# Unstructured PDF parsing: fast, hi_res and ocr_only solve different inputs

Unstructured PDF strategies should be selected by the document's actual content and required structure, rather than treating fast, hi_res and ocr_only as quality levels.

Author: Retrivium team
Updated: 2026-11-03
Canonical URL: https://retrivium.ai/journal/unstructured-pdf-strategy-selection/
Language: en

Unstructured PDF strategies should be selected by the document's actual content and required structure, rather than treating fast, hi_res and ocr_only as quality levels. Digital text, scanned pages and layout-dependent tables present different extraction problems and can require different processing paths.

## Read strategy responsibilities

The official [strategy documentation](https://docs.unstructured.io/open-source/concepts/partitioning-strategies) describes the available partitioning approaches. A text-oriented path and an OCR-oriented path do not consume equivalent evidence. Layout analysis adds another responsibility: identifying elements and their relationships. Avoid assuming the most elaborate strategy is universally preferable. It can introduce dependencies and output differences that are unnecessary for a simple digital document but material for a complex scanned form.

## Inspect the PDF before selecting a path

The [partitioning reference](https://docs.unstructured.io/open-source/core-functionality/partitioning) documents PDF-specific behavior and strategy options. Sample pages for usable embedded text, images containing text, columns and tables. A file can mix digital and scanned pages, so a successful first page is not a sufficient sample. Determine whether the output needs plain paragraphs, element categories, table structure or page-linked evidence before deciding which strategy to evaluate.

## Create a three-document acceptance set

Use a digital policy, a scanned invoice and a brochure with columns. Ask each conversion to recover a specific evidence relationship, not just produce nonempty text. Keep the same downstream retrieval question for comparable outputs. If an extraction path changes text order, that defect belongs to parsing even when an embedding model later ranks the corrupted fragment highly.

| Input | Key acceptance check |
| --- | --- |
| Digital policy | Preserve paragraph and section boundaries |
| Scanned invoice | Recover labels and corresponding values |
| Multicolumn brochure | Preserve intended reading flow |
| Layout-dependent table | Keep row and header relationships |

## Inspect dependencies and fallbacks

The [primary implementation](https://github.com/Unstructured-IO/unstructured) supplies version-specific behavior. Record the package revision, OCR configuration and required model or system dependencies. A requested strategy and the path actually executed may differ under documented conditions, so retain logs and output metadata. Do not present a command as universally equivalent across environments when dependency availability can change processing or prevent the requested operation from running.

## Accept the output contract, not the label

Compare missing text, ordering defects, element types and evidence provenance across the fixture. Choose the least complex path that meets those requirements, while retaining exceptions for difficult document classes. Report uncertain pages for review rather than inventing uniform extraction quality. The operational artifact is a document-class decision table with verified output examples, not a blanket declaration that one strategy always produces better RAG answers or faster conversion on every machine.

Related reading: [A GPU OCR pipeline for a 1,000-page PDF workload](/journal/pdf-ocr-gpu-pipeline/); [OCR on CPU or GPU: where acceleration changes the pipeline](/journal/ocr-gpu-vs-cpu/).