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LlamaParse 支持 SaaS、自有云与本地硬件等 5 种部署方式

LlamaIndex@llama_index
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Why we picked it

做 RAG 的朋友可以看看，LlamaParse 现在能部署在自己云账号甚至自己 GPU 上，数据不出内网。相比只用托管 API 的解析服务，它给了 5 档选择，合规要求严的企业团队尤其值得对比一下。

LlamaIndex 宣布其文档解析产品 LlamaParse 可按 5 种部署模式运行：托管 API、部署到客户自己的云账户或数据中心、平台与存储留在客户环境但由 LlamaIndex 运行模型、接入客户现有推理服务商、以及客户在自己的 GPU 上运行受支持的模型。

Image · LlamaIndex
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选型的核心判断标准是文档允许存放的位置和基础设施由谁管理。官方明确：使用其推理服务时，LlamaIndex 不留存客户数据，也不用客户数据训练模型。

配套博客逐项说明每种模式下各组件的归属，帮助团队按数据合规要求选择部署方案。

Original · LlamaIndex

LlamaParse can run anywhere: SaaS, in your cloud, or on your hardware. Which one fits usually comes down to one question: where are your documents allowed to live and who manages infra? 1/ Our managed API, where we run everything 2/ The full platform in your own cloud account or data center 3/ The platform and storage in your environment, with us running the models 4/ Your existing inference provider, connected to the platform 5/ Your own GPUs, running supported models yourself If you use our inference, we don’t retain your data or train on it. The blog walks through what runs where, what your team owns in each setup, and how to pick from our deployment models: llamaindex.ai/blog/how-to-fl…📊 2 ⚡

Industry Coordinates & Source Verification

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. Key entities and technical topics under continuous tracking include LlamaParse, LlamaIndex, RAG, 文档解析.

Source attribution: curated from LlamaIndex (@llama_index).

#LlamaParse#LlamaIndex#RAG#文档解析

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