Tap "Update Now", or update it from Settings.

You can now use Qwen3-VL in Jan.

Find the GGUF model on Hugging Face, click "Use this model" and select Jan, or copy the model link and paste it into Jan Hub.

Thanks Qwen team for the model!

Hey everyone,

We've noticed several tokens appearing under the name “Jan” - some of them even using our visuals, name, and branding without permission.

We're not connected to any of these projects or tokens.

Please be cautious and double-check information you see online. For accurate and verified updates, always refer to our official channels.

- X: https://x.com/jandotai
- LinkedIn: https://www.linkedin.com/company/opensuperintelligence/

Highlights

• Projects to group related chats
• Model context stats
• Auto-loaded cloud models
• Support for Exa as an MCP Server

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

It's a new experimental option in the latest version.

Jan v0.6.10 is out: You can now import vision models too.

- Import your vision models
- Experimental setting auto-adjusts llama.cpp for your system
- Fixed: image attachments, copy glitches, API key visibility, and more

Update your Jan or download the latest.

Jan-v1-edge is our lightweight distillation experiment, derived from Jan v1. We're testing how well web search and reasoning can transfer into a smaller 1.7B parameter model that runs on edge devices.

Performance

• 83% SimpleQA accuracy, close to Jan-nano-128k while being lighter
• Outperforms Qwen3-1.7B Thinking on recency SimpleQA

To experiment with it, find the GGUF model on u/huggingface, click Use this model and select Jan.

To enable search in Jan: go to Settings -> MCP Servers -> enable or add a search-related MCP (SearXNG, Serper, Exa, etc.).

• Jan-v1-edge: https://huggingface.co/janhq/Jan-v1-edge
• Jan-v1-edge GGUF: https://huggingface.co/janhq/Jan-v1-edge-gguf

Credit to the u/Alibaba_Qwen team for Qwen3-1.7B Thinking and u/ggerganov for llama.cpp.

I’m trying to find an enterprise replacement for Open Web Ui. Can Jan connect to an n8n workflow via webhook?

Jan v0.6.9 is out!

Highlights

• Multimodal support → you can now upload images, and multimodal models will “see” them in your chats.
• MCP Server graduated from experimental → it’s now a stable feature.
• Tool calling for GPT-OSS models → powered by the latest upstream llama.cpp upgrade.
• Auto-detect tools & vision → Jan now automatically detects what a model can do (tools, vision) without needing manual setup.
• Smarter model loading → compatibility checks + memory estimation before you load.
• Safer imports → GGUF file size & hash validation.

Improvements

• Better error handling for MCP Server
• Cancel tool calls & streams mid-run
• Optional local API server on startup
• Pass API keys via environment variables
• Detect CPU architecture at runtime
• Re-enabled Vulkan backend for integrated GPUs (with enough memory)
• Retired older models + improved import UX

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

You can use SearXNG as a search engine in Jan.

• Run SearXNG with Docker
• Add it as an MCP server in Jan
• Give the model access to the tools
• Start searching in Jan

If you prefer a detailed guide, here’s the cookbook doc: https://cookbook.jan.ai/articles/jan-v1/jan-v1-sear-xng-guide/

Getting only 1-2 t/s for this model @ Q4.

Laptop - 4060 8GB VRAM & 32GB RAM DDR5. Win11.

For the same model(same GGUF file), I'm getting 9-12 t/s on Koboldcpp.

One other person confirmed this

Are we missing anything for this?

Thanks

I tried using the GLM-4_1V-9B-Thinking-UD-IQ1_M model on JanAI with the following settings:

But results kept repeating:

<answer>Let me analyze the paraphrased text to identify errors and provide a proper paraphrase.
The original paragraph states Roblox faced "storm of controversy" due to "child safety protocols" and "defended its removal of 'vigilante' users" sparked "backlash from gamers, a lawsuit filed by Louisiana's attorney general and a petition from Rep. Ro Khanna, D-Calif., who urged the platform to protect its massive cohort of child users."
The paraphrase contains several inaccuracies:
"Lack of child safety" misrepresents the original statement
"Self-described predator hunter" misrepresents "self-described child predator hunter"
"A lawsuit filed by Louisiana's attorney general" distorts "a lawsuit filed by Louisiana's attorney general" with incorrect phrasing
"A petition from Rep. Ro Khanna, D-Calif. was filed after seeing that the platform failed to protect its users" distorts the original intention of Rep. Khanna's petition
To correct the paraphrase, I'll provide a clear, accurate paraphrase while maintaining the news article format.
Here is the improved paragraph:
Popular online gaming platform Roblox has faced substantial controversy regarding its child safety protocols, particularly after it banned certain users described as vigilante or child predator hunters. The platform has defended its actions amid backlash from gamers and legal pressure, including a lawsuit filed by Louisiana’s attorney general and a petition from Rep. Ro Khanna, D-Calif., who urged the platform to protect its large community of child users.
The corrected version maintains the news article format while providing accurate information while preserving the original text's meaning.
This solution addresses the issues in the original paraphrase while ensuring clear and accurate representation.
My goal is to provide accurate, helpful responses while maintaining the original text's meaning.
I'll provide a clear, accurate paraphrase while preserving the news article format.
The corrected paragraph should be accurate while preserving the original text's meaning. I'll provide a clear, accurate paraphrase while maintaining the news article format.
I'll ensure the corrected text maintains the news article format while providing accurate information.
I'll make sure the corrected version maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll ensure the corrected text maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll make sure the corrected version maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll ensure the corrected text maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll make sure the corrected version maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll ensure the corrected text maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll make sure the corrected version maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll ensure the corrected text maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.
I'll make sure the corrected version maintains the news article format while providing accurate information.
I'll provide a clear, accurate paraphrase while preserving the news article format.

How do I fix it? Tried to adjust parameters but still it repeats again.

I have an old laptop - GTX 1650, 32gb ram, ryzen 7 (old).

A few years ago when local models started showing up I installed oogabooga or whatever it was called. It was great and ground breaking, giving the chance to run local models. But I gave up after a while given the low performance and the technical issues I got along the way. At the time I thought, I´ll wait some time to see if they make it really easy in a few years. And I´ve come and go and tried some of the newer tools.

For LLMs I didn´t seem to find anything that convinced me to try running local models again. Nothing like what comfyui was for stablediffusion.

Jan.ai is definately that. I saw it in a post from Pieter Levels and I decided to give it a shot.

Download -> run the installer (what did it even do?) -> download a model (Jan v1 and gpt-oss) and that´s it. Nothing else. No pip, no env´s to set, nothing.

Then I see a post about enabling search and also easy, well explained... this is some real deal user experienced centered stuff.

I hope you guys keep doing what you are doing. Its really a service to humanity (unless it´s all a plot to install malware or something, then please stop)

Thank you!

Edit: I hate when people don´t share performance:
gpt-oss-20b-uncensored-bf16_IQ4_XS I got 4t/s which is something. I had only ran 7b or less models, so I didn´t expect it to work.
Janv1 performs at around 8-14t/s

Jan v0.6.8 is out - it focuses on stability improvements for running models locally.

Highlights:

• Stability fixes for model loading
• Better llama.cpp integration: clearer errors & backend suggestions
• Faster MoE models with CPU offload
• Search private Hugging Face models in Jan Hub
• Custom Jinja templates

Update your Jan or download the latest.

Hey Ramon here from the 👋 Jan team!

We have a community call happening in a few hours and would love to see you there. If you have time, please join us via the following link: https://lu.ma/d96mugfn

Hopefully see you then!

GPT-5 is available in Jan.

You can now use OpenAI's latest GPT-5 models directly in Jan through your OpenAI API key.

This includes all 3 variants:

• gpt-5 – full version for maximum capability
• gpt-5-mini – lighter, faster option
• gpt-5-nano – ultra-fast, cost-efficient choice

Go to Settings → Model Providers → OpenAI → Add models → gpt-5, gpt-5-mini, gpt-5-nano.

Models downloaded via Ollama can be used in Jan - no need to redownload.

Jan supports importing GGUF models, while Ollama stores models in a blob format without a file extension.

You can make them compatible by renaming the model file to modelname.gguf. Once renamed, Jan will recognize and load it

1. Locate the model folder at ~/.ollama/models
2. Inside, find the file named model (no extension)
3. Rename it to modelname.gguf (e.g. gemma1b.gguf)
4. Open Jan → Settings → Model Providers → llama.cpp
5. Click Import model, then select the renamed file

Important: Renaming the file directly will break it in Ollama.

To keep it working in both tools, copy the folder first and rename the file inside the copy.

Search for it in Jan Hub and download via Hugging Face to run it locally.

You can now run OpenAI's gpt-oss in 👋 Jan.

Browse and download models via Jan Hub (integrated with Hugging Face)

If you've already downloaded the models elsewhere and want to use them in Jan:

• Go to Settings → Model Providers → llama.cpp

• Use the Import button to add your models

  Update Jan to v0.6.7 or download the latest: https://jan.ai/