LlamaParse新增企业自托管部署选项
LlamaIndex宣布，LlamaParse现可部署在客户的AWS、Azure或Google Cloud账户中，也可通过Kubernetes运行在自有数据中心。Enterprise套餐支持自托管，客户可使用自有模型提供商、在本地GPU托管受支持模型，或交由LlamaIndex管理推理。厂商称，本地托管文档模型时，Parse Cost-Effective和Agentic应保持相同质量，但部署使用不同前沿模型可能导致Extract结果变化。
自托管让企业能控制文档存储、基础设施、模型提供商协议和推理运维，但可用性与质量说法目前仅来自LlamaIndex Blog的单一来源。
Most document AI platforms make you pick between convenience and control. LlamaParse doesn't. It's built to run wherever your documents need to live: as a fully managed API, inside your own cloud account, or in your own data center. And you choose who runs the models behind it. The same parsing and extraction engine works across every setup, so your deployment fits your security, compliance, and infrastructure requirements, not the other way around.
That flexibility matters most when document pipelines move into production. Where will your documents live? What needs to run in your environment? How much infrastructure does your team want to own? LlamaParse has an answer for each:
- SaaS: We run the platform and inference infrastructure.
- VPC (BYOC): You deploy the platform in your AWS, Azure, or Google Cloud account.
- On-prem: You run the platform in your own data center.
And running the platform yourself doesn’t have to mean signing up to run a fleet of GPUs. LlamaIndex can manage inference for you, giving you cost savings, immediate compute availability, and less operational overhead.