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 OpenAI AgentKit
Pricing, pros, cons, and ideal use cases — side by side.
OpenAI AgentKitFreemium
OpenAI first-party agent toolkit — a visual Agent Builder, embeddable ChatKit UI, a connector registry, and evals, billed at plain API rates.
At a glance
| LangGraph | OpenAI AgentKit | |
|---|---|---|
| Pricing | FreemiumOpen-source framework, free to use. Paid tiers apply to the surrounding LangSmith platform, not the framework itself. | FreemiumNo separate platform fee. Agent Builder design is free; you pay standard OpenAI API model and storage rates for execution. As a reference point, GPT-5.2 runs roughly $1.75 per million input tokens and $14 per million output tokens, with GPT-5 mini at about $0.25 per million input tokens. |
| Category | AI / LLM | AI / LLM |
| Ideal for | Engineering teams building multi-step agentsEnterprise platform teamsWorkflows needing human-in-the-loop control | Product teams embedding agents into their own softwareEngineering teams already building on the OpenAI APIStartups that want agent scaffolding without a platform feeTeams standardizing evals alongside agent development |
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
OpenAI AgentKit
Pros
- No platform fee on top of API usage
- Visual workflow builder with versioning
- ChatKit ships a production-ready chat UI
- Evals are first-class rather than an afterthought
- Cost model is the API cost model you already forecast
Cons
- Single-provider lock-in at the orchestration layer
- Agent Builder and Connector Registry have been in beta rather than fully GA
- Fewer enterprise governance controls than Copilot Studio or Agentforce
- No managed hosting story comparable to Bedrock AgentCore
Which should you choose?
LangGraph is built around engineering teams building multi-step agents; OpenAI AgentKit leans more toward product teams embedding agents into their own software. Shortlist the one whose strengths line up with your biggest constraint.