LiteParse v2, now in Rust 100x faster
LiteParse is an open-source (Apache 2.0) document parser that provides high-quality spatial text parsing with bounding boxes. It does not depend on local or frontier VLMs. Because it does not require GPUs, liteparse can be run on any machine, and process a few hundred pages of documents in seconds. It offers higher accuracy than similar tools like PyPDF, PyMuPDF, MarkItDown. It supports a variety of file formats - PDFs, Office documents, images. It can be one-line installed as a skill for 40+ different AI agents, including Claude Code, Cursor, OpenClaw, Windsurf, and more.
LiteParse v2, now in Rust 100x faster launched on May 28, 2026 with 15 votes, #1,002 of 20,538 launches that month and more than 90% of that year's launches.
In plain words
LiteParse v2 is a parsing tool rewritten in Rust for improved performance. It is designed for developers who need efficient code parsing and analysis. The software is available on GitHub. This version emphasizes speed improvements over its predecessor, making it suitable for projects requiring fast parsing operations.
written from the facts on this page · September 2026
From the sources
A fast, helpful, and open-source document parser. Contribute to run-llama/liteparse development by creating an account on GitHub.
In the maker’s words, at launch
LiteParse is a standalone OSS (Apache 2.0) PDF (and other document types) parsing tool focused exclusively on fast and light parsing. It provides high-quality spatial text parsing with bounding boxes, without proprietary LLM features or cloud dependencies. Everything runs locally on your machine.
Does a similar job
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Local Document Parsing for AgentsMar 2026 · llamaindex.ai · ▲20The core processing engine behind LlamaParse is now open source. LiteParse runs entirely locally, has zero Python dependencies, and is built around how agents actually iterate on documents: parse text fast, fall back to screenshots when you need visual reasoning.
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