PyMuPDF4LLM now includes Layout. Native PDF structure intelligence, no GPU required.

Native PDF Structure
Intelligence for LLMs

Extract structured text, tables, and images from PDFs with automatic structure preservation. Optimized for RAG pipelines and Large Language Models.

MosttoolsrenderPDFsintoimages,thenguessthestructureback.PyMuPDF4LLMreadsthevectordatadirectly,preserving100%fidelity.

TRY DEMO

0×

Faster than vision models

0×

Cost reduction at scale

Table accuracy, financial docs

0.0M

Parameters vs VLM billions

Compare Python-native performance against vision models

PyMuPDF4LLM processes PDFs 10x faster than alternatives. Extract text, tables, and structure at lightning speed, no GPUs, no cloud APIs, just pure Python performance.

GET STARTED TRY DEMO

Why PyMuPDF4LLM?

Reading the Document's DNA

We read PDF structure (fonts, spacing, positions, etc) directly, then use a Graph Neural Network to understand the patterns.

TRY DEMO

CPU Processing, GPU-Level Accuracy

While VLMs burn through expensive compute just to recognize titles and tables, our CPU-based approach handles all the structure extraction.

TRY DEMO

Built on Decades of PDF Knowledge

Decades of PDF expertise meeting real-world AI demands, engineered for modern workflows.

TRY DEMO

Try the PyMuPDF4LLM
Interactive Demo

10x faster than GPU-based solutions. Runs on any CPU. Upload your PDF and watch PyMuPDF4LLM extract clean, structured text in seconds—no signup required.

TRY DEMO

Enterprise Scalability
Starts with Better Data

PyMuPDF is built on open collaboration and always will be. Our code is freely available on GitHub under the AGPL license, welcoming contributions from developers worldwide. For projects requiring different terms, we also offer commercial licensing through Artifex.

SEE LICENSE