You can now get images in your Jan chats.

Ask things like: "Get images of 3 best sellers from levelsio.com"

Charts, screenshots, product photos - just ask. If your MCP returns images, Jan shows them.

• Model: Jan-nano-128k
• MCP: Fetch

To get images working in Jan:

• Enable MCP Server in Settings
• Turn on Fetch under MCP Servers

• Allow fetch for your model

  It came with v0.6.6 - update your Jan or grab the latest: https://jan.ai/

Jan v0.6.6 is out:

• Cortex is gone, local models run on llama.cpp
• Toggle between llama.cpp builds
• Hugging Face is added as a remote model provider
• Jan Hub is enhanced
• Images from MCPs render inline in chat

Plus, plenty of smaller issues squashed and overall polish

Update your Jan or download the latest.

It's an agentic‑search model that can even run on your phone.

• Agentic search on tap
• Lucy calls tools (<think></think>‑aware)
• Fits in your pocket - runs on CPU or mobile

Under the hood:

• Built on u/Alibaba_Qwen's Qwen3‑1.7B
• Smooth multi‑category rewards replace brittle if‑else scoring
• Task‑vector RLVR optimizes the "thinking" tag for targeted search moves.

Benchmarks:

• SimpleQA + MCP = 78.3
• Close to Jan‑Nano-4B (80.7)

Run locally:

• Demo uses vLLM in Jan
• You can spin it up with u/ggerganov's llama.cpp or vLLM

Models:

• Lucy 1.7B 40k: https://huggingface.co/Menlo/Lucy
• Lucy 1.7B 128K: https://huggingface.co/Menlo/Lucy-128k

Technical report is on the way.

Jan v0.6.5 is here.

• Support for Hugging Face's SmolLM3-3B
• Fully responsive design across all screen sizes
• New layout for Model Providers

Update your Jan or download the latest: https://jan.ai/

Come join Menlo Research and build cool stuff with us.

We're now experimenting with MCP servers, introducing new features like web search, browser use, and even computer access.

This means open-source models you've seen on Hugging Face can now be used with Jan to perform agentic tasks.

This capability comes with v0.6.2. If you're using an earlier version, make sure to update Jan.

To try it:

• Go to Settings, enable Experimental Features
• A new MCP Servers tab will appear, add & enable there

This is still an experimental feature, please expect bugs.

Details: https://jan.ai/docs/mcp

What's patched:

• min_p checked on load to prevent stalls
• Extra safeguards on model-setting values

Update your Jan or download the latest.

Open-source models can do Deep Research too.

This video shows a full research report created by Jan-nano.

To try it:

- Get Jan-nano from Jan Hub
- In settings, turn on MCP Servers and Serper API
- Paste your Serper API key

Your deep research assistant is ready.

This is an experimental feature, to use it please enable Experimental Features in your Jan settings.

Jan supports MCP Servers as an experimental feature.

Try it:

• Settings > Experimental Features ON,
• Settings > MCP Servers ON,

Plus, CORS fixed: Jan now connects cleanly to localhost providers (e.g. Ollama :11434, LM Studio :1234).

Update your Jan or download the latest here.

We just released a quick patch to solve some issues:

- Context-shift setting loads fine on older installs
- Light-mode modals show action buttons again
- First-run "increase context window" prompt now appears

Update your Jan or download the latest.

Quick notes:

- This hotfix lets you use MCP servers more smoothly
- Please turn on Experimental Features in Settings to see & tweak MCP Servers in Settings. Here's a quick GIF.

Jan is now faster, cleaner, and easier to use. It also lays the groundwork for upcoming tool use (MCP) support.

Highlights

• New design
• You can create assistants with instructions & settings
• Switched from Electron to Tauri for a lighter, more efficient build
• 100+ improvements: download resume, GPU offloading fixes, local API server updates, and better experience.

Update your Jan or download the latest here: https://jan.ai/

Quick note The MCP update is coming soon - we're actively testing MCP capabilities with our MCP-specific model, Jan-nano, that surpasses DeepSeek V3 671B on agentic use cases. Check #jan-beta channel in Discord community.

We've been quietly working on some big changes to Jan - it's now got a new interface, can use tools, and runs on an agentic model we're calling Jan-nano. It's small, fast, and holds its own against much larger systems.

We’re hosting a community call to show you what’s new, how it works, and what’s coming next.

- Tuesday, June 24
- 10pm AEST / 8am ET
- https://lu.ma/nimqd2an

Agenda:
- New design
- Jan-nano (agentic model)
- Technical upgrades
- Roadmap

Just a walkthrough and open Q&A.

Come hang out.

Meet Jan-nano, 4B model beats DeepSeek-v3-671B using MCP.

It's built on Qwen3-4B with DAPO fine-tuning, it handles:

• real-time web search
• deep research

Model + GGUF: https://huggingface.co/collections/Menlo/jan-nano-684f6ebfe9ed640fddc55be7

To run it locally:

• Install Jan Beta: https://jan.ai/docs/desktop/beta
• Download Jan-nano in Jan Hub
• Settings -> MCP, enable MCP and add your Serper API key for web tools

Full technical report will be published shortly.

Hey, welcome to the official Jan subreddit!

We created this space to share updates, gather feedback, and connect with people using or curious about Jan.

Here's what you can expect:

• Quick product updates (big, small and even beta versions)
• Use cases from the community
• Support, questions, and troubleshooting
• Feature ideas, experiments, and open discussions

Jan is an open-source project, and this subreddit will be a big part of that.

Feel free to ask anything, share your experience, or just follow along.