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@jerryjliu0

There’s not that many fast, free, non-VLM document parsers out there: there’s PyPDF, PyMuPDF, Markitdown, OpenDataLoader. Last week, we launched LiteParse ⚡️📄: a fast, free, and non-VLM based document parser that provides the highest quality context to AI agents compared to other tools out there. ✅ It extracts document text into an interpretable spatial representation ✅ It has native screenshotting capabilities to let agents (e.g. Claude Code) to do a “fast and light” text parsing step, and then a “deep-dive” into specific page content by feeding the screenshot into itself. ✅ It supports out-of-the-box integrations with other tools like PaddleOCR (@PaddlePaddle) Check out our benchmark below against the other tools. We use LLM QA performance to measure the ability for LLMs to semantically understand the parsed text, and also measure latency. If you try it out, we’d love to get your feedback. The repo is here: https://t.co/JNER0mVcB8 If you’re looking for a more accurate, VLM-native solution that can parse any document at scale, LlamaParse might be better for you! https://t.co/TqP6OT5U5O

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