Why Guess When You Can Read?

AI extraction agents rely on vision models that convert crisp vectors into fuzzy pixels. We read the source code of the PDF.

Vision Language Models

~35s

Using Gemini 3.0 Pro which is current SOTA vision model at highest image res

per page

✓

Great for Scans

Necessary for complex, handwritten, or scanned docs

Overkill for Digital

Using heavy GPUs to read simple text layers

Slow & Expensive

Reconstructs text visually instead of reading data

Cost at Scale

$14.40/1k pages

PyMuPDF4LLM

0.17s

per page

✓

Perfect for Born-Digital

Extracts text directly from the source layer

✓

Instant & Precise

Direct text extraction from source

✓

Structured Topology

Reconstructs reading order mathematically

Cost at Scale

~$0.06/1k pages

Based on prorated second-level billing for a c2d-highcpu-32 instance (32 vCPUs) on Google Cloud.

Calculated on Google Cloud Compute

⚡️

RAG Pipelines

Fast indexing

📊

Financial

Cut extraction costs

⚖️

Legal

Verify against source

🎓

Academic Research

Parse papers at scale

Stop Paying Vision Rates for Text.

Switch to native extraction and reduce your costs by 250x.