LangGraph vs Langflow

LLangGraph9.2Visit Langflow8.7Visit

Higher score L LangGraph #2 in LLM Application Development Frameworks 9.2/10 Free plan Free plan✓ 0 of 5 features Visit LangGraph

vs

Langflow #7 in LLM Application Development Frameworks 8.7/10 Free plan Free plan✓ 0 of 5 features Visit Langflow

• LangGraph fits best

  Developers building durable, stateful agent workflows

• Langflow fits best

  Visual prototyping and deployment of AI flows

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Side by side

Feature	LLangGraph 9.2/10 Visit ↗	Langflow 8.7/10 Visit ↗
At a glance
Editor score	9.2	8.7
Ranking	#2 in LLM Application Development Frameworks	#7 in LLM Application Development Frameworks
Best for	Developers building durable, stateful agent workflows	Visual prototyping and deployment of AI flows
Pricing model	Free	Free
Starting price	Not published	Not published
Free plan	✓	✓
Free trial	—	—
Deployment	Self-hosted, Cloud	Cloud, Self-hosted, Desktop
Integrations	2 integrations	12 integrations
Built for	Solo, Small business, Mid-market, Enterprise	Solo, Small business, Mid-market, Enterprise
Features LangGraph 0/5 · Langflow 0/5
RAG support	Not published	Not published
Agent and tool use	Not published	Not published
Workflow graphs	Not published	Not published
Prompt optimization	Not published	Not published
JavaScript/TypeScript SDK	Not published	Not published
Specs
Primary language	Not published	Not published
Open-source license	Not published	Not published
Our review
Pros	Combines deterministic code and LLM-driven steps in graph workflows Supports durable execution, checkpointing, and resumption after failures Offers memory, streaming, and human review of agent state	Connect models, tools, components, and outputs in a visual flow builder Build multi-agent and RAG workflows with human approval steps Deploy through APIs, Docker, Kubernetes, cloud, self-hosting, or desktop
Cons	Low-level control requires developers to define workflow behavior Does not prescribe a high-level agent architecture Verified integrations are narrower than LangChain’s	Voice mode is not available in Langflow Desktop Provider integrations are delivered through installable extensions Support channels are community and documentation
Our verdict	LangGraph is an open-source framework and runtime for developers building long-running, stateful agents and workflows. Its graph model combines deterministic code with model-driven steps, and supports single-agent, multi-agent, and… Read the review →	Langflow is an open-source, Python-powered framework for building, testing, and deploying AI agents and LLM applications. Its visual flow builder connects models, components, tools, and outputs, making it relevant to developers and teams… Read the review →

Strengths and trade-offs

• LangGraph — where it wins

  • Combines deterministic code and LLM-driven steps in graph workflows
  • Supports durable execution, checkpointing, and resumption after failures
  • Offers memory, streaming, and human review of agent state

  Where it doesn't

  • Low-level control requires developers to define workflow behavior
  • Does not prescribe a high-level agent architecture
  • Verified integrations are narrower than LangChain’s

• Langflow — where it wins

  • Connect models, tools, components, and outputs in a visual flow builder
  • Build multi-agent and RAG workflows with human approval steps
  • Deploy through APIs, Docker, Kubernetes, cloud, self-hosting, or desktop

  Where it doesn't

  • Voice mode is not available in Langflow Desktop
  • Provider integrations are delivered through installable extensions
  • Support channels are community and documentation

• LLangGraph9.2/10 · Free plan

  Graph-based control for developers who need durable, stateful agent workflows.

  Visit LangGraphFull verdict →
• Langflow8.7/10 · Free plan

  A visual, open-source framework for prototyping and deploying AI flows across environments.

  Visit LangflowFull verdict →