LangGraph vs OpenAI Agents SDK

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-09-29
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At a glance

DimensionLangGraphOpenAI Agents SDK
Pricingfreemium · from Developer $0/seat per monthfree · from Open Source (MIT) $0
Best forBackend and platform engineers building production agents, Teams needing fine-grained control over agent workflowsPython developers building multi-agent workflows with OpenAI models, Teams automating code review, file inspection, and command execution with SandboxAgent
Standout featuresGraph-based state management for agent control flow · Human-in-the-loop checkpoints to steer and approve agent actions · Built-in memory storing conversation histories across sessionsAgents as LLMs configured with instructions, tools, guardrails, and handoffs · SandboxAgent runs in a container to inspect files, run commands, apply patches, and preserve workspace state · RealtimeAgent for low-latency server-side voice and multimodal sessions over WebSocket
Viability score81/10078/100
APIYesYes

LangGraph is the stronger pick for backend and platform engineers building production agents; OpenAI Agents SDK fits better for python developers building multi-agent workflows with openai models.

Built from live tool data, last verified 2026-09-29.

LangGraph
LangGraph

MIT-licensed agent runtime and low-level orchestration framework for building reliable, stateful AI agents.

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OpenAI Agents SDK
OpenAI Agents SDK

Free MIT-licensed Python framework for multi-agent workflows with handoffs, guardrails, sandbox agents, and voice agents.

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Pricing
Freemium
Free
Plans
$0/seat per month
$39/seat per month
Custom
$0
Popularity
3.1k views
6.1k views
Skill Level
Advanced
Intermediate
API Available
Platforms
API
WebAPI
Categories
🕸️ Agent Frameworks & Orchestration📡 LLM Observability & Evals
🕸️ Agent Frameworks & Orchestration
Features
Graph-based state management for agent control flow
Human-in-the-loop checkpoints to steer and approve agent actions
Built-in memory storing conversation histories across sessions
Token-by-token streaming of agent reasoning and actions
Single-agent, multi-agent, and hierarchical architectures in one framework
Low-level primitives for fully custom agent design
Model-agnostic: works with any LLM provider
Sandboxed code execution for agent-generated code
Prompt caching
Agent self-evaluation
MCP support including stateless protocol and elicitation
Integrates with the Deep Agents harness for long-running tasks
LangSmith observability, tracing, and evaluation
LLM Gateway runtime controls: cost limits, rate limiting, fallbacks, PII redaction
Deployment with scale-to-zero and cron scheduling
Agents as LLMs configured with instructions, tools, guardrails, and handoffs
SandboxAgent runs in a container to inspect files, run commands, apply patches, and preserve workspace state
RealtimeAgent for low-latency server-side voice and multimodal sessions over WebSocket
Realtime agents built on gpt-realtime-2.1 with full agent feature set
VoicePipeline chains speech-to-text, an agent workflow, and streaming text-to-speech
Agent handoffs and agents-as-tools for hierarchical delegation
Configurable input and output guardrails for safety validation
Human-in-the-loop checkpoints across agent runs
Automatic conversation history management via sessions
Optional Redis-backed session persistence
Built-in tracing to view, debug, and optimize agent runs
MCP tool integration for external tools and data
Provider-agnostic via LiteLLM across 100+ LLMs
Supports OpenAI Responses and Chat Completions APIs
Install via pip or uv; Python 3.10 or newer required
Integrations
OpenAI
Anthropic
Google
Ollama
Azure
AWS Bedrock
HuggingFace
Fireworks
Baseten
Mistral
Meta
OpenRouter
NVIDIA
GitHub
Redis
Docker
LiteLLM

What real users say: LangGraph vs OpenAI Agents SDK

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

LangGraph

117 mentions across 6 sources · 53% positive — mixed (averaged across 6 sources)

Hacker News, YouTube, Bluesky, Stack Overflow, GitHub, Lemmy

What users praise

  • • Fine-grained control over agent workflows and state transitions.
  • • Excellent for building complex multi-agent and hierarchical systems.
  • • Human-in-the-loop checks provide reliable agent moderation.
  • • Graph-based orchestration makes deterministic workflows intuitive.

What frustrates them

  • • Steep learning curve and API confusion for new users.
  • • Gets complicated fast for simple or single-agent tasks.
  • • Long tool calls silently re-execute on cloud, wasting cost.
  • • Security vulnerabilities can expose files and secrets.

Researched Jul 25, 2026

OpenAI Agents SDK

70 mentions across 4 sources · 64% positive — mixed (weighted across 4 sources)

Hacker News, YouTube, Product Hunt, Lemmy

What users praise

  • • Lean, low-boilerplate orchestration compared with LangChain and AutoGen, with far fewer abstractions to learn
  • • Provider-agnostic via LiteLLM across 100+ LLMs, so teams aren't locked into OpenAI models
  • • Sandbox harness for file inspection, command execution, and patch application ships out of the box
  • • Guardrails for input and output validation are first-class, not an afterthought bolted on later

What frustrates them

  • • Narrower than LangChain or AutoGen — no sprawling integration catalog when you need exotic connectors
  • • Documentation is largely OpenAI-authored, so community troubleshooting resources are thinner than competitors'
  • • Optional extras like voice and Redis sessions add dependency and setup complexity teams underestimate
  • • Sandbox provider abstraction is unclear — reviewers can't tell if you're locked into one per run

Researched Sep 29, 2026

Frequently Asked Questions

Which is better, LangGraph or OpenAI Agents SDK?

The best choice between LangGraph and OpenAI Agents SDK depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.

What are the main differences between LangGraph and OpenAI Agents SDK?

The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.

Is there a free version of LangGraph or OpenAI Agents SDK?

Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.

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Last reviewed: May 12, 2026