Iteration Layer vs OlmOCR
OlmOCR is a strong open-source OCR model — but English-only, GPU-dependent, and strips headers and footers by design.
No credit card required — start with free trial credits
Why developers switch from OlmOCR
OlmOCR requires a GPU, only supports English, and intentionally strips headers and footers.
Image description field
When you convert an image file, we return both the OCR-extracted markdown and a natural language description of the image content. OlmOCR returns text extraction only — no semantic understanding of what the image shows.
EU hosting with GDPR compliance
OlmOCR runs on your infrastructure — data residency is your responsibility. We process all documents on EU servers with zero data retention and a Data Processing Agreement available for every customer.
No GPU infrastructure to manage
OlmOCR requires an NVIDIA GPU with 12–20 GB of VRAM for local inference. We are a managed API: one HTTP call, no GPU procurement, no model downloads, no Python environment.
Feature-by-feature comparison
We went through the docs so you don't have to. Here's how every feature compares — including the ones where we're not the better choice.
| Feature | Iteration Layer | OlmOCR |
|---|---|---|
| Markdown output |
Clean markdown
Returns well-structured markdown with preserved headings, tables, and lists from any document |
Markdown
Outputs markdown with tables as HTML and math as LaTeX, but strips headers and footers by design |
| Image description |
Yes
Returns a natural language description of image content alongside OCR markdown for image files |
No
Text extraction only — no semantic description of visual image content |
| Supported input formats |
40+ formats
Process 40+ formats — PDF, Office, EPUB, RTF, LaTeX, email, Jupyter, images, and more — in a single API endpoint |
PDF, images
Supports PDF and image files (PNG, JPEG) only |
| Language support |
Multilingual
Handles documents in any language |
English only
Fine-tuned on English documents only — non-English performance is unreliable |
| Headers and footers |
Preserved
Document headers and footers are preserved in the markdown output |
Stripped
Intentionally removes headers, footers, and page numbers — designed for LLM training data |
| MCP server |
Yes
MCP server available for integration with AI agents and assistants |
No
No MCP server available |
| Open source |
Proprietary
Closed-source managed SaaS platform |
Apache 2.0
Fully open source including model weights, training data, and code under Apache 2.0 |
| Math and tables |
Standard
Standard table extraction and document structure preservation |
Strong
Strong handling of tables (as HTML) and math equations (as LaTeX) within the markdown output |
| EU hosting |
EU only
All processing happens exclusively on EU-hosted servers |
Your choice
Runs on your infrastructure, so data residency depends on where you deploy |
| Pricing model |
Per page
Simple, predictable per-page pricing |
Free
Open source and free — costs are limited to GPU compute infrastructure |
| Infrastructure required |
None
Fully managed API with no deployment or infrastructure to manage |
GPU required
Requires an NVIDIA GPU with 12–20 GB VRAM, Python 3.11, and poppler-utils |
| GDPR / Data privacy |
Zero retention
No files or results stored beyond temporary 90-day logs |
Your responsibility
Data privacy depends entirely on your deployment and infrastructure choices |
Pricing
Start with free trial credits. No credit card required.
Developer
For individuals & small projects
Startup
Save 40%For growing teams
Business
Save 47%For high-volume workloads
Or pay as you go from $0.022/credit with automatic volume discounts.
Still evaluating?
See how we compare — and where the competition still wins. Choosing the right tool shouldn't require a week of research.
Reducto
Reducto outputs markdown from US servers and charges per page — without an image description field.
LlamaParse
LlamaParse is US-based and per-page — and doesn't describe image content.
Mistral OCR
Mistral has best-in-class OCR and returns markdown, but doesn't describe image content and processes files from US servers.
Nanonets
Nanonets DocStrange outputs markdown, but has no image descriptions and no EU hosting option.
DocuPipe
DocuPipe extracts structured fields from documents — it doesn't produce clean, readable markdown.
Unstructured
Unstructured is built for ETL pipelines and RAG ingestion — not a simple document-to-markdown API.
AWS Textract
Textract returns raw strings and bounding boxes — not a markdown document ready to read or embed.
Azure Document Intelligence
Azure outputs model-specific field values, not clean markdown — and requires model selection or training first.
Google Document AI
Document AI requires a GCP project, processor selection, and S3-equivalent storage before you get any text out.
PaddleOCR
PaddleOCR outputs markdown, but requires the PaddlePaddle framework and self-hosted infrastructure.
Tesseract
Tesseract outputs raw text — no headings, no tables, no document structure preserved.
Start building in minutes
Free trial credits included. No credit card required.