# LlamaIndex releases OCRia-1, a 4B document parsing model with SOTA scores

> Original title: Today we’re releasing OCRia-1, a frontier VLM for document parsing that sets a new SOTA in accuracy, cost, and latency.

- Source: Jerry Liu
- Published: 2026-10-22T15:30:33.000Z
- Bad Influence: https://badinfluence.news/items/li9t3x2dzk121owlwzuml88j9
- Original: https://x.com/jerryjliu0/status/2113291928292790725

## Summary

LlamaIndex releases OCRia-1, a 4B-parameter vision-language model for document parsing, reporting 87.4 on ParseBench. It also scores 83.5 overall and 92.9 on tables in olmOCR-bench, 84.1 on PulseBench-Tab, and 72.1 on fr-bench-pdf2md, and the company says it outperforms similar-sized models including LightOnOCR-3, Chandra-OCR 2, and Mistral OCR 4.1. OCRia-1 now powers LlamaParse's cost-effective, agentic, and agentic plus modes, and enterprises that book a demo can get up to $3k in credits for evaluation.

## Post

Today we’re releasing OCRia-1, a frontier VLM for document parsing that sets a new SOTA in accuracy, cost, and latency. 

It not only sets a new high score on ParseBench (87.4), but also leads in three 3rd-party benchmarks: olmOCR-bench* (83.5 overall, 92.9 on tables!), PulseBench-Tab (84.1), and fr-bench-pdf2md (72.1).

OCRia-1 is really, really good at parsing complex tables: nested headers, merged cells, irregular grids, scanned tables, and more. It is also fantastic at parsing complex unlabeled charts (line, bar, pie, technical diagrams), and preserving complex formatting. Most real-world enterprise documents contain at least one of the these, whether it’s a big tax withholding table or a public economic report.

It is a 4B model and outperforms all other models within a similar parameter class: LightOnOCR-3, Chandra-OCR 2, Mistral OCR 4.1, and more. It is also extremely fast.

All credit goes to our research team, who spent countless hours on curating a diverse dataset, tuning our training pipeline, and squeezing every last drop out of model optimization so that it can process billions of pages at scale. 

OCRia-1 as a base is powering all of our modes within LlamaParse (cost-effective, agentic, agentic plus), so you can access its capabilities today! 

If you’re processing millions/billions of documents at scale, we’re offering enterprises that book a demo up to $3k in credits for a guided evaluation.**

*olmOCR-bench scores are adjusted based on unifying rendering at 1,288px for all models 
**enterprise POC credits apply to eligible organizations that book a demo

[Video](https://badinfluence.news/api/img-proxy?u=https%3A%2F%2Fpbs.twimg.com%2Fext_tw_video_thumb%2F2113291822562721792%2Fpu%2Fimg%2FaFE0Q04DhH_id6Io.jpg&mode=thumb&exp=1793923200&sig=a65a55a06135e8ca)