LangChain vs LangGraph

Choose LangChain if…

Best for developers building custom applications on top of large language models, and its edge is composable chains, agents, and memory abstractions that cut LLM app code from hundreds of lines to dozens. The standard starting framework for LLM app development, expect the API to keep shifting under you. Lean toward LangGraph instead if graph visualization makes complex agent logic debuggable in a way a purely sequential framework can't match matters more for your use case.

Choose LangGraph if…

Best for developers building agent workflows that need loops, branching, or human-in-the-loop checkpoints, and its edge is graph visualization makes complex agent logic debuggable in a way a purely sequential framework can't match. The right tool once your agent logic outgrows a simple pipeline, overkill for a straightforward linear task. Lean toward LangChain instead if composable chains, agents, and memory abstractions that cut LLM app code from hundreds of lines to dozens matters more for your use case.