LlamaIndex 开源 PDF 解析工具 LiteParse 更新，速度达 2.8ms/页
LlamaIndex 家的 PDF 转 Markdown 工具 LiteParse，一页只要 2.8ms，本地就能跑，做 RAG 解析文档的可以试试。
LlamaIndex 发布 LiteParse v2.14.
6，文本型 PDF 解析速度提升约 25%。在真实文档测试中达到 2.
8ms/页，比次快的本地解析器快 1.5 倍。
LiteParse 是开源项目，支持在 Python、Node.js、Rust 以及浏览器中本地运行，输出 PDF 转 Markdown 结果。
liteparse is the fastest pdf parser on the planet parses each page at just 2.8ms / page!! check it out: github.com/run-llama/lite… LlamaIndex 🦙 @llama_index The fastest PDF-to-Markdown parser just got faster. ⚡️ With LiteParse v2.14.6, text-based PDFs parse about 25% faster. Across realistic documents, LiteParse processed pages at 2.8ms/page and 1.5× faster than the next-fastest local parser. LiteParse is open source and runs locally in Python, Node.js, Rust, or directly in the browser. Grab v2.14.6 → github.com/run-llama/lite… Bench Docs → huggingface.co/datasets/llama… 🔗 View Quoted Tweet📊 6 ⚡
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 LiteParse, LlamaIndex, RAG, PDF解析.
Source attribution: curated from Jerry Liu (@jerryjliu0). Cross-source corroboration: 3 independent sources have covered this development (including Perplexity, Aravind Srinivas), confirming industry-wide signal strength.
