LangChain / LangGraph vs OpenAI Agents SDK
Side-by-side comparison of LangChain / LangGraph and OpenAI Agents SDK. Pricing, features, best use cases, and honest verdict from a developer who has tested both.
LangChain / LangGraph
Most popular LLM framework. 100K+ GitHub stars. Chains, RAG, vector stores, tool use. LangGraph adds stateful multi-agent workflows with cycles and persistence.
OpenAI Agents SDK
Lightweight Python framework for multi-agent systems. Agent handoffs, tool use, guardrails, tracing. Successor to the experimental Swarm project.
Feature Comparison
| Feature | LangChain / LangGraph | OpenAI Agents SDK |
|---|---|---|
| Category | AI Frameworks | AI Frameworks |
| Type | SDK / Framework | SDK / Framework |
| Pricing | See website for pricing | See website for pricing |
| Best For | RAG, chains, and stateful agent workflows | Lightweight multi-agent orchestration |
| Language / Platform | Python | Python |
| Open Source | No | No |
In Depth
LangChain / LangGraph
LangChain is the most popular framework for building LLM applications, with over 100K GitHub stars. It provides abstractions for chains (sequential LLM calls), RAG (retrieval-augmented generation with any vector store), tool use, and output parsing. LangGraph extends it with stateful, graph-based workflows - agents that can loop, branch, and persist state across interactions. Their latest push is 'Deep Agents' for autonomous coding. LangSmith provides observability and tracing. The ecosystem is massive - integrations with every model provider, vector database, and tool imaginable. I cover LangChain in my AI Agent Frameworks course.
OpenAI Agents SDK
The OpenAI Agents SDK (the production successor to Swarm) is a minimal Python framework for building multi-agent systems. Core concepts: Agents (an LLM + instructions + tools), Handoffs (agents delegating to specialists), Guardrails (input/output validation), and Tracing (built-in observability). It's deliberately lightweight - no heavy abstractions or state management. You define agents as simple Python objects, wire them together with handoffs, and the SDK handles the orchestration. It works with any OpenAI model and supports streaming. Good for building customer service bots, research agents, and workflow automation.
The Verdict
Both LangChain / LangGraph and OpenAI Agents SDK are strong tools in the ai frameworks space. The right choice depends on your workflow. Read the full review of each tool for a deeper dive, or watch the video walkthroughs to see them in action.