LangGraph vs Suna

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	LangGraph Agents	Suna Agents
Tagline	Stateful, graph-based agent orchestration from LangChain.	Open-source AI command center for deploying a workforce of autonomous agents across your company
Category	Agents	Agents
Pricing	Freemium· Free open-source; LangGraph Platform paid	Freemium· Free ($0, 200 sandbox credits/mo, 3 projects, BYO API keys) / Team ($40 per seat/mo, 2,500 pooled credits/seat, up to 200 projects & 100 seats) / Enterprise (custom, SAML SSO + SCIM, audit logs, flexible deployment, SLA)
Model	BYO (Claude / GPT / open)	Bring-your-own-model (OpenAI GPT, Anthropic Claude, and other providers via API keys or existing subscriptions)
Editorial score	8.8 / 10	—
Use cases	stateful agentshuman-in-loopproduction	Autonomous research and market intelligenceWeb scraping and data enrichment agentsBrowser automation workflowsScheduled report generationSlack and Teams AI assistantsCode review and PR triage botsCustomer support ticket triageCron- and webhook-triggered agent jobsInternal knowledge-base Q&AMulti-agent orchestration at company scale
Pros	Reliable, debuggable agent graphs Built-in persistence + HITL Production-grade Tight LangSmith integration	Fully open source and self-hostable, including air-gapped Docker deployments for regulated environments Bring-your-own-model design works with any LLM provider and can reuse existing ChatGPT/Claude/Cursor subscriptions 3,000+ integrations spanning MCP, OpenAPI, GraphQL, and HTTP, so most SaaS tools are reachable out of the box Git-native workflow (agents as files, isolated sandboxes, reviewed change requests) makes autonomous work auditable Multi-surface access via Slack, Teams, web, and CLI suits real cross-functional teams rather than solo devs Enterprise-grade controls at the top tier: SAML SSO, SCIM directory sync, audit logging, and SLA support Generous free tier plus a flat per-seat price on Team, with pooled credits that scale with headcount
Cons	Steeper learning curve than CrewAI Verbose to set up	Sandbox compute is credit-metered on cloud tiers, so heavy browser-automation runs can burn through allocations quickly Self-hosting is powerful but non-trivial — Docker, secrets management, and connector setup require real DevOps effort You still supply and pay for model API keys separately; the subscription only covers orchestration and sandboxing General-purpose agent framework rather than a tuned vertical tool, so you build the workflows and evals yourself Documentation and community are growing fast but still lag behind more mature closed-source agent platforms
Website	www.langchain.com	www.suna.so

Pick LangGraph if

✅ Reliable, debuggable agent graphs
✅ Built-in persistence + HITL
✅ Production-grade
✅ Tight LangSmith integration

Pick Suna if

✅ Fully open source and self-hostable, including air-gapped Docker deployments for regulated environments
✅ Bring-your-own-model design works with any LLM provider and can reuse existing ChatGPT/Claude/Cursor subscriptions
✅ 3,000+ integrations spanning MCP, OpenAPI, GraphQL, and HTTP, so most SaaS tools are reachable out of the box
✅ Git-native workflow (agents as files, isolated sandboxes, reviewed change requests) makes autonomous work auditable

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