LlamaIndex 发布文档解析模型 OCRia-1，ParseBench 得分 87.4
LlamaIndex 发了个 4B 的小模型 OCRia-1，专门啃文档解析，表格图表扫描件都能转成结构化内容，跑分超过了 Mistral OCR，直接用在 LlamaParse 里。
LlamaIndex 团队发布 4B 参数的视觉语言模型 OCRia-1，专注文档解析。该模型在 ParseBench 上取得 87.4 分，在第三方基准 olmOCR-bench（总分 83.5，表格项 92.9）、PulseBench-Tab（84.1）和 fr-bench-pdf2md（72.1）上均领先。它擅长解析嵌套表头、合并单元格、扫描表格等复杂表格，也能处理折线图、饼图、技术示意图等无标注图表。OCRia-1 已作为底层模型接入 LlamaParse 的全部模式，同参数量级下超过 LightOnOCR-3、Chandra-OCR 2 和 Mistral OCR 4.1。企业预约演示可获得最高 3000 美元评估额度。
YOU CAN PARSE EVERYTHING 11.17.26 ocria-1 is already the cheapest, most accurate unified model for doc parsing (not only tables/text, but also charts/diagrams/images/scans) it's only getting better. stay tuned Your browser does not support the video tag. 🔗 View on Twitter Jerry Liu @jerryjliu0 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 Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 4 🔄 0 ❤️ 15 👀 847 📊 6 ⚡
