Compare LangChain and LangGraph side by side. Both are tools in the Agent Frameworks category.
Updated April 29, 2026
Choose LangChain if largest ecosystem and community in AI application development.
Choose LangGraph if most production-ready open-source agent framework in 2026.
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | Open Source | Free open-source (LangSmith + LangGraph Platform paid) |
| Best For | Developers building complex LLM applications who need a comprehensive orchestration framework | Production engineering teams building reliable, multi-step AI agents at scale with full observability |
| Website | langchain.com | langchain.com |
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Curated quotes from Hacker News, Reddit, Product Hunt, and review blogs. Dates shown so you can judge whether early criticism still applies.
“LangGraph and AutoGen are the only two frameworks with full enterprise certifications as of 2026. LangChain and LangGraph have 90M monthly downloads and power production at Uber, JPMorgan, BlackRock, and Cisco.”
“If the team already has ML/LLM experience, LangGraph pays off in the long run thanks to the maturity of its ecosystem.”
“Lower-level framework designed for highly custom and controllable agents in production-grade scenarios — not the easiest entry point.”
“LangChain 1.0 now uses LangGraph internally — start with the simple LangChain interface and access LangGraph features when you need them.”
Key criteria to evaluate when comparing Agent Frameworks solutions:
LangChain is the most widely adopted framework for building LLM-powered applications and AI agents, founded in 2022 by Harrison Chase. The company provides an open-source Python and TypeScript framework with abstractions for chains, agents, tools, memory, and retrieval that make it easy to compose complex AI systems.
LangGraph, its agent orchestration layer, enables building stateful, multi-actor workflows with human-in-the-loop capabilities. LangSmith provides tracing, evaluation, and monitoring for LLM applications in production. The LangChain ecosystem is the largest in the AI application development space, with the company reaching $16M in revenue and 1,000 customers by 2025.
Backed by $260M in total funding at a $1.25B valuation, LangChain has grown to 199 employees and is headquartered in San Francisco. The company serves as the de facto orchestration layer for teams building production AI applications.
LangGraph is LangChain's graph-based orchestration framework for building stateful, multi-step AI agents. Unlike linear chains, LangGraph models agent workflows as directed graphs with nodes (functions or LLM calls) and edges (conditional routing), enabling cycles, branching, parallel execution, and durable state across long-running interactions.
Together, LangChain and LangGraph have 90M monthly downloads and power production applications at Uber, JPMorgan, BlackRock, and Cisco. LangGraph 1.0 (released 2026) added enterprise certifications, durable execution with checkpointing, time-travel debugging, and human-in-the-loop interrupts. LangChain 1.0 now uses LangGraph under the hood — start with the simple LangChain API and drop down to LangGraph for advanced control when needed.
LangGraph is fully MIT-licensed open-source and free. LangSmith (the observability and eval companion) and LangGraph Platform (managed deployment) are paid SaaS offerings on top. Positioned as the production-control framework for teams that need reliability, observability, and durability — the most enterprise-ready open-source agent framework in 2026.
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
Browse all Agent Frameworks tools →