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Pricing sourced from Microsoft AutoGen · Last verified March 2026
Microsoft has been developing the Azure AI Agent Service and related agent tooling. AutoGen remains available as an open-source multi-agent framework. Check Microsoft's official documentation for the latest on how these projects relate.
Based on our testing, AutoGen excels at complex multi-agent orchestration with its event-driven architecture, cross-language support, and deep Azure integration. It has a steeper learning curve than CrewAI but offers more flexibility for advanced use cases.
Yes, AutoGen is fully open-source under the MIT license. You can use it freely for commercial and non-commercial projects. Azure AI Foundry hosting is a separate paid service.
Use v0.4 for new projects. It features a completely redesigned async architecture, better observability, and improved extensibility. v0.2 is the legacy version.
AutoGen works with OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, Mistral, and local models via Ollama. It uses a model-agnostic interface for easy provider switching.
AI builders and operators use Microsoft AutoGen to streamline their workflow.
Try Microsoft AutoGen Now →Microsoft's unified open-source framework for building AI agents and multi-agent systems, combining AutoGen's multi-agent patterns with Semantic Kernel's enterprise features into a single Python and .NET SDK.
Compare 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.
Compare 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.
Compare Pricing →Deprecated educational framework that teaches multi-agent coordination fundamentals through minimal Agent and Handoff abstractions, now superseded by production-ready OpenAI Agents SDK for modern development workflows
Compare Pricing →Revolutionary multi-agent framework that automates complete software development lifecycles by orchestrating specialized AI agents in product manager, architect, engineer, and QA roles to generate production-ready code from single prompts.
Compare Pricing →LlamaIndex: Build and optimize RAG pipelines with advanced indexing and agent retrieval for LLM applications.
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