Baidu OCR in the stack: why classic text recognition stays alongside visual search
OCR is not dead. PaddleOCR-VL delivers searchable text where visual search alone falls short.
This translation was produced automatically using AI. The German version is the editorially reviewed original.
Amid all the enthusiasm for visual document search, a sober line is worth stating: OCR is not dead. Modern text recognition like Baidu's PaddleOCR-VL has become good and cheap enough that it keeps a firm place alongside visual retrieval, not as a competitor, but as the layer that delivers searchable, copyable, auditable text. The right question is not OCR or visual search, but which one for which job.
01. WHAT VISUAL SEARCH DELIBERATELY DOES NOT DELIVER
Visual retrieval models find the right page, even in a difficult scan. But they give you back an image, not text. You cannot easily copy a line from it, run full-text search across the archive, or build a machine-readable audit trail. For all of that, you need recognised text. This is not a weakness of the new approach, but a deliberate division of labour: search on the image, text extraction via OCR, each stage doing what it does best.
02. WHAT PADDLEOCR-VL CAN DO
Baidu has released PaddleOCR-VL, an open OCR model that achieves top scores with only 0.9 billion parameters (project). It recognises text, tables, formulas and diagrams in 109 languages and reconstructs the semantic structure of a document. On the OmniDocBench v1.5 benchmark, it leads with around 94.5% accuracy. It is released under the Apache 2.0 licence, so it can be used commercially free of charge and run on-premise. For an SME, that means strong text recognition without a recurring fee and without data leaving the building.
03. THE HYBRID SETUP
In practice, both approaches run side by side. Visual search finds the relevant pages quickly and preserves layout fidelity. Where that needs to become hard text, for instance for an invoice line item, a contract clause to quote, or an entry into the ERP system, OCR takes over on precisely those few pages. You do not need to run the entire archive through OCR, only what search has already flagged as important. That keeps the pipeline lean and prevents OCR errors from seeping into search from the outset.
04. THE PRAGMATIC LINE
Either-or is the wrong stance here. Visual search improves finding, OCR improves further processing. Anyone who treats both as tools with clear roles builds a more resilient knowledge base than someone who dogmatically backs one side. How the building blocks fit together, from the encoder to the vector database, is covered in the stack overview.
