Dify vs Langflow (2026): Pricing, Features & Verdict
Dify is our pick, scoring 7.3/10 against 6.9/10 for Langflow on our AI Software criteria. Its biggest advantage: higher Security score (8/10 vs 4/10). For 10 users, Langflow is free, against $159/mo for Dify; both Dify and Langflow have a free plan.
Last updated: November 2026
Dify
7.3/10
Open-source platform for building LLM apps, agents, RAG knowledge pipelines and visual AI workflows, available as cloud SaaS or self-hosted.
Langflow
6.9/10
Langflow is an open-source, Python-based visual builder that developers use to create, test and deploy AI agents, RAG pipelines and MCP servers as APIs.
Feature-by-Feature Comparison
| Feature | | |
|---|---|---|
| Scores | ||
| Overall Rating | 7.3/10 | 6.9/10 |
| Integration | 7/10 | 8/10 |
| Analytics | 6/10 | 5/10 |
| Customization | 9/10 | 9/10 |
| Ease of Use | 7/10 | 7/10 |
| Support | 6/10 | 5/10 |
| Cost | 8/10 | 9/10 |
| Scalability | 6/10 | 5/10 |
| Security | 8/10 | 4/10 |
| Output Quality | 7/10 | 6/10 |
| Pricing | ||
| Free plan | Yes | Yes |
| Cheapest paid plan | $59/mo Professional | Contact for pricing |
| Estimated cost for 10 users | $159/mo Team | Free Langflow OSS (self-hosted) |
| Features | ||
| AI Agents | ||
| API Access | ||
| Chatbots | ||
| Enterprise Controls | ||
| Knowledge Base Search | ||
| Private Deployment | ||
| Workflow Automation | ||
| Text Generation | Not listed | |
Dify vs Langflow cost by team size
Dify and Langflow cost the same at 1 user; Langflow costs less from 5 users.
| Team size | Dify | Langflow |
|---|---|---|
| 1 user | FreeSandbox | FreeLangflow OSS (self-hosted) |
| 5 users | $159/moTeam | FreeLangflow OSS (self-hosted) |
| 10 users | $159/moTeam | FreeLangflow OSS (self-hosted) |
| 25 users | $159/moTeam | FreeLangflow OSS (self-hosted) |
| 50 users | $159/moTeam | FreeLangflow OSS (self-hosted) |
The plan that fits each team size, billed monthly, before add-ons and usage charges. Each cost opens that tool's pricing calculator for the team size.
Who Dify and Langflow suit
Dify fits enterprise and small business better; Langflow fits agencies better.
| Audience | Dify | Langflow |
|---|---|---|
| Agencies | 5/10Teams can publish chatbots as embeds or web apps, which could be built for clients. | 7/10An independent reviewer used it for client agent projects and reported much faster delivery than hand-coding. |
| Enterprise | 8/10The Enterprise edition offers VPC or self-hosted deployment, SSO, RBAC and audit logs, and Dify names large customers such as Maersk and Volvo. | 6/10IBM sells SLA-backed support, and version 1.13 adds audit logging and user, team and role management, but the company must self-host and patch it. |
| Small Business | 6/10It is affordable, but it still needs technical skills to build apps and integrate them. | 4/10Without a managed hosted service and with AI concepts such as embeddings to learn, non-technical small firms will struggle. |
| Startups | 9/10The free self-hosted edition and low-cost cloud plans suit teams prototyping AI MVPs quickly. | 8/10There is no license fee, and a basic RAG prototype can be built in minutes, so it suits teams with engineers but a small budget. |
| Developers | 9/10It is an open-source LLM app platform with an API, self-hosting and support for many model providers. | 9/10It is Python-based and open source, with editable component code, a REST API, MCP server and client support, and pip, Docker and Desktop installs. |
| IT Teams | 6/10Self-hosting with Docker or Helm, SSO, RBAC and audit logs support internal deployment. | 6/10IT teams can run it on their own infrastructure with OpenTelemetry monitoring, but they carry the hardening and upgrade work. |
| Consultancies | 7/10Visual workflows and self-hosting let consultancies build and hand off client AI apps. | Not rated |
| Customer Support Teams | 5/10A review describes building a RAG support workflow with human handoff in under an hour. | Not rated |
| Freelancers | 5/10The free Community Edition and free Sandbox tier lower the cost for individuals. | Not rated |
| Mid-Market | 7/10The Team plan supports 50 members and 200 apps, which fits internal AI tooling. | Not rated |
| SaaS Companies | 6/10API endpoints and embeds let software companies ship AI features to customers. | Not rated |
Which One Should You Choose?
Why choose Dify
- Higher Security score (8/10 vs 4/10)
- Higher Analytics score (6/10 vs 5/10)
- Better fit for small business (6/10 vs 4/10)
- Better fit for enterprise (8/10 vs 6/10)
Why choose Langflow
- Lower estimated cost for 10 users: Free vs $159/mo
- Higher Integration score (8/10 vs 7/10)
- Higher Cost score (9/10 vs 8/10)
- Better fit for agencies (7/10 vs 5/10)
Pros & Cons
Dify
Pros
- The Community Edition is free to self-host with no license fees, so the only costs are infrastructure and model APIs.
- The visual workflow builder lets a team build a RAG support workflow with human handoff in under an hour, according to one review.
- Document ingestion, chunking, embedding and retrieval are handled in a single interface.
- Teams can switch between many model providers per node, including local models via Ollama.
- Apps can be published as web apps, embeds, APIs or MCP tools.
Cons
- Self-hosting needs Docker or Kubernetes skills, and reviewers report scaling problems under heavy workloads.
- Reviewers say Dify has fewer connectors than rivals such as LangFlow.
- Multi-agent orchestration and built-in observability are basic.
- Workflows have no built-in version control, and the canvas can lag on large flows.
- Removing Dify branding from self-hosted apps requires a commercial license.
Langflow
Pros
- The MIT license means no software fees and full source access. Teams can change any component in Python instead of being limited to the built-in nodes.
- Flows can be served as REST APIs or exposed as MCP servers, so agents built on the canvas plug straight into other apps and MCP clients.
- It includes ready-made RAG building blocks such as document loaders, chunking, embeddings and many vector store connectors. One review found a basic RAG pipeline took about 10 to 15 minutes, against 1 to 2 hours in LangChain code.
- Developers can test each component or flow on its own in the Playground before connecting it, which speeds up iteration.
- It is very popular open-source software, with about 156,000 GitHub stars, and is now backed by IBM, which sells SLA support.
Cons
- DataStax shut down its hosted Langflow on Astra on April 9, 2026, so production use usually means self-hosting and running it yourself.
- Its security record is weak. Two CVSS 9.8 flaws covering authentication bypass and code execution affected versions 1.0.0 to 1.12.8, and several older Langflow flaws are in CISA's Known Exploited Vulnerabilities catalog.
- Users report instability between versions and slow responses, with some flows taking 10 to 30 seconds or more, so pinning versions and testing upgrades is recommended.
- The canvas becomes hard to manage beyond roughly 20 to 30 nodes, and reviewers describe limited multi-agent orchestration.
- Reviewers say the documentation and error messages are thin, which makes debugging tedious.
Not sold on either?
Frequently Asked Questions
Dify scores higher on our AI Software criteria: 7.3/10 against 6.9/10 for Langflow. The largest gap is in Security: 8/10 for Dify and 4/10 for Langflow.
Langflow costs less for 10 users: free on its Langflow OSS (self-hosted) plan, against about $159/mo on its Team plan for Dify, billed monthly.
Yes, both Dify and Langflow have a free plan.
Langflow is the better fit for agencies: we rate it 7/10 for them, against 5/10 for Dify.
