Open-Source AI · AI agent framework

LangGraph vs Letta

LangGraph vs Letta compared for 2026 — features, license, ease of use, performance and which one to choose. Stateful, controllable agent graphs vs Stateful agents with long-term memory.

Updated regularly · curated by OpenSourceAI.tech

Choose LangGraph for developers needing controllable agent workflows. Choose Letta for agents that remember across sessions.

LangGraph vs Letta at a glance

SpecLangGraphLetta
CategoryAI agent frameworkAI agent framework
TypeAgent orchestration (graphs)Agent runtime (memory)
LicenseMITApache-2.0
Runs locallyCloud-optionalSelf-hosted
Primary languagePython / JSPython
Ease of useAdvancedAdvanced
Best fordevelopers needing controllable agent workflowsagents that remember across sessions
GitHub stars38.4k24k

How LangGraph and Letta score

🤝 Too close to call — LangGraph and Letta land within a hair (4.0 vs 4.1 / 5). Pick on fit, not on score.
CriterionLangGraphLetta
Popularity4.03.5
Maintenance5.05.0
Ease of use2.52.5
Privacy3.54.5
License freedom5.05.0

Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.

What each one is

LangGraph

Agent orchestration (graphs) · MIT

LangGraph is a library for building stateful, controllable agents as graphs, giving you fine-grained control over loops, branching and persistence.

  • Explicit, controllable agent state machines
  • Persistence and human-in-the-loop built in
  • Integrates with the LangChain ecosystem
See the LangGraph page →

Letta

Agent runtime (memory) · Apache-2.0

Letta (formerly MemGPT) is a framework and server for building stateful agents with long-term memory that persists across sessions, with a visual agent editor.

  • Persistent long-term agent memory
  • Server with REST API and visual editor
  • Model-agnostic and self-hostable
See the Letta page →

Key differences

LangGraph is agent orchestration (graphs), while Letta is agent runtime (memory). Their licenses differ (MIT vs Apache-2.0), which matters if you ship a commercial product. They also differ in how they run (Cloud-optional vs Self-hosted). In short, LangGraph fits developers needing controllable agent workflows, and Letta fits agents that remember across sessions.

Which should you choose?

Choose LangGraph for developers needing controllable agent workflows. Choose Letta for agents that remember across sessions.

There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.

Frequently asked questions

Is LangGraph or Letta easier to use?

Both sit at a similar level (Advanced). Your choice should come down to fit rather than difficulty.

Are LangGraph and Letta free?

LangGraph is free and open source (MIT), and Letta is free and open source (Apache-2.0). Neither charges for the core software.

Can I run LangGraph and Letta locally?

LangGraph: cloud-optional · Letta: self-hosted. Both can be used without sending your data to a third-party cloud where their setup allows.

LangGraph vs Letta — which should I pick in 2026?

Choose LangGraph for developers needing controllable agent workflows. Choose Letta for agents that remember across sessions.

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