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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".

探索定價選項

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

價格僅為估算值,並非實際價格報價。實際定價可能會根據與 Microsoft 簽訂的合約類型、購買日期和目前貨幣匯率而有所不同。價格是根據美元計算,並使用前一個月底最後一個工作天之前兩個工作天內擷取的倫敦即期匯率進行轉換。如果月底的前兩個工作天是主要市場中的銀行假日,則匯率設定日期通常為兩個工作天之前的那一天。此匯率適用於下個月的所有交易。登入 Azure 定價計算機查看依據您目前 Microsoft 方案/供應項目所訂的定價。如需定價的詳細資訊或要求報價,請連絡 Azure 銷售專員。請參閱 Azure 定價常見問題集。

Dedicated pricing

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

免費 基本 標準 S1 標準 S2 標準 S3 儲存體最佳化 L1 儲存體最佳化 L2
儲存體1 50 MB 15GB
(每項服務最多 45GB)
160GB
(每項服務最多 1.9 TB)
512GB
(每項服務最多 6 TB)
1 TB
(每項服務最多 12 TB)
2 TB
(每項服務最多 24 TB)
4 TB
(每項服務最多 48 TB)
每項服務的索引上限 3 15 50 200 200 或高密度模式中每分割區 1,000 10 10
擴增規模限制 N/A 每項服務最多 9 個單位
(最多 3 個分割區;最多 3 個複本)
每項服務最多 36 個單位
(最多 12 個分割區;最多 12 個複本)
每項服務最多 36 個單位
(最多 12 個分割區;最多 12 個複本)
每項服務最多 36 個單位
(最多 12 個分割區;最多 12 個複本)
高密度 2 模式中最多 3 個分割磁碟
每項服務最多 36 個單位
(最多 12 個分割區;最多 12 個複本)
每項服務最多 36 個單位
(最多 12 個分割區;最多 12 個複本)
計算類型為預設
每個搜尋單位 (Search Unit) 的價格
$- $- $- $- $- $- $-
計算類型為機密3
每個搜尋單位 (Search Unit) 的價格
$- $- $- $- $- $- $-

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
語意排名工具
1k requests
First 1k requests free per month
$- per 1k requests
自訂實體查閱技能
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
文件萃取:影像擷取
1k transactions (t)
$- per 1k t | 0-1M images
$- per 1k t | 1M-5M images
$- per 1k t | 5M+ images

如何為公司選取正確 SKU 的指導方針

每家企業隨著成長和演進,都有獨特的需求。探索下列指導方針,了解如何從適合您組織的商務模式開始。

Azure 定價與購買選項

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其他資源

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定價計算機

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SLA

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文件

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  • 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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