LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.
LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.
LangGraph is the agent framework from the LangChain team, designed for stateful multi-agent applications where vanilla chains run out of expressiveness. Where LangChain models AI work as a linear chain, LangGraph models it as a directed graph: nodes are functions or LLM steps, edges define conditional control flow, and state is a first-class object that persists across steps with checkpointing. That makes LangGraph the right choice for agent loops with branching (router patterns), human-in-the-loop pauses (resume from checkpoint), durable long-running tasks (server-side persistence), and supervisor/worker multi-agent topologies. LangGraph is open source and free in code form; the optional LangGraph Platform adds managed deployments, observability via LangSmith, and a hosted server. Pricing follows LangChain's standard tiers: Developer at $0/seat/month (5k base traces/mo, 1 free dev deployment), Plus at $39/seat/month (10k base traces/mo, 1 free dev-sized agent deployment, unlimited seats), and Enterprise custom (advanced security, on-prem, dedicated support). Usage adds $2.50 per 1k LangSmith base traces, $0.0036/min for production deployments, $0.0007/min for dev deployments, and $1.50 per LCU (LangChain Compute Unit) for engine execution.
Was this helpful?
LangGraph is the most production-ready agent orchestration framework available, offering fine-grained control over agent state, deterministic execution paths, and enterprise-grade observability through LangSmith. With over 12,000 GitHub stars and adoption by companies like Klarna, Replit, and LinkedIn, it has proven its reliability at scale. The trade-off is a steeper learning curve and more boilerplate compared to higher-abstraction alternatives, making it best suited for teams that prioritize auditability, compliance, and production reliability over rapid prototyping speed.
Free
$0/seat/month
$39/seat/month
Custom
Ready to get started with LangGraph?
View Pricing Options →LangGraph works with these platforms and services:
We believe in transparent reviews. Here's what LangGraph doesn't handle well:
Weekly insights on the latest AI tools, features, and trends delivered to your inbox.
Through 2025 and into 2026, LangGraph has continued to mature into one of the most widely adopted production agent frameworks. Recent updates include the introduction of the interrupt() primitive for more ergonomic human-in-the-loop workflows, long-term semantic memory with cross-thread persistence, MCP (Model Context Protocol) support for standardized tool interoperability, background run mode for fire-and-forget tasks, and significant performance optimizations to the checkpointing layer. The LangGraph Platform added cron-based scheduled assistants, webhook triggers, and improved Studio debugging capabilities. GitHub stars have surpassed 12,000 and PyPI weekly downloads exceed 150,000 as of early 2026.
Battle-Tested Blueprints for Real Systems
What you'll learn:
Multi-Agent Builders
Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.
AI Agents
Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.
Enterprise Agents
Enterprise durable execution platform designed for AI agent orchestration with guaranteed reliability, state management, and human-in-the-loop workflows.
No reviews yet. Be the first to share your experience!
Get started with LangGraph and see if it's the right fit for your needs.
Get Started →Take our 60-second quiz to get personalized tool recommendations
Find Your Perfect AI Stack →Explore 20 ready-to-deploy AI agent templates for sales, support, dev, research, and operations.
Browse Agent Templates →Learn LangGraph from scratch. Build stateful AI agent workflows with cycles, branching, persistence, human-in-the-loop, and multi-agent coordination — with real Python code examples.
A hands-on comparison of the top AI agent frameworks — CrewAI, LangGraph, OpenAI Agents SDK, AutoGen, Google ADK, and more. Real code examples, setup times, and production guidance for builders.
A comprehensive guide to multi-agent AI systems: what they are, why they outperform single agents, the five core architecture patterns, and how to choose the right framework. Practical advice for builders.
Build production-ready multi-agent AI systems from scratch. Covers architecture selection, agent design, orchestration, tool integration, and deployment with CrewAI, LangGraph, and AutoGen.