Model Releases
We created a document OCR router that can estimate the complexity of every single page and parse it with the relevant mode 💫 * Some pages a…
We created a document OCR router that can estimate the complexity of every single page and parse it with the relevant mode 💫 * Some pages are full of native text, which can be directly handled with Li
We created a document OCR router that can estimate the complexity of every single page and parse it with the relevant mode 💫 * Some pages are full of native text, which can be directly handled with LiteParse * Some pages contain scanned images or tables, which can be handled with our cost-effective or agentic tiers * Some pages contain garbled text - it decodes to garbage - so you need a heavier-weight VLM to interpret the text elements * Some pages contain heavy visuals like labeled/unlabeled charts or diagrams, which also require deeper visual processing You actually get the routing capabilities for free with the is_complex toggle in LiteParse. The next step is figuring out what the relevant VLM modes are to parse varying page complexities. That's well served by LlamaParse! Blog: https://www.llamaindex.ai/blog/parse-gateway-smart-page-level-document-parser-routing LiteParse: https://github.com/run-llama/liteparse LlamaParse: https://cloud.llamaindex.ai/ Not every page in your PDF needs the same treatment. A scanned cover, a dense table, a clean text page, a figure-heavy diagram.... most parsing pipelines throw all of them at the same parser, forcing a tradeoff between cost, speed, and accuracy across the whole document. We built…
Source: Jerry Liu (X) | 2026-07-31