pymupdf/PyMuPDF Alternatives

Choose for a Rust-based PDF library with faster text/image extraction and permissive Apache-2.0 license, if AGPL of PyMuPDF is a concern and you don't need MuPDF's rendering.

The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry leaders, 100% pass rate on 3,830 PDFs. MIT/Apache-2.0.

Choose for pure-Python PDF manipulation (split, merge, crop, rotate) with no native dependencies and an active community, if you accept slower text extraction and no rendering.

A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files

Choose for high-accuracy PDF-to-Markdown conversion with deep-learning layout/OCR when you need a ready-made pipeline rather than a general PDF library.

Convert PDF to markdown + JSON quickly with high accuracy

Choose for AI-ready structured extraction with layout analysis in Java, if your stack is Java and you need multimodal PDF parsing.

PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.

Choose for polyglot document extraction with a Rust core across many formats, if you want a native library in non-Python environments.

A polyglot document intelligence framework with a Rust core. Extract text, metadata, images, and structured data from 101 formats (115 file extensions) plus code intelligence for 371 code languages. 15 language bindings — Rust, Python, Ruby, Java, Go, PHP, Elixir, C#, TypeScript — plus CLI, REST API, and MCP server.

Choose for a visual/rule-based pipeline that turns PDFs into structured JSON/CSV with OCR support, if you need a server-side document-to-data service.

Transforms PDF, Documents and Images into Enriched Structured Data

Choose for a RAG-focused toolkit that converts PDFs to clean Markdown and analyzes chunking, if your use case is specifically building LLM retrieval pipelines.

Open-source toolkit for reliable RAG pipelines: convert PDFs to Markdown, clean documents, inspect chunks, compare chunking strategies, and enrich metadata for LLM applications.

Choose for complex document-to-Markdown/JSON conversion with strong OCR and layout models, especially for mixed-form scanned documents.

Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.

Choose for a fast Rust-based document parser that handles many formats, if you need high-throughput extraction and don't require PDF manipulation or rendering.

A fast, helpful, and open-source document parser

Choose for an on-premises, OCR-free unstructured data extraction and Markdown conversion toolkit with a benchmarking component, if you want a self-contained extraction pipeline.

An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit. (https://idp-leaderboard.org/)

Choose for vision-model-based OCR and document extraction on complex/scanned files, when you can tolerate latency/cost and don't need low-level PDF control.

OCR & Document Extraction using vision models

Choose for specialized conversion of scanned book PDFs to other formats, if your workflow focuses on OCR-heavy book scanning rather than general PDF tasks.

PDF craft can convert PDF files into various other formats. This project will focus on processing PDF files of scanned books.

Choose for detailed character-level text extraction and table parsing in pure Python with a permissive MIT license, if you don't need PDF editing or rendering.

Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.

Choose for fast Rust-based PDF inspection and classification (scanned vs text) if your focus is document routing, not manipulation.

Fast Rust library for PDF inspection, classification, and text extraction. Intelligently detects scanned vs text-based PDFs to enable smart routing decisions.

Choose for a pre-built high-quality PDF extraction toolkit if you are willing to use an older, less actively maintained codebase.

A Comprehensive Toolkit for High-Quality PDF Content Extraction

Choose for niche table extraction from OCR'd scanned PDFs, but it is outdated and unmaintained.

A set of tools for extracting tables from PDF files helping to do data mining on (OCR-processed) scanned documents.

Choose for multi-language unstructured data extraction from a Rust core with bindings, but the project has not been updated in over 1.7 years.

Fast and efficient unstructured data extraction. Written in Rust with bindings for many languages.

Choose for simple PDF table extraction as a Python library, but it is archived and unmaintained, so only for legacy use.

Camelot: PDF Table Extraction for Humans

Choose when you want a ready-to-deploy API service for OCR/extraction with PII removal, rather than a library to embed in your code.

Document (PDF, Word, PPTX ...) extraction and parse API using state of the art modern OCRs + Ollama supported models. Anonymize documents. Remove PII. Convert any document or picture to structured JSON or Markdown

Choose for a user-facing web application to manipulate PDFs (split, merge, compress) through a GUI, not a library.

#1 PDF Application on GitHub that lets you edit PDFs on any device anywhere

Actually a CLI client for LandingAI's commercial Agentic Document Extraction API, not a standalone library.

The official CLI for Agentic Document Extraction (ADE) by LandingAI — parse documents and extract schema-shaped data from your terminal

Choose for a Windows GUI utility for editing PDF bookmarks, cropping, splitting, and extracting images, if you need an interactive tool rather than a code library.

PDF补丁丁——PDF工具箱，可以编辑书签、剪裁旋转页面、解除限制、提取或合并文档，探查文档结构，提取图片、转成图片等等