LlamaIndex 发布 ParseBench-2 与 OCRia-1.5 文档解析模型
LlamaIndex 这次一次发了两样东西：ParseBench-2 基准给 330 多种解析错误标了严重度，评分终于和人 judgment 对得上；OCRia-1.5 模型专攻表格、表单、图表这些最难啃的版式。做 RAG 文档入库或选 OCR 方案的团队可以直接拿来当选型标准。
LlamaIndex 推出文档解析基准 ParseBench-2，包含 4.3k+ 文档页面，比上一版翻倍，并新增表单（forms）维度。
基准对 330+ 错误类型逐一标注严重度分数，让指标与人工判断高度对齐。相比 OmniDocBench 的确定性指标和 ParseArena 的 LLM-as-a-judge 方法，ParseBench-2 同时兼顾细粒度错误定位和稳定的评分。
同期发布的 OCRia-1.5 是驱动 LlamaParse 各解析模式的模型家族，在复杂表格、表单、图表、格式还原和复杂版式 bounding box 标注上达到当前最优。
其前代 ParseBench 已有 5 万+ 月下载量、150+ 个 OCR 方案被测评，NVIDIA、Cohere、Perplexity 等公司采用。
rain or snow, we keep shipping Jerry Liu @jerryjliu0 Today we’re introducing ParseBench-2 - our most ambitious document parsing benchmark to date. It is the only benchmark that provides both extreme granularity into every single type of production parsing error, while also making sure that metric scores are highly aligned with human judgment. We do this by painstakingly assigning severity scores to 330+ error types, and tuning each metric to match the severity scores. Existing benchmarks either use brittle deterministic metrics (e.g. OmniDocBench) or LLM-as-a-judge (ParseArena), which can help recognize equivalent representations but are coarse/stochastic/subject to bias by the prompt+model. ParseBench-2 also contains: ✅ 4.3k+ document pages (double from ParseBench-1). ✅ An extra dimension (forms) ✅ Much better ground-truth across all dimensions compared to ParseBench-1. This is the next evolution of ParseBench, our hugely popular benchmark that has 50k+ monthly downloads, over 150+ OCR solutions benchmarked, and has been adopted by companies like NVIDIA, Cohere, Aleph Alpha, Perplexity, and others. Alongside ParseBench-2, we are also releasing OCRia-1.5 - a new family of document parsing models that powers all our modes in LlamaParse. They represent a massive step up in capabilities from our latest release, and are state of the art in parsing complex tables, forms, charts, formatting, and assigning bounding boxes to complex layouts. Come check out our blog post, technical report, and website. Blog: llamaindex.ai/blog/introduci… Technical Report: llamaindex.ai/files/parseben… Website: parsebench.ai If you’re interested in trying out our OCRia-1.5 capabilities, come sign up for LlamaParse: cloud.llamaindex.ai
This report is categorized under AITOP's "Products" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include LlamaParse, ParseBench, OCRia, OCR.
Source attribution: curated from Jerry Liu (@jerryjliu0).
