LangGraph vs Vellum
A side-by-side comparison of two ai agents tools — pricing, integrations, and the trade-offs that matter — so you can pick the right fit fast.
| Feature | LangGraph | Vellum |
|---|---|---|
| Category | AI Agents | AI Agents |
| Pricing | Freemium · from Free | Paid · from Custom pricing |
| Best for | Developers | Developers, Product Managers |
| Use cases | Building stateful, multi-step agent applications, Designing complex agent logic with branching and loops, Creating production-grade controllable AI agents | Testing and evaluating prompts systematically, Building production-grade LLM applications, Iterating on AI agent workflows before deployment |
| Integrations | LangChain, OpenAI API, Anthropic API | OpenAI API, Anthropic API, API |
| Rating | — | — |
| Website | Visit LangGraph | Visit Vellum |
LangGraph
Framework for building stateful, multi-agent AI workflows with LangChain.
Pros
- +Graph-based structure makes complex agent logic easier to control
- +Supports persistent state across multi-step workflows
- +Backed by the widely adopted LangChain ecosystem
Cons
- –Requires familiarity with graph-based programming concepts
- –Steeper learning curve than simpler linear agent frameworks
Vellum
Development platform for building, testing, and deploying production LLM agents.
Pros
- +Provides systematic prompt testing and evaluation tools
- +Helps teams iterate on agent workflows before production deployment
- +Built specifically for production LLM application development
Cons
- –Most valuable for teams building and iterating on LLM apps regularly
- –Requires some technical setup to integrate into existing pipelines
LangGraph vs Vellum FAQ
- Is LangGraph better than Vellum?
- Neither is universally better — both are ai agents tools. LangGraph (Freemium, from Free) is a strong fit for Building stateful, multi-step agent applications, while Vellum (Paid, from Custom pricing) suits Testing and evaluating prompts systematically. Pick by your primary use-case and budget.
- What is the main difference between LangGraph and Vellum?
- LangGraph focuses on "Framework for building stateful, multi-agent AI workflows with LangChain." whereas Vellum focuses on "Development platform for building, testing, and deploying production LLM agents.". Their pricing starts at Free and Custom pricing respectively.
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