LangGraph vs OpenAI Agents SDK
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | LangGraph | OpenAI Agents SDK |
|---|---|---|
| Pricing | Free (MIT License) | Free (MIT License) |
| Core Architecture | Graph-based state machines | Agent-based with handoffs & delegation |
| Best for | Production-grade, stateful multi-agent systems | Rapid prototyping with OpenAI models |
| Key Differentiator | Human-in-the-loop, fault tolerance, prompt caching | Sandbox Agents & Realtime Agents (voice) |
| LLM Support | All major providers (OpenAI, Anthropic, Google, etc.) | 100+ via LiteLLM; native OpenAI |
| Observability | LangSmith integration for monitoring & evaluation | Built-in tracing |
Choose OpenAI Agents SDK if you're prototyping multi-agent workflows with OpenAI models or need Sandbox Agents for containerized code execution. Choose LangGraph if you need battle-tested production reliability, human-in-the-loop controls, and fine-grained graph-based state management—especially for enterprise deployment.
Open-source framework for building reliable, stateful AI agents with low-level control.
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Open-source Python framework for building multi-agent workflows with handoffs, guardrails, and voice.
Visit WebsiteWho should pick which
- Solo founder prototyping a multi-agent Python app with OpenAIPick: OpenAI Agents SDK
Quick setup, native OpenAI integration, and Sandbox Agents for code execution out of the box.
- Enterprise DevOps engineer building a reliable stateful agentPick: LangGraph
LangGraph offers human-in-the-loop, fault tolerance, and LangSmith integration for production monitoring.
- Researcher experimenting with agent handoffs and guardrailsPick: OpenAI Agents SDK
Designed for rapid iteration with built-in tracing and guardrails; ideal for experimentation.
- Multi-agent system architect needing fine-grained controlPick: LangGraph
Graph-based state machines allow custom workflows and complex agent hierarchies.
- Developer building a voice assistant using gpt-realtime-2Pick: OpenAI Agents SDK
Realtime Agents in v0.17.6+ directly support gpt-realtime-2 voice integration.
Frequently Asked Questions
LangGraph vs OpenAI Agents SDK: which should you choose?
Choose OpenAI Agents SDK if you're prototyping multi-agent workflows with OpenAI models or need Sandbox Agents for containerized code execution. Choose LangGraph if you need battle-tested production reliability, human-in-the-loop controls, and fine-grained graph-based state management—especially for enterprise deployment.
Which tool is better for production use?
LangGraph, with its fault tolerance, human-in-the-loop, and enterprise backing (Lyft, United Airlines).
Can OpenAI Agents SDK be used with non-OpenAI models?
Yes, via LiteLLM integration supporting 100+ LLMs.
Does LangGraph support voice agents?
Not natively; it focuses on text-based stateful agents. Voice would require additional TTS/ASR integration.
What is a Sandbox Agent?
A feature in OpenAI Agents SDK (v0.14.0+) that runs containerized tasks with filesystem and command execution for safe code review.
What is prompt caching in LangGraph?
Introduced June 2026, it reduces latency and cost by reusing cached prompt results across sessions in Deep Agents.
Which tool is easier to learn?
OpenAI Agents SDK, with a simpler agent-based API. LangGraph's graph paradigm requires more upfront investment.
Can I add human oversight in OpenAI Agents SDK?
Yes, it includes human-in-the-loop mechanisms, but LangGraph's implementation is more mature and configurable.
Do these tools require LangSmith?
No, but LangSmith is recommended for LangGraph for observability and evaluation. OpenAI Agents SDK has built-in tracing.
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Last reviewed: May 12, 2026