# Jan vs n8n

Jan records 291,894 monthly visits with -9.6% month-over-month growth and Free pricing. n8n records 4,522,449 monthly visits with -7.4% growth and Freemium pricing.

| Metric | [Jan](https://openaitools.app/tool/jan) | [n8n](https://openaitools.app/tool/n8n) |
| :--- | :--- | :--- |
| Website URL | https://jan.ai | https://n8n.io |
| Categories | AI Chatbot, AI Assistant, Open Source AI Models, Large Language Models (LLMs) | AI Workflow, AI Agent, No-Code&Low-Code, AI Developer Tools |
| Pricing Model | Free | Freemium |
| Monthly Visits | 291,894 | 4,522,449 |
| MoM Growth Rate | -9.6% | -7.4% |
| Primary Market | United States | India |
| Direct Visits | 105,615 | 1,565,199 |
| Review Score | 4.6 | 4.7 |
| Saved Count | 6 | 4 |
| Supported Platforms | Website | Website |

## Jan

Jan is a desktop application that positions itself as an open replacement for ChatGPT, with the key difference that inference happens on hardware you control. After installing the app you pick a model, and Jan downloads and runs it locally, so prompts, chat history, and files stay on your machine rather than on someone else's server. For heavier workloads you can connect an OpenAI, Anthropic, Gemini, or Mistral key and route requests to the cloud while keeping the same chat interface and local history.

The project is developed in the open by Menlo Research and has accumulated tens of thousands of GitHub stars along with millions of downloads. It exposes OpenAI-compatible local endpoints, which means existing tooling and SDKs can point at Jan instead of a hosted service, and it supports custom assistants with their own instructions and model choices. Recent releases have added an agent surface alongside the classic desktop chat, and a memory feature is announced as coming to carry context and preferences between sessions.

Because it is open source, Jan can be audited, self-built, and extended, and there is no paid tier gating the desktop client. The practical tradeoff is that local model quality and speed depend entirely on your own GPU or CPU, so lighter machines will favor smaller quantized models while cloud keys remain the escape hatch for harder tasks.

**Pricing & Plans:** Jan is free and open source, with no paid tier for the desktop app. Costs only appear if you optionally connect your own paid cloud API keys for providers such as OpenAI or Anthropic.

- **Local-first inference:** Download and run open models such as Llama, Mistral, Qwen, Gemma, and DeepSeek directly on your own machine, with chat data kept on device.
- **Bring your own cloud models:** Optionally connect API keys for OpenAI, Anthropic, Gemini, Mistral, and other providers to route requests to frontier models from the same interface.
- **OpenAI-compatible local API:** Jan exposes a local server endpoint that follows the OpenAI API shape, so existing SDKs and tools can talk to your local models without code changes.
- **Custom assistants:** Create assistants with their own system instructions, model selection, and parameters, then reuse them across conversations.
- **Open source and extensible:** The full desktop client and agent code are public on GitHub, so you can audit behavior, build your own version, and contribute improvements.

**Strengths:** Completely free and open source, with no account required to run local models; Conversation data stays on your device by default; Works across macOS, Windows, and Linux with an OpenAI-compatible local endpoint; Optional cloud key support lets you mix local and frontier models in one app

**Limitations:** Local model quality and speed are capped by your own hardware; Very large models may need substantial RAM or VRAM to be practical; Some cloud-connected and memory features are newer or still rolling out

[Profile (Markdown)](https://openaitools.app/tool/jan.md)

## n8n

n8n is a workflow automation platform built for technical teams who want automation they can actually read and audit. Rather than hiding logic behind opaque configuration, every step stays open: you can see what a node does and explain the whole flow to whoever runs it. It combines a drag-and-drop visual builder with the ability to drop into code at any point, so simple tasks stay simple while complex ones remain possible.

A major focus of the current product is AI agents. You can connect any model, watch an agent work step by step in the same workflow view, open past runs, and constrain behaviour with structured inputs and outputs, rule-based automation and human-in-the-loop approval gates. That makes it practical to put agents into processes like refund handling, alert triage, lead qualification and security investigation without losing control.

n8n is open source and can be self-hosted on-prem or with Docker to keep data in your own environment, or used as a hosted service. Enterprise capabilities add SSO with SAML and LDAP, RBAC, encrypted secret stores, audit logs, log streaming to SIEM systems, isolated environments and Git-based control. Integrations span 500+ native services, arbitrary HTTP APIs and MCP connections to agents and coding assistants.

**Pricing & Plans:** n8n offers a free self-hosted open-source edition, a paid cloud service with a free trial, tiered paid plans, and enterprise pricing on request. Feature limits scale with plan tier, so check the official pricing page for current details.

- **Visual builder with code escape hatch:** Build automations with a visual node editor, then insert JavaScript or Python code nodes when you need custom logic.
- **500+ integrations and any API:** Connect to 500+ native services, any REST API via HTTP nodes, and any agent or coding assistant through MCP.
- **AI agents you can follow and trust:** Run agents alongside regular steps, inspect every decision, and add structured inputs, guardrails and human approval steps.
- **Observability and reproducible runs:** Watch workflows execute live, open past runs, replay a run with mocked data and re-run just the step that failed.
- **Self-host or cloud with governance:** Deploy on your own infrastructure with Docker or on-prem, or use the hosted cloud product, with version history and RBAC.

**Strengths:** Open source and self-hostable, keeping data in your own environment; Visual builder plus full code access for complex workflows; Strong observability: live runs, past-run inspection and step-level retries; 500+ integrations and generic HTTP nodes cover almost any service

[Profile (Markdown)](https://openaitools.app/tool/n8n.md)

## Frequently Asked Questions

### How do Jan and n8n compare in monthly traffic?

Jan has 291,894 monthly visits, while n8n has 4,522,449. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Jan has a month-over-month growth rate of -9.6%; n8n has -7.4%.

### How does pricing compare?

Jan: Free. Jan is free and open source, with no paid tier for the desktop app. Costs only appear if you optionally connect your own paid cloud API keys for providers such as OpenAI or Anthropic. n8n: Freemium. n8n offers a free self-hosted open-source edition, a paid cloud service with a free trial, tiered paid plans, and enterprise pricing on request. Feature limits scale with plan tier, so check the official pricing page for current details.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Provides a lightweight command-line runtime for local LLMs, though it lacks Jan's built-in graphical user interface. | [.md](https://openaitools.app/tool/ollama.md) |
| 2 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Unmatched ecosystem of app connectors and reliability, but significantly more expensive and lacks n8n's self-hosting freedom. | [.md](https://openaitools.app/tool/zapier-com.md) |
| 3 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder for custom AI agents and workflows | [.md](https://openaitools.app/tool/mindstudio.md) |
| 4 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Outstanding open-source visual canvas for RAG pipelines and LLM agents, but less suited for general API integrations. | [.md](https://openaitools.app/tool/dify-ai.md) |
| 5 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | Offers a powerful self-hosted web interface for local models, but requires manual Docker setup rather than desktop installation. | [.md](https://openaitools.app/tool/open-webui.md) |
| 6 | [Dust](https://openaitools.app/tool/dust) | 547,217 | +1.8% | Contact for Pricing | Multiplayer AI where people and agents work side by side | [.md](https://openaitools.app/tool/dust.md) |
| 7 | [Taskade](https://openaitools.app/tool/taskade) | 539,714 | -9.4% | Freemium | Turn one prompt into live business apps, AI agents and automated workflows | [.md](https://openaitools.app/tool/taskade.md) |
| 8 | [AnythingLLM](https://openaitools.app/tool/anythingllm) | 512,269 | +12.9% | Freemium | Specializes in document chat and local RAG workflows, though less focused on general-purpose model tinkering than Jan. | [.md](https://openaitools.app/tool/anythingllm.md) |
| 9 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Powerful visual builder specifically tailored for complex AI agent workflows, but less mature for traditional enterprise automation. | [.md](https://openaitools.app/tool/gumloop.md) |
| 10 | [LibreChat](https://openaitools.app/tool/librechat) | 346,879 | -3.5% | Free | Unites multiple AI providers in a customizable open-source platform, but is typically deployed as a web server. | [.md](https://openaitools.app/tool/librechat.md) |

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Source: https://openaitools.app/compare/jan-vs-n8n

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)