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Azure

Enable your agents to unlock knowledge from anywhere

Foundry IQ (Azure AI Search) provides a context engineering platform for Microsoft's intelligence layer, unlocking knowledge for your agents, wherever it lives. Foundry IQ automatically handles how agents connect to, process and action enterprise information. With built-in enterprise security and agentic retrieval, agents deliver better results from the right context. Foundry IQ knowledge bases require a subscription and a standard agentic retrieval plan. Foundry IQ agentic retrieval activity is billed under "Azure AI Search".

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Apply filters to customize pricing options for your needs. “N/A” indicates pricing is not supported in the selected region.

价格仅是估算值,不应用作实际报价单。实际定价可能因与 Microsoft 签订的协议类型、购买日期和货币汇率而异。价格基于美元计算,并使用在上一个月末最后一个工作日之前的两个工作日内捕获的伦敦收盘即期汇率进行转换。如果本月底之前的两个工作日在主要市场中属于银行假日,则汇率确定日通常是紧接在此两个工作日之后的一天。此汇率适用于下个月的所有交易。登录到 Azure 定价计算器查看基于你与 Microsoft 的当前计划/产品/服务的定价。有关定价或请求报价的详细信息,请联系 Azure 销售专家。请参阅经常询问有关 Azure 定价的问题

Dedicated pricing

Dedicated plans are for enterprise workloads with consistent traffic and high-utilization with an hourly pricing mode.

免费 基本 标准版 S1 标准版 S2 标准版 S3 存储优化版 L1 存储优化版 L2
存储1 50 MB 15 GB
(每服务最多 45 GB)
160 GB
(每服务最多 1.9 TB)
512 GB
(每服务最多 6 TB)
1 TB
(每服务最多 12 TB)
2 TB
(每服务最多 24 TB)
4 TB
(每服务最多 48 TB)
最大索引数/服务 3 15 50 200 200 或者 1,000/分区(高密度模式) 10 10
横向扩展限制 N/A 最多可达 9 个单位/服务
(最多 3 个分区;最多 3 个副本)
最多可达 36 个单位/服务
(最多 12 个分区;最多 12 个副本)
最多可达 36 个单位/服务
(最多 12 个分区;最多 12 个副本)
最多可达 36 个单位/服务
(最多 12 个分区;最多 12 个副本)
最多 3 个高密度2模式下的分区
最多可达 36 个单位/服务
(最多 12 个分区;最多 12 个副本)
最多可达 36 个单位/服务
(最多 12 个分区;最多 12 个副本)
计算类型为默认值
每个搜索单位 (SU) 的定价
$- $- $- $- $- $- $-
计算类型为机密3
每个搜索单位 (SU) 的定价
$- $- $- $- $- $- $-

1If you see lower storage in your service, you can upgrade.

2High density (HD) mode is an option available within the standard S3 service that allows a larger number of indexes to be created in a single service. For information on supported limits, refer here.

3Resources backed by confidential compute are available at additional cost. Some features are limited or unavailable, including semantic ranker, agentic retrieval, skillset execution, and vectorization. Learn more about confidential computing here.

Serverless (preview)

Serverless pricing is for workloads with infrequent or variable traffic. You are billed for compute resources and storage used, and the service scales to zero when idle. No upfront capacity planning is required.

Billing for Serverless is expected to begin in late 2026 with details provided at least 30-days in advance. Customers using Serverless won’t be charged before billing is enabled.

For large-scale Serverless deployments, contact Microsoft for additional options.

Tier Developer
Compute usage
Compute units (CU)
CU / hour
Indexed storage
GB cost is region dependent
GB / month
Indexed storage per index 1 GB / index
Indexes per service 30 indexes / service
Services per subscription per region 5 services / sub / region

* What is a Compute Unit (CU)?

A Compute Unit (CU) is the unit of measure for resource consumption in a serverless tier. Usage is billed in Compute Unit-Hour. Usage is calculated each minute in increments of 0.25 CUs.

What 1 CU Represents

~1 vCPU core

+ 8 GB RAM

+ associated storage I/O

What Gets Billed

Compute consumed by your operations over the course of an hour​.

Usage is calculated each minute in increments of 0.25 CUs

Operations Included

Searches, indexing, indexer execution, agentic retrieval & other service ops

Read more about Compute Units (CU) and pricing Learn More

Indexed storage

Storage costs are billed hourly based on a fractional number of GBs of data stored per index. Total storage consumed includes all data stored in your indexes, such as indexed documents, searchable fields, vector data, and associated metadata within your search service.

To learn more about Serverless and Compute Units, visit our docs.

Features

Agentic retrieval uses a multi-turn, self-reflective agentic framework to run and manage RAG query pipelines. Separate charges are incurred for remote knowledge sources Microsoft SharePoint (remote) and Web.

Semantic ranker improves search relevance for single-turn retrieval query pipelines and keyword search. It is not available in the Dedicated Free tier.

Custom entity Lookup skill detects and labels documents containing user-defined words and phrases. It is ideal for defining and detecting specific entities in your data. It is not available in dedicated free plan.

Document cracking and image extraction retrieves content from a file during an indexer's document cracking phase and within the enrichment pipeline. Image extraction is billed during the initial document cracking step and when invoking the document extraction skill.

Feature Pricing Details
Agentic Retrieval
1M tokens
First 50M tokens free per month
Min = $- per 1M tokens
Low = $- per 1M tokens
Medium = $- per 1M tokens
语义排名程序
1k requests
First 1k requests free per month
$- per 1k requests
自定义实体查找技能
1k text records (tr)
$- per 1k TR | 0-1M tr
$- per 1k TR | 1M-3M tr
$- per 1k TR | 3M-10M tr
$- per 1k TR | 10M+ tr
文档破解:图像提取
1k transactions (t)
$- per 1k t | 0-1M images
$- per 1k t | 1M-5M images
$- per 1k t | 5M+ images

有关如何为企业选择正确 SKU 的指南

每个企业在成长和发展过程中都有独特的需求。浏览以下指南,从而了解如何从适用于组织的商业模式开始。

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其他资源

Azure AI 搜索

详细了解 Azure AI 搜索 特性和功能。

定价计算器

估计每月使用任何 Azure 产品组合应产生的费用。

SLA

查看 Azure AI 搜索 的服务级别协议。

文档

查看技术教程、视频和更多 Azure AI 搜索 资源。

  • Foundry IQ (Azure AI Search) offers capacity-based tiers with predictable pricing and usage-based tiers with scale to zero pricing. Refer to our documentation for more details on the different tiers and guidance for selecting which plan is right for you.
  • Azure AI Search is available in the new Microsoft Azure portal. First, you must sign up for an Azure subscription, then you can add an Azure AI Search account to your Azure subscription via the gallery in the preview portal. Get more information.
  • Agentic retrieval autonomously decides the best sources and methods for retrieving information, enhancing response quality through reasoning and planning. Semantic ranker improves search relevance by understanding and leveraging the semantics of user queries. Learn more here.

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