LangGraph vs AutoGen (2026): Microsoft vs LangChain
We tested both LangGraph and Microsoft AutoGen side by side for two weeks.
TL;DR — Key Takeaways
- LangGraph vs Microsoft AutoGen: LangGraph excels at stateful graphs with cycles and branches, Microsoft AutoGen excels at microsoft-backed with quality assurance
- Pricing: LangGraph (Open source, free) vs Microsoft AutoGen (Open source, free)
- Best for general use: LangGraph. Best for general use: Microsoft AutoGen
- Both have free tiers — try both before committing
Business
LangGraph
general use
View full review →VS
Business
Microsoft AutoGen
general use
View full review →At-a-glance comparison
| Feature | LangGraph | Microsoft AutoGen |
|---|---|---|
| Best for | general use | general use |
| Category | Business | Business |
| Pricing | Open source, free | Open source, free |
| Free tier | Yes | Yes |
| Open source | Yes | Yes |
| API available | Check website | Check website |
| Key strength | Stateful graphs with cycles and branches | Microsoft-backed with quality assurance |
| Main drawback | Steep learning curve | Documentation less complete than LangChain |
| Use cases | Multi-agent orchestration, Complex workflows, RAG enhancement, Code execution | Multi-agent collaboration, Code generation and execution, Research prototyping, Task decomposition |
| Website | LangGraph | Microsoft AutoGen |
Overview
LangGraph — LangGraph is an agent orchestration framework from the LangChain team, supporting stateful graphs, cycles, human-in-the-loop, and persistent memory. Ideal for building complex multi-step agent systems with streaming and parallel execution.
Microsoft AutoGen — AutoGen is a multi-agent framework from Microsoft Research that accomplishes complex tasks through agent-to-agent conversations. Supports custom agent roles, tool calling, code execution, and group chat modes. Ideal for research and prototyping.
Pricing comparison
Best for
LangGraph is best for
- Multi-agent orchestration
- Complex workflows
- RAG enhancement
- Code execution
Microsoft AutoGen is best for
- Multi-agent collaboration
- Code generation and execution
- Research prototyping
- Task decomposition
LangGraph: what we liked
- Stateful graphs with cycles and branches
- Native human-in-the-loop support
- Persistent memory and checkpointing
- Deep LangChain ecosystem integration
LangGraph: what we did not like
- Steep learning curve
- Requires Python programming
- Debugging complex agent systems is challenging
Microsoft AutoGen: what we liked
- Microsoft-backed with quality assurance
- Flexible agent role definition
- Built-in code execution sandbox
- Group chat mode for multi-agent discussion
Microsoft AutoGen: what we did not like
- Documentation less complete than LangChain
- Complex configuration
- Performance tuning requires experience
Verdict
Pick LangGraph if you need general use.
Pick Microsoft AutoGen if you need general use.
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