Parashift vs. OpenAI
Both run on language models. With Dokumentli®, Parashift uses its own vision language model built for one thing: business documents. The difference lies in the model class, in how it is operated, and in the platform around it.
Not whether a language model. Which one, where it runs, and what sits around it.
The question «why not just use GPT for this» assumes an opposition that does not exist. Parashift works with a language model too. Dokumentli® is a small special-purpose vision language model, trained for exactly one job: classifying business documents and reading fields out of them.
A general-purpose frontier model can do that as well. It can also write code, reason and produce prose. That breadth has a price: accuracy on documents, speed, cost per page, and the freedom to decide where processing happens.
The difference sits on three levels. Which model does the work. Where it runs. And what else has to happen between document intake and the target system.
Where the difference actually sits.
A specialist, not a generalist
Dokumentli® is trained on business documents and deliberately cannot do anything else. No open reasoning, no code, no conversation. That is why it is more accurate at its own job.
Measured, not claimed
In our own benchmark from August 2026 across 3368 real business documents, Dokumentli® reaches 88.4% cANLS@0.8, ahead of Gemini 3.6 Flash at 83.5% and GPT-5.6 Sol at 81.8%.
Runs on your own hardware
Dokumentli® runs on a single GPU with 24 GB of VRAM, on premise or in a private cloud. A hosted API service does not offer that choice.
Fix the processing location
Switzerland, Germany or the EU, contractually assured. For banks, insurers and hospitals that is the condition under which a project starts at all.
A platform, not an endpoint
Separation and classification come before extraction, then confidence checks, validation against master data and handover to the target system. A model call covers one of those steps.
Evidence chain per field
It is logged which document and which page a value came from, how certain it was and who corrected it. That is the basis for audit.
Which model is right when.
Frontier model
Reasoning, code, open conversation, creative writing. Dokumentli® is not built for any of that.
Frontier model
One stack, one analysis, no audit duty. Fast and without setup.
Dokumentli®
Daily throughput, identical results, confidence, handover to the core system.
Dokumentli®
Processing location, evidence and logging are part of the requirement.
General-purpose frontier model and Parashift with Dokumentli®.
| Task | General-purpose frontier model | Parashift with Dokumentli® |
|---|---|---|
| Classify business documents and extract fields | Possible, at lower accuracy | Core task, trained for it |
| Accuracy in our benchmark 08/2026 | GPT-5.6 Sol: 81.8% cANLS@0.8 | Dokumentli®: 88.4% cANLS@0.8 |
| Open reasoning, code, conversation | Core task | Not provided for |
| On-premise operation | Not provided for | A single GPU with 24 GB VRAM |
| Fixing the processing location | Depends on the provider | Switzerland, Germany or the EU |
| Splitting stacks into documents | Not provided for | Part of the processing |
| Confidence value per field | No calibrated value | Per field, with a threshold |
| Evidence for audit | No per-field log | Document, page, timestamp per value |
| Cost at high volume | Grows with every token | Calculable per page or per node |
Our own measurement, August 2026.
cANLS@0.8, highest of seven models tested
Parashift benchmark 08/2026real business documents across five datasets
Parashift benchmark 08/2026of VRAM are enough for production use
Dokumentli® data sheetNot an either-or.
Many customers use both: a frontier model for analysis, reasoning and text work, Dokumentli® for the document stream that has to reach the core system every day.
Questions about this comparison.
Is Parashift not just a language model as well?
Why would a smaller model be more accurate than GPT?
What can Dokumentli® not do?
Can we run the model ourselves?
What is the difference between the model and the platform?
How do costs behave at high volume?
See the difference on your own documents.
Book a no-obligation briefing: we run your documents through Dokumentli® and a frontier model and show the results side by side.
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