# Dify vs Jan

Dify records 819,691 monthly visits with -15% month-over-month growth and Freemium pricing. Jan records 291,894 monthly visits with -9.6% growth and Free pricing.

| Metric | [Dify](https://openaitools.app/tool/dify-ai) | [Jan](https://openaitools.app/tool/jan) |
| :--- | :--- | :--- |
| Website URL | https://dify.ai | https://jan.ai |
| Categories | AI App Builder, AI Agent, AI Workflow, AI API | AI Chatbot, AI Assistant, Open Source AI Models, Large Language Models (LLMs) |
| Pricing Model | Freemium | Free |
| Monthly Visits | 819,691 | 291,894 |
| MoM Growth Rate | -15% | -9.6% |
| Primary Market | China | United States |
| Direct Visits | 470,604 | 105,615 |
| Review Score | 4.8 | 4.6 |
| Saved Count | 22 | 6 |
| Supported Platforms | Website | Website |

## Dify

Dify pairs a visual canvas with code-level control so both technical and non-technical teams can assemble AI applications and agents. Workflow Studio turns prompt logic into an inspectable execution graph of building blocks: retrieval, branching, tool calls, human-in-the-loop steps, and model calls. Agent builder lets you create agents by chatting or by configuring them directly, then run them as a standalone app, embed them into a website, or reuse them as a node inside a larger workflow.

A major part of the platform is context engineering. The Knowledge Pipeline lets you define repeatable ingestion flows for files, websites, online documents, and cloud drives, handling extraction, cleaning, chunking, indexing, and retrieval testing before a knowledge base is attached to agents or workflows. The Marketplace supplies model providers, tools, data sources, and MCP integrations that teams can install once and then reuse across many apps as approved plugins.

Dify ships in three deployment shapes: Dify Cloud (fully managed SaaS with workspace, logs, and scaling handled for you), Dify Enterprise (self-hosted or VPC deployment with SSO/SAML, RBAC, audit logs, Helm charts for Kubernetes, and enterprise support), and the open-source Community Edition, a source-available single-command Docker deployment with a large GitHub community. Published apps can be delivered as hosted web apps, API endpoints, embeds, or MCP-compatible tools, with logs, feedback, annotations, latency, and usage analytics to keep improving them after launch.

**Pricing & Plans:** Freemium model with a free cloud sandbox and free trial credits, paid Cloud plans that scale with team size, storage, logs, and usage, and a free open-source Community Edition. Dify Enterprise is quoted per deployment via sales.

- **Workflow Studio:** A visual canvas where retrieval, branching, tool calls, human review, and model steps form a visible, testable execution path you can debug and hand off.
- **Agent Builder:** Create agents through chat or manual configuration, give them skills, tools, and knowledge, then ship them as apps, embeds, or reusable nodes inside workflows.
- **Knowledge Pipeline:** Build repeatable ingestion pipelines for documents, sites, and drives, with extraction, cleaning, chunking, indexing, and retrieval testing before you go live.
- **Plugin Marketplace and MCP:** Install model providers, tools, data sources, and MCP integrations once and reuse approved plugins across every app in the workspace.
- **Flexible Deployment and Observability:** Run on managed Cloud, in your VPC, or self-hosted with Docker, and monitor published apps through logs, annotations, feedback, latency, and usage data.

**Strengths:** Combines a visual builder with code-level extensibility in one product; Three deployment options, including a free self-hosted Community Edition; Strong retrieval and knowledge pipeline tooling for RAG applications; Large plugin marketplace plus MCP support reduces integration work

**Limitations:** Self-hosted deployments require real infrastructure and maintenance effort; Complex multi-step workflows take time to learn and tune; Advanced enterprise governance features sit behind a sales-quoted plan

[Profile (Markdown)](https://openaitools.app/tool/dify-ai.md)

## 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)

## Frequently Asked Questions

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

Dify has 819,691 monthly visits, while Jan has 291,894. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Dify has a month-over-month growth rate of -15%; Jan has -9.6%.

### How does pricing compare?

Dify: Freemium. Freemium model with a free cloud sandbox and free trial credits, paid Cloud plans that scale with team size, storage, logs, and usage, and a free open-source Community Edition. Dify Enterprise is quoted per deployment via sales. 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.

## 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 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | An open-source automation powerhouse with deep app connectors, though less specialized for native LLM prompt chaining. | [.md](https://openaitools.app/tool/n8n.md) |
| 3 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | Offers a streamlined no-code builder for deploying custom AI agents, but lacks Dify's open-source flexibility. | [.md](https://openaitools.app/tool/mindstudio.md) |
| 4 | [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) |
| 5 | [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) |
| 6 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Provides advanced programmatic frameworks for document parsing and RAG pipelines, but requires coding instead of visual canvases. | [.md](https://openaitools.app/tool/llamaindex.md) |
| 7 | [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) |
| 8 | [Activepieces](https://openaitools.app/tool/activepieces) | 258,553 | +1.5% | Freemium | An open-source automation platform combining visual flows with AI steps, though geared more towards general app integration. | [.md](https://openaitools.app/tool/activepieces.md) |
| 9 | [Dyad](https://openaitools.app/tool/dyad) | 207,981 | +3.5% | Freemium | Free, open-source AI app builder that runs on your own machine | [.md](https://openaitools.app/tool/dyad.md) |
| 10 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | Built for scaling multi-agent workforces and B2B task automation, though less focused on open-source RAG pipelines. | [.md](https://openaitools.app/tool/relevance-ai.md) |

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Source: https://openaitools.app/compare/dify-ai-vs-jan

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