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Stateful agent orchestration runtime

LangGraph

A low-level open-source graph runtime for long-running stateful agents with explicit nodes, transitions, persistence, interrupts, and streaming.

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Editorial verdict

Choose LangGraph when durable state, explicit transitions, human interruption, and replay are central requirements. Prefer a smaller loop or deterministic workflow when a graph would add more lifecycle than control.123

Best for

  • Long-running stateful agent workflows
  • Teams needing explicit graph transitions and human interruption
  • Systems prepared to design durable checkpoints and idempotent side effects
123

Not ideal for

  • Simple model-and-tool loops
  • Teams seeking a high-level agent abstraction with little state design
  • Projects unwilling to own checkpoint schema and deployment lifecycle
123
Main trade-off

Explicit graph state improves control and recovery while increasing graph design, checkpoint, schema migration, idempotency, deployment, and observability responsibilities.123

Product boundary

Whether explicit graph state, checkpointing, interruption, and replay justify a low-level orchestration runtime.

LangGraph is an orchestration runtime, not a model provider, evaluation proof, safe tool layer, or managed persistence service by default. LangSmith observability and deployment are separately priced and governed.123

For: Teams building complex stateful agent workflows that can own graph design, persistence, idempotency, deployment, and migration

  • A deterministic workflow or minimal tool loop is sufficient
  • The team cannot own checkpoint and state-schema evolution
  • A higher-level framework better matches language and deployment constraints

Why teams consider LangGraph

  • Durable executionCheckpointed state can support resume, recovery, memory, and human-in-the-loop workflows.123
  • Explicit controlNodes, edges, state, and interrupts make orchestration paths inspectable.123
  • Deployment choiceThe open-source runtime can be operated independently or paired with separately governed LangSmith services.123

Pricing

The open-source runtime has no separate software fee. Self-operation requires persistence and compute; LangSmith adds seat, trace, compute, storage, deployment, and enterprise dimensions.4

Current decision boundary

Open-source runtime with optional LangSmith services

Verified 2026-07-27: LangGraph is open source, while current LangSmith plans combine included usage with seat and metered compute, trace, and storage dimensions.4

Framework
Open-source runtime4
Managed route
LangSmith plan and usage meters are separate4
Owned cost
Checkpoint storage, workers, model calls, and operations4
Pricing checked View official pricing

LangGraph vs alternatives

OpenAI Agents SDK

Choose when
OpenAI-aligned agent applications needing a focused runtime
Avoid when
Deterministic workflows that do not need model-directed control
Compared with LangGraph
A focused runtime removes agent-loop plumbing while adding SDK, model, tool-safety, session, tracing-data, and provider dependencies.567

CrewAI

Choose when
Python teams testing role-based agent collaboration
Avoid when
Tasks solved reliably by one model call or deterministic workflow
Compared with LangGraph
Role-oriented composition can accelerate multi-agent experiments while increasing token use, latency, nondeterminism, delegation failure, tracing, and platform complexity.8910

Mastra

Choose when
TypeScript agent products needing integrated workflows and memory
Avoid when
Bounded model-and-tool loops
Compared with LangGraph
An integrated TypeScript framework reduces assembly work while adding framework, storage, memory, tracing, gateway, managed-platform, and upgrade dependencies.111213

Resources and sources

Official product, pricing, policy, and lifecycle sources

  • LangGraph overview
    Open
  • LangGraph persistence
    Open
  • LangGraph license
    Open
  • LangSmith plans and pricing
    Open

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