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← Back to Azure AI Agent Service Overview

Azure AI Agent Service Pricing & Plans 2026

Complete pricing guide for Azure AI Agent Service. Compare all plans, analyze costs, and find the perfect tier for your needs.

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💎3 Paid Plans
⚡No Setup Fees

Choose Your Plan

Pay-As-You-Go

Usage-based, no upfront cost

mo

  • ✓Model token charges at standard Azure OpenAI rates (e.g., GPT-4o: $2.50 per 1M input tokens, $10 per 1M output tokens)
  • ✓No separate agent orchestration fee
  • ✓Tool invocation charges based on Azure Functions and Logic Apps consumption pricing
  • ✓Managed memory included during public preview at no additional cost
  • ✓Access to Foundry portal no-code builder and playground
  • ✓Traces and observability included
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Most Popular

Agent Commit Units (ACUs)

Pre-purchase commitments starting at $5,000/month with tiered volume discounts off pay-as-you-go rates

mo

  • ✓Discounted per-token rates for committed monthly spend
  • ✓Tiered discounts scaling with commitment level: savings increase at higher spend tiers ($5K/mo, $25K/mo, $100K+/mo)
  • ✓Applies across all Azure AI Agent Service consumption including model tokens and tool calls
  • ✓Predictable monthly billing for high-volume enterprise workloads
  • ✓Available through Azure Enterprise Agreements
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Managed Hosting Runtime (Expected 2026)

Compute-based billing for hosted agent deployments (pricing TBD at GA)

mo

  • ✓Managed runtime for LangGraph, Semantic Kernel, and Agent Framework code
  • ✓Serverless scaling with per-invocation billing
  • ✓VNet isolation for enterprise security requirements
  • ✓Integrated with ACU discounts for combined savings
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Pricing sourced from Azure AI Agent Service · Last verified March 2026

Feature Comparison

FeaturesPay-As-You-GoAgent Commit Units (ACUs)Managed Hosting Runtime (Expected 2026)
Model token charges at standard Azure OpenAI rates (e.g., GPT-4o: $2.50 per 1M input tokens, $10 per 1M output tokens)✓✓✓
No separate agent orchestration fee✓✓✓
Tool invocation charges based on Azure Functions and Logic Apps consumption pricing✓✓✓
Managed memory included during public preview at no additional cost✓✓✓
Access to Foundry portal no-code builder and playground✓✓✓
Traces and observability included✓✓✓
Discounted per-token rates for committed monthly spend—✓✓
Tiered discounts scaling with commitment level: savings increase at higher spend tiers ($5K/mo, $25K/mo, $100K+/mo)—✓✓
Applies across all Azure AI Agent Service consumption including model tokens and tool calls—✓✓
Predictable monthly billing for high-volume enterprise workloads—✓✓
Available through Azure Enterprise Agreements—✓✓
Managed runtime for LangGraph, Semantic Kernel, and Agent Framework code——✓
Serverless scaling with per-invocation billing——✓
VNet isolation for enterprise security requirements——✓
Integrated with ACU discounts for combined savings——✓

Is Azure AI Agent Service Worth It?

✅ Why Choose Azure AI Agent Service

  • • No separate orchestration fee — you pay only for model tokens and tool invocations, reducing the cost premium over self-hosted alternatives like LangGraph
  • • Strong developer experience with Traces debugging, integrated playground testing, and streamlined onboarding that compares favorably to AWS Bedrock based on community developer feedback
  • • Dual no-code and code-based deployment lets teams prototype in the Foundry portal and scale to LangGraph, Semantic Kernel, or Agent Framework agents on the same infrastructure
  • • Managed long-term memory (public preview) eliminates weeks of custom memory infrastructure work that LangGraph and CrewAI teams typically build themselves
  • • Agent Commit Units provide predictable pre-purchase volume discounts unique to Azure — no equivalent agent-specific discount mechanism exists on AWS Bedrock or Google Vertex AI Agent Builder
  • • Deep Microsoft ecosystem integration: Azure AD, Office 365, SharePoint, and Microsoft 365 Copilot data is accessible without building new auth plumbing, plus Azure's compliance certifications (HIPAA, SOC 2, FedRAMP, ISO 27001)

⚠️ Consider This

  • • Narrower model selection than AWS Bedrock — primarily Azure OpenAI Service models with limited access to open models like Llama and Mistral compared to Bedrock's broader marketplace
  • • Customization ceiling is lower than self-hosted LangGraph for advanced agent behaviors requiring fine-grained orchestration control
  • • Enterprise Azure AI pricing at scale can exceed open-source alternatives — cost projections are essential before committing to high-volume workloads
  • • Managed hosting runtime billing timeline is still evolving, creating pricing uncertainty for teams committing to hosted agent deployments today
  • • Strongest value proposition requires existing Microsoft/Azure ecosystem investment — less compelling for AWS-native or multi-cloud organizations

What Users Say About Azure AI Agent Service

👍 What Users Love

  • ✓No separate orchestration fee — you pay only for model tokens and tool invocations, reducing the cost premium over self-hosted alternatives like LangGraph
  • ✓Strong developer experience with Traces debugging, integrated playground testing, and streamlined onboarding that compares favorably to AWS Bedrock based on community developer feedback
  • ✓Dual no-code and code-based deployment lets teams prototype in the Foundry portal and scale to LangGraph, Semantic Kernel, or Agent Framework agents on the same infrastructure
  • ✓Managed long-term memory (public preview) eliminates weeks of custom memory infrastructure work that LangGraph and CrewAI teams typically build themselves
  • ✓Agent Commit Units provide predictable pre-purchase volume discounts unique to Azure — no equivalent agent-specific discount mechanism exists on AWS Bedrock or Google Vertex AI Agent Builder
  • ✓Deep Microsoft ecosystem integration: Azure AD, Office 365, SharePoint, and Microsoft 365 Copilot data is accessible without building new auth plumbing, plus Azure's compliance certifications (HIPAA, SOC 2, FedRAMP, ISO 27001)

👎 Common Concerns

  • ⚠Narrower model selection than AWS Bedrock — primarily Azure OpenAI Service models with limited access to open models like Llama and Mistral compared to Bedrock's broader marketplace
  • ⚠Customization ceiling is lower than self-hosted LangGraph for advanced agent behaviors requiring fine-grained orchestration control
  • ⚠Enterprise Azure AI pricing at scale can exceed open-source alternatives — cost projections are essential before committing to high-volume workloads
  • ⚠Managed hosting runtime billing timeline is still evolving, creating pricing uncertainty for teams committing to hosted agent deployments today
  • ⚠Strongest value proposition requires existing Microsoft/Azure ecosystem investment — less compelling for AWS-native or multi-cloud organizations

Pricing FAQ

Can I deploy existing LangGraph agents to Azure AI Agent Service?

Yes. The hosted agents feature supports Microsoft Agent Framework, LangGraph, Semantic Kernel, or custom code deployment on the same managed runtime. You can bring your existing agent codebase and run it on Azure's managed infrastructure without rewriting for Azure-specific orchestration. This dual-path support — no-code in the portal or code-first through hosted agents — is unique among cloud agent platforms and means you are not locked into a single framework or forced to rewrite existing agent logic to benefit from Azure's managed infrastructure, security, and memory capabilities.

How does the no-code agent builder work?

Create prompt-based agents directly in the Microsoft Foundry portal by configuring tools, knowledge sources, and workflows through the UI. You can attach SharePoint sites, Azure AI Search indexes, Bing grounding, OpenAPI tools, and Logic Apps actions without writing code. Deploy with a single click. This path is best suited for simple agents, rapid prototyping, and business teams that need conversational AI without engineering resources. When requirements grow more complex, agents can be transitioned to code-based deployment on the same managed runtime without starting over.

What does the managed memory service include?

Foundry's managed memory, available in public preview, provides automatic extraction of key information from conversations, consolidation across agent sessions, and intelligent retrieval based on the current request context. Agents remember customer preferences, previous requests, and ongoing project state without you building a vector store, summarization pipeline, or custom retrieval logic. This eliminates weeks of infrastructure work that teams using LangGraph or CrewAI typically invest in building and maintaining their own memory systems. The service handles storage, indexing, and context-aware recall natively within the Azure platform.

How does pricing compare to AWS Bedrock Agents?

Both charge for model tokens with no separate orchestration fee. Azure AI Agent Service's GPT-4o pricing runs $2.50/1M input tokens and $10/1M output tokens at pay-as-you-go rates, comparable to Bedrock's Claude and Llama pricing tiers. Azure adds unique value through Agent Commit Units — pre-purchase volume discounts for committed monthly spend starting at $5,000/month. AWS counters with a broader model marketplace. For high-volume enterprise workloads, ACU discounts can meaningfully reduce total cost versus Bedrock's strictly pay-as-you-go model.

Does it work with non-Microsoft models?

Foundry Agent Service primarily supports models available through Azure OpenAI Service (GPT-4, GPT-4o, GPT-5 family) plus a curated Foundry Models catalog that includes select Meta Llama, Mistral, and partner models. Model availability is narrower than AWS Bedrock's marketplace. Verify your preferred models are available in your target Azure region before committing, as catalog availability varies by region and new models are added on a rolling basis through the Foundry Models program.

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More about Azure AI Agent Service

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Compare Azure AI Agent Service Pricing with Alternatives

Amazon Bedrock Agents Pricing

Build, deploy, and manage autonomous AI agents that use foundation models to automate complex tasks, analyze data, call APIs, and query knowledge bases — all within the AWS ecosystem with enterprise-grade security.

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LangGraph Pricing

Graph-based workflow orchestration framework for building reliable, production-ready AI agents with deterministic state machines, human-in-the-loop capabilities, and comprehensive observability through LangSmith integration.

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CrewAI Pricing

Open-source Python framework that orchestrates autonomous AI agents collaborating as teams to accomplish complex workflows. Define agents with specific roles and goals, then organize them into crews that execute sequential or parallel tasks. Agents delegate work, share context, and complete multi-step processes like market research, content creation, and data analysis. Supports 100+ LLM providers through LiteLLM integration and includes memory systems for agent learning. Features 48K+ GitHub stars with active community.

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Microsoft Semantic Kernel Pricing

SDK for building AI agents with planners, memory, and connectors. - Enhanced AI-powered platform providing advanced capabilities for modern development and business workflows. Features comprehensive tooling, integrations, and scalable architecture designed for professional teams and enterprise environments.

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