# Jan vs LobeHub

Jan records 291,894 monthly visits with -9.6% month-over-month growth and Free pricing. LobeHub records 654,548 monthly visits with -25% growth and Freemium pricing.

| Metric | [Jan](https://openaitools.app/tool/jan) | [LobeHub](https://openaitools.app/tool/lobehub) |
| :--- | :--- | :--- |
| Website URL | https://jan.ai | https://lobehub.com |
| Categories | AI Chatbot, AI Assistant, Open Source AI Models, Large Language Models (LLMs) | AI Agent, AI Chatbot, AI Assistant, Large Language Models (LLMs) |
| Pricing Model | Free | Freemium |
| Monthly Visits | 291,894 | 654,548 |
| MoM Growth Rate | -9.6% | -25% |
| Primary Market | United States | China |
| Direct Visits | 105,615 | 193,171 |
| Review Score | 4.6 | 4.6 |
| Saved Count | 6 | 0 |
| 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)

## LobeHub

LobeHub positions itself as a home for "super-agents" that behave less like a chatbot you prompt and more like a colleague who joins the team. You invite an agent into a channel such as Slack, Discord or Telegram, and it reads back through messages, docs and repositories to build context. From there it watches for requests that fit its remit, creates its own tasks when nobody tags it, and reports back in the original thread once something ships.

The agents are built to work in parallel and across tools. LobeHub can plug in different IM apps, agent runtimes and models side by side, so work like writing code, drafting documentation or running releases can be delegated to the runtime best suited for it. Deliverables come with acceptance checks and evidence — a screenshot or short recording — so a human can accept, reject or send back a result before it is merged into the main workflow.

The project also leans heavily on a self-evolving loop. Each practice an agent performs is scored, recurring mistakes are surfaced for a human to re-teach, and learned lessons take effect immediately. LobeHub is available as a hosted service plus a downloadable desktop client, and the core codebase is open source with a large GitHub following.

**Pricing & Plans:** LobeHub offers a free tier to get started and paid plans for heavier private or team usage; the pricing page source flags custom or contact-for-pricing options for business needs.

- **Agents that join your channels:** Invite an AI teammate into Slack, Discord, Telegram or other IM apps and let it read channel history, docs and code to get up to speed.
- **Proactive task picking:** Agents can claim and create tasks they were never tagged in, based on permissions you set, then ping you only when something is ready.
- **Parallel multi-model work:** Point an agent at different runtimes and models so several jobs — coding, docs, releases — progress at the same time.
- **Evidence-based acceptance:** Every delivery arrives with checks and visual proof, and you accept or send it back before changes are merged.
- **Self-evolving learning:** Agents track how often they get things right, flag recurring mistakes and turn your corrections into lessons that apply right away.

**Strengths:** Agents work proactively instead of waiting for prompts; Connects multiple chat apps, runtimes and models in one workspace; Open-source core with an active community and large GitHub presence; Deliveries include evidence so humans can review before accepting

**Limitations:** The bot-facing pages block automated access, which can frustrate scripted workflows; Setup and permission tuning take real effort before agents are useful; Best value comes from heavy chat-based team workflows, not solo casual use

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

## Frequently Asked Questions

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

Jan has 291,894 monthly visits, while LobeHub has 654,548. 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%; LobeHub has -25%.

### 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. LobeHub: Freemium. LobeHub offers a free tier to get started and paid plans for heavier private or team usage; the pricing page source flags custom or contact-for-pricing options for business needs.

## 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 | [Hermes-Agent](https://openaitools.app/tool/hermes-agent-1) | 3,638,741 | -5.4% | Freemium | Open-source personal AI assistant with persistent memory and multi-platform messaging integration for automated task execution. | [.md](https://openaitools.app/tool/hermes-agent-1.md) |
| 3 | [Clawdbot (OpenClaw)](https://openaitools.app/tool/clawdbot) | 1,903,068 | -25.4% | Paid, Free | Open-source personal AI assistant running locally and connecting to chat apps to automate everyday tasks. | [.md](https://openaitools.app/tool/clawdbot.md) |
| 4 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | Self-hosted open-source AI platform and chat interface for running local or cloud large language models. | [.md](https://openaitools.app/tool/open-webui.md) |
| 5 | [AnythingLLM](https://openaitools.app/tool/anythingllm) | 512,269 | +12.9% | Freemium | Privacy-first open-source AI assistant for document chat, local RAG, and meeting transcription workflows. | [.md](https://openaitools.app/tool/anythingllm.md) |
| 6 | [LibreChat](https://openaitools.app/tool/librechat) | 346,879 | -3.5% | Free | Open-source AI platform uniting multiple LLM providers, custom agents, and tools in a customizable workspace. | [.md](https://openaitools.app/tool/librechat.md) |
| 7 | [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) |
| 8 | [OpenBot](https://openaitools.app/tool/openbot) | 145,308 | +2,617.1% | Freemium, Free, Contact for Pricing | Desktop application that runs collaborative teams of AI agents locally using existing developer subscriptions. | [.md](https://openaitools.app/tool/openbot.md) |
| 9 | [Lemonade](https://openaitools.app/tool/lemonade-ai) | 96,232 | -34.4% | Free | Acts as an open-source local AI server supporting multimodal models, though it is less established as a desktop client. | [.md](https://openaitools.app/tool/lemonade-ai.md) |
| 10 | [ChatBotKit](https://openaitools.app/tool/chatbotkit) | 95,095 | +17.1% | Paid | Managed developer platform for building, deploying, and operating conversational AI agents connected to external tools. | [.md](https://openaitools.app/tool/chatbotkit.md) |

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

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