Anthropic's Haiku model. The results are surprising. Not only is the local model 3x faster on average. It also costs a total of 0 EUR. All while keeping your data 100% private. And everything is powered by NobodyWho.
If you want to run the demo yourself, it's just a couple of commands, and the code is [right here](https://github.com/nobodywho-ooo/nobodywho-invoice-demo).
Everything NobodyWho does is open-source, please leave [a star on GitHub](https://github.com/nobodywho-ooo/nobodywho) to support us ❤️
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source & further reading
nobodywho.ai — original article
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LLM, give me a JSON. Make no mistakes.