LangGraph vs 
AG2
LangGraph vs AG2 compared for 2026 — features, license, ease of use, performance and which one to choose. Stateful, controllable agent graphs vs The community continuation of AutoGen.
Updated regularly · curated by OpenSourceAI.tech
LangGraph vs AG2 at a glance
| Spec | LangGraph | AG2 |
|---|---|---|
| Category | AI agent framework | AI agent framework |
| Type | Agent orchestration (graphs) | Multi-agent framework |
| License | MIT | Apache-2.0 |
| Runs locally | Cloud-optional | Cloud-optional |
| Primary language | Python / JS | Python |
| Ease of use | Advanced | Intermediate |
| Best for | developers needing controllable agent workflows | teams invested in the AutoGen conversation model |
| GitHub stars | 37.1k | 4.8k |
How LangGraph and AG2 score
| Criterion | LangGraph | AG2 |
|---|---|---|
| Popularity | 4.0 | 2.5 |
| Maintenance | 5.0 | 5.0 |
| Ease of use | 2.5 | 3.5 |
| Privacy | 3.5 | 3.5 |
| License freedom | 5.0 | 5.0 |
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
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
AG2
AG2 is the community-driven continuation of AutoGen, focused on multi-agent conversations and orchestration with an open governance model.
- Continuity for the AutoGen ecosystem
- Community-governed, Apache-2.0
- Mature multi-agent conversation patterns
Key differences
LangGraph is agent orchestration (graphs), while AG2 is multi-agent framework. Their licenses differ (MIT vs Apache-2.0), which matters if you ship a commercial product. LangGraph leans more advanced-friendly, whereas AG2 is more suited to intermediate users. In short, LangGraph fits developers needing controllable agent workflows, and AG2 fits teams invested in the AutoGen conversation model.
Which should you choose?
Choose LangGraph for developers needing controllable agent workflows. Choose AG2 for teams invested in the AutoGen conversation model.
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 AG2 easier to use?
AG2 is generally the easier of the two to get started with, while LangGraph rewards more setup with more control.
Are LangGraph and AG2 free?
LangGraph is free and open source (MIT), and AG2 is free and open source (Apache-2.0). Neither charges for the core software.
Can I run LangGraph and AG2 locally?
LangGraph: cloud-optional · AG2: cloud-optional. Both can be used without sending your data to a third-party cloud where their setup allows.
LangGraph vs AG2 — which should I pick in 2026?
Choose LangGraph for developers needing controllable agent workflows. Choose AG2 for teams invested in the AutoGen conversation model.
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