LangGraphFreemium
A low-level orchestration framework for building stateful, multi-step agent workflows with explicit control over state, branching, and human-in-the-loop steps.
AI / LLM comparison
LangGraph vs Microsoft AutoGen
Pricing, pros, cons, and ideal use cases — side by side.
An open-source framework from Microsoft Research for building multi-agent applications, where agents converse to solve tasks together.
At a glance
| LangGraph | Microsoft AutoGen | |
|---|---|---|
| Pricing | FreemiumOpen-source framework, free to use. Paid tiers apply to the surrounding LangSmith platform, not the framework itself. | FreeOpen-source (MIT), free to use. You pay only for the underlying model API calls. |
| Category | AI / LLM | AI / LLM |
| Ideal for | Engineering teams building multi-step agentsEnterprise platform teamsWorkflows needing human-in-the-loop control | Engineering teams prototyping multi-agent systemsResearch and innovation groupsTeams already in the Microsoft ecosystem |
Pros & cons
LangGraph
Pros
- Explicit control over agent state and branching
- First-class human-in-the-loop and checkpointing
- Strong fit for durable, long-running workflows
- Large ecosystem and active development
Cons
- Requires real engineering investment
- Lower-level than no-code agent builders
- You own deployment and observability
Microsoft AutoGen
Pros
- Mature multi-agent conversation patterns
- Backed by Microsoft Research
- Flexible high-level and low-level APIs
- Strong fit for experimentation
Cons
- Multi-agent conversations are hard to evaluate and debug
- Token costs can escalate without guardrails
- APIs have changed significantly between versions
Which should you choose?
Microsoft AutoGen is the lighter-weight option (Free), while LangGraph sits higher on the pricing ladder (Freemium). LangGraph is built around engineering teams building multi-step agents; Microsoft AutoGen leans more toward engineering teams prototyping multi-agent systems. Shortlist the one whose strengths line up with your biggest constraint.