Building powerful, LLM-driven document applications often starts with an accurate and efficient parser. But for many real-world workflows, privacy is non-negotiable sensitive files must run locally on your laptop, without a single byte touching the cloud.
That local setup also has to be fast. An ideal parser should reach 5 to 10 frames per second, which means a 100-page document can be parsed in about 10 to 15 seconds, fast enough for users to move straight into interactive Q&A. But speed alone is not enough. The parser also has to handle complex layouts, dense tables, and paragraphs that span pages, scanned documents, and multiple languages.
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We built DocDot because local PDF work still comes with a bad tradeoff. Keep documents on-device, and setup gets messy. Chase speed, and you often give up fidelity. DocDot gives you a one-line install on macOS, runs fully local, and brings multiple PDF parsers into one workflow so you can install them, switch instantly, and compare output on the same file. It also auto-installs skills for popular agents, so the parsed result can move straight into downstream agent workflows.
Today DocDot includes NanoDoc, PaddleOCR, GLM-OCR, LiteParse, and MinerU.
In our current benchmark, NanoDoc leads on overall quality at 83.66, table TEDS at 83.19, and speed at 9.25 FPS, with peak memory at 1.78 GB. MinerU still leads formula CDM at 86.64, which is exactly why we keep multiple parsers in one workflow.
Rather than forcing a single solution, we provide a streamlined local method to pick the right backend for the document in front of you.
We will be in the comments all day. If you have a file that usually breaks your workflow, please share it with us.