Langflow vs Flowise
You are comparing two self-hostable visual builders for LLM workflows. Langflow is actively maintained; Flowise official core-team maintenance ended and its repository is archived, making fork ownership or migration a primary decision factor.
Langflow
Open-source Python visual builder for AI applications, agents, RAG, and MCP flows, with core components and provider bundles.
Read review →
Flowise
Archived visual builder for LLM agents and chatflows — self-hostable for teams with an explicit maintenance plan.
Read review →- Langflow criteria edges: 3
- Flowise criteria edges: 1
- Ties: 8
Side-by-side
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| Langflow | Flowise | |
|---|---|---|
| Agent layer DB | Builder (visual/low-code) | Builder (visual/low-code) |
| Primary surface DB | Visual-first | Visual-first |
| Model support DB | Any (via adapter) | Any (via adapter) |
| Runtime | Python (core components + provider bundles) | Node.js / TypeScript |
| License | MIT | Apache 2.0 outside specified enterprise paths |
| Canvas performance | Validate with the representative graph | Validate with the representative graph |
| Provider architecture | Core components + extension bundles | Own component abstractions |
| Custom components | Python classes | TypeScript classes |
| Embedded chat / SDK | API + iframe | Chat widget + REST API + SDK |
| Maintenance status | Active project | Official repository archived; core-team maintenance ended |
| Adoption boundary | Candidate for new deployments | Requires maintained fork or migration plan |
| Best for | Python teams using a visual component system | Existing JS / TS-shaped deployments with an ownership plan |
DB rows are facts from the Tool Database. The ✓ mark is our editorial verdict, not a sourced fact.
Evidence & sources
Comparison facts are drawn from our Tool Database; the verdict and analysis are editorial. Verify each fact against the official sources below.
Langflow
Last verified:
- license · checked 2026-09-20
- agentLayer · checked 2026-09-23
- aiCapabilities · checked 2026-09-23
- aiCapabilities · checked 2026-09-23
- language · checked 2026-07-18
- security (MCP Stdio) · checked 2026-09-23
- security (MCP resource authorization) · checked 2026-09-23
Flowise
Last verified:
- license · checked 2026-09-15
- lifecycle · checked 2026-09-15
- agentLayer · checked 2026-07-18
- language · checked 2026-07-18
Two near-identical mental models, two different runtimes
Unlike most compare pages, this is not a mental-model fight. Both Langflow and Flowise model your AI workflow as a canvas of nodes: a prompt node feeds a retriever node feeds a model node feeds an output node. The difference is not the conceptual model but the runtime, the integrations, and the host ecosystem.
Langflow lives in Python. In the 1.12 architecture it combines generic core components with provider-specific extension bundles, custom Python components, a visual editor, and API serving. LangChain is one supported provider ecosystem rather than the definition of every component.
Flowise lives in Node.js and uses LangChain.js-oriented components. Official core-team maintenance ended on August 31, 2026 and the repository is archived, so runtime fit is no longer the only decision: continued use requires a maintained fork or migration plan.
Use cases: when each one wins
Langflow fits Python-shaped backends, data-team-owned AI where maintainers already write Python, teams that want visual flow testing plus API serving, and self-hosted deployments that can operate its component and extension model.
Flowise fits JavaScript-shaped products (Next.js, Remix, SvelteKit apps that want an LLM workflow), web-team-owned AI where frontend engineers do not want to run Python services, quick chat embeds via the clean embed widget, a smaller curated component set for non-LangChain veterans, and self-hosted deployments that drop into existing Node containers.
Learning curve
The two canvases expose different component sets and runtimes. Test the representative flow with the intended operators rather than assuming a universal learning-curve winner.
Langflow rewards Python and LangChain familiarity. Flowise can remain familiar to JS-first teams, but its maintenance status now outweighs a small onboarding preference for a new deployment.
Pricing comparison
Langflow is MIT-licensed. In Flowise, code outside specified enterprise paths is Apache-2.0 while specified enterprise code uses commercial terms. Total cost depends on model calls, context, retrieval, infrastructure, hosted services, and maintenance ownership.
Flowise also carries maintenance ownership after official core-team support ended. Include fork maintenance or migration in the comparison rather than treating Python-versus-Node hosting as the entire cost split.
Final verdict
For a new deployment, Langflow is the maintained default in this pair. Flowise remains a possible existing-system choice only when the team has selected a maintained fork or accepts a migration plan.
If the real need is a fuller AI product platform, compare Dify separately. Category fit still matters, but Flowise lifecycle risk must now be evaluated before runtime preference.
FAQ
- Which is better, Langflow or Flowise?
- For a new maintained deployment, Langflow is the safer default. Existing Flowise users may keep its Node.js fit, but should select a maintained fork or plan migration. If you need a fuller end-user product surface, compare Dify separately.
- What are the main differences?
- Agent layer: Langflow — Builder (visual/low-code); Flowise — Builder (visual/low-code). Primary surface: Langflow — Visual-first; Flowise — Visual-first. Model support: Langflow — Core components + provider bundles; Flowise — Provider components, including LangChain.js paths. Runtime: Langflow — Python (core components + provider bundles); Flowise — Node.js / TypeScript. License: Langflow — MIT; Flowise — Apache 2.0 outside specified enterprise paths. Canvas performance: Langflow — Validate with the representative graph; Flowise — Validate with the representative graph. Provider architecture: Langflow — Core components + extension bundles; Flowise — Own component abstractions. Custom components: Langflow — Python classes; Flowise — TypeScript classes. Embedded chat / SDK: Langflow — API + iframe; Flowise — Chat widget + REST API + SDK. Maintenance status: Langflow — Active project; Flowise — Official repository archived; core-team maintenance ended. Adoption boundary: Langflow — Candidate for new deployments; Flowise — Requires maintained fork or migration plan. Best for: Langflow — Python teams using a visual component system; Flowise — Existing JS / TS-shaped deployments with an ownership plan.
- Is Langflow cheaper than Flowise?
- Pricing depends on workload. See each tool's review for current tiers.