Dify score factors
Editorial quality82
Practical utility84
Trust & transparency82
Freshness87
Engagement quality5
Momentum100
Decision guide · Reviewed Sep 8, 2026 · AI Agent & Chatbot Builders, AI Coding & Development, Agent Platforms & Frameworks
Dify
78
LangGraph
77.4Choose Dify when you need engineering and platform teams that want a self-hostable LLM app builder with retrieval and workflows. Choose LangGraph when you need building complex, custom, and multi-actor agent workflows that require explicit state management, human approvals, and real-time streaming.
At a glance
The practical differences
| Decision factor | Dify | LangGraph |
|---|---|---|
| Best for | engineering and platform teams that want a self-hostable LLM app builder with retrieval and workflows | building complex, custom, and multi-actor agent workflows that require explicit state management, human approvals, and real-time streaming |
| Not ideal for | non-technical teams that need a turnkey chatbot with no infrastructure decisions | non-technical users looking for no-code bot builders or projects requiring only basic, linear LLM call chains |
| Pricing | The open-source edition can be self-hosted; the cloud service has a free sandbox and paid Professional and Team plans at the review date. Model usage is billed separately by your provider. Check the official pricing page for current tiers. | At the review date, the LangGraph orchestration library is open source under an MIT license and free to use. Optional hosted infrastructure, tracing, and managed deployment through LangSmith offer a free Developer tier (1 seat, 5,000 monthly traces) and a paid Plus tier at $39 per seat per month plus compute and storage usage. |
| Key difference | A capable open-source LLM app platform that you can self-host, combining workflows, retrieval, and agents with observability and model flexibility. | Unlike generic black-box autonomous loops, LangGraph models agent workflows as explicit stateful graphs with fine-grained control over cyclical transitions, state persistence, and human-in-the-loop interruptions. |
| Overall rank | #67 | #88 |
| Review verdict | Best for engineering teams that want ownership over hosting and models while keeping a visual builder. Teams without operations capacity should weigh the cloud plan or a fully managed builder. | LangGraph suits software engineers who need precise, low-level control over multi-agent workflows, state persistence, and human approval steps. It is not designed for non-technical users seeking no-code drag-and-drop builders or teams that only need standard, non-cyclical prompt chaining. |
LangGraph score factors
Editorial quality82
Practical utility92
Trust & transparency85
Freshness90
Engagement quality0
Momentum50
Dify strengths
- Open source and self-hostable
- Model-provider flexibility
- Workflows, retrieval, and agents together
- Active community
LangGraph strengths
- Open-source and MIT-licensed with no licensing cost for the core framework
- Provides fine-grained state machine control rather than rigid black-box agent loops
- Native token-by-token streaming for both intermediate actions and final outputs
- Seamless optional observability and evaluation integration with LangSmith
Frequently asked
Dify vs LangGraph
Should I choose Dify or LangGraph?+
Choose Dify when you need engineering and platform teams that want a self-hostable LLM app builder with retrieval and workflows. Choose LangGraph when you need building complex, custom, and multi-actor agent workflows that require explicit state management, human approvals, and real-time streaming. ToolsRank scores Dify 78 and LangGraph 77.4; the gap reflects editorial quality, utility, trust, and freshness, not popularity or payment.
Is Dify cheaper than LangGraph?+
Dify: The open-source edition can be self-hosted; the cloud service has a free sandbox and paid Professional and Team plans at the review date. Model usage is billed separately by your provider. Check the official pricing page for current tiers. LangGraph: At the review date, the LangGraph orchestration library is open source under an MIT license and free to use. Optional hosted infrastructure, tracing, and managed deployment through LangSmith offer a free Developer tier (1 seat, 5,000 monthly traces) and a paid Plus tier at $39 per seat per month plus compute and storage usage. Compare the plan you would actually use and verify current prices on each vendor's pricing page before purchasing.
Which is better for ai agent & chatbot builders?+
Dify currently scores higher for ai agent & chatbot builders work. LangGraph remains the stronger pick when your priority is building complex, custom, and multi-actor agent workflows that require explicit state management, human approvals, and real-time streaming. Avoid Dify if you are non-technical teams that need a turnkey chatbot with no infrastructure decisions.
Can I use Dify and LangGraph together?+
Yes. Dify stands out for a capable open-source LLM app platform that you can self-host, combining workflows, retrieval, and agents with observability and model flexibility. LangGraph stands out for unlike generic black-box autonomous loops, LangGraph models agent workflows as explicit stateful graphs with fine-grained control over cyclical transitions, state persistence, and human-in-the-loop interruptions. Pairing them makes sense when one workflow needs both strengths; otherwise pick the tool that matches your primary job.