LangChainvsMicrosoft AutoGen

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

LangChain

AI Agent Frameworks

Framework for building applications with large language models

Microsoft AutoGen

AI Agent Frameworks

Featured

Framework for building multi-agent conversational AI

FeatureLangChainMicrosoft AutoGen
CategoryAI Agent FrameworksAI Agent Frameworks
PricingFree + LangSmith paidFree (open-source)
GitHub Stars
More stars
98k
35k
PlatformsmacOS, Linux, WindowsLinux, macOS, Windows
Key Features
  • Chain composition
  • RAG pipelines
  • Agent toolkits
  • Memory systems
  • Streaming
  • Multi-model
  • LangGraph
  • Multi-agent conversations
  • Code execution
  • Human-in-the-loop
  • Customizable
  • Group chat
Pros
  • + Massive ecosystem and community
  • + Modular and composable
  • + Supports every major LLM provider
  • + Excellent documentation
  • + LangSmith for monitoring
  • + Strong multi-agent conversation support
  • + Code execution built-in
  • + Human-in-the-loop capability
  • + Microsoft backing
  • + Research-grade quality
Cons
  • Can be overly complex for simple tasks
  • Frequent breaking changes
  • Abstraction overhead
  • Steep learning curve
  • Complex API for beginners
  • Heavy dependency tree
  • Documentation could be better
  • Resource intensive
Tags
open-sourceframeworkpythonjavascriptragchains
multi-agentmicrosoftconversationsopen-source

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