Skip to content

Troubleshooting

When Jan isn’t working properly, error logs help identify the problem. Here’s how to get them:

In Jan Interface:

  1. Look for System Monitor in the footer
  2. Click App Log

App log

Via Terminal:

Terminal window
# macOS/Linux
tail -n 50 ~/Library/Application\ Support/Jan/data/logs/app.log
# Windows
type %APPDATA%\Jan\data\logs\app.log

If Jan gets stuck after installation or won’t start properly:

Clean Reinstall Steps:

  1. Uninstall Jan from Applications folder

  2. Delete all Jan data:

Terminal window
rm -rf ~/Library/Application\ Support/Jan
  1. Kill any background processes (for versions before 0.4.2):
Terminal window
ps aux | grep nitro
# Find process IDs and kill them:
kill -9 <PID>
  1. Download fresh copy from jan.ai

If Jan isn’t using your NVIDIA graphics card for acceleration:

Verify GPU Detection:

Windows: Right-click desktop → NVIDIA Control Panel, or check Device Manager → Display Adapters

Linux: Run lspci | grep -i nvidia

Install Required Software:

NVIDIA Driver (470.63.01 or newer):

  1. Download from nvidia.com/drivers
  2. Test: Run nvidia-smi in terminal

CUDA Toolkit (11.7 or newer):

  1. Download from CUDA Downloads
  2. Test: Run nvcc --version

Linux Additional Requirements:

Terminal window
# Install required packages
sudo apt update && sudo apt install gcc-11 g++-11 cpp-11
# Set CUDA environment
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64
  1. Open Settings > Hardware
  2. Turn on GPU Acceleration
  3. Check System Monitor (footer) to verify GPU is detected

Hardware

  1. Go to Settings > Advanced Settings > Data Folder
  2. Open settings.json file
  3. Check these settings:
{
"run_mode": "gpu", // Should be "gpu"
"nvidia_driver": {
"exist": true, // Should be true
"version": "531.18"
},
"cuda": {
"exist": true, // Should be true
"version": "12"
},
"gpus": [
{
"id": "0",
"vram": "12282" // Your GPU memory in MB
}
]
}

Close and restart Jan to apply changes.

Desktop Systems:

  • Windows 11 + RTX 4070Ti + CUDA 12.2 + Driver 531.18
  • Ubuntu 22.04 + RTX 4070Ti + CUDA 12.2 + Driver 545

Virtual Machines:

  • Ubuntu on Proxmox + GTX 1660Ti + CUDA 12.1 + Driver 535

”Failed to Fetch” or “Something’s Amiss” Errors

Section titled “”Failed to Fetch” or “Something’s Amiss” Errors”

When models won’t respond or show these errors:

1. Check System Requirements

  • RAM: Use models under 80% of available memory
    • 8GB system: Use models under 6GB
    • 16GB system: Use models under 13GB
  • Hardware: Verify your system meets minimum requirements

2. Adjust Model Settings

  • Open model settings in the chat sidebar
  • Lower the GPU Layers (ngl) setting
  • Start low and increase gradually

3. Check Port Conflicts If logs show “Bind address failed”:

Terminal window
# Check if ports are in use
# macOS/Linux
netstat -an | grep 1337
# Windows
netstat -ano | find "1337"

Default Jan ports:

  • API Server: 1337
  • Documentation: 3001

4. Try Factory Reset

  1. Settings > Advanced Settings
  2. Click Reset under “Reset To Factory Settings”

5. Clean Reinstall If problems persist, do a complete clean installation (see “Jan Won’t Start” section above).

If you see permission errors during installation:

Terminal window
# Fix npm permissions (macOS/Linux)
sudo chown -R $(whoami) ~/.npm
# Windows - run as administrator

For OpenAI connection problems:

1. Verify API Key

  • Get valid key from OpenAI Platform
  • Ensure sufficient credits and permissions

2. Check Regional Access

  • Some regions have API restrictions
  • Try using a VPN from a supported region
  • Test network connectivity to OpenAI endpoints

Models Running Slowly:

  • Enable GPU acceleration (see NVIDIA section)
  • Use appropriate model size for your hardware
  • Close other memory-intensive applications
  • Check Task Manager/Activity Monitor for resource usage

High Memory Usage:

  • Switch to smaller model variants
  • Reduce context length in model settings
  • Enable model offloading in engine settings

Frequent Crashes:

  • Update graphics drivers
  • Check system temperature
  • Reduce GPU layers if using GPU acceleration
  • Verify adequate power supply (desktop systems)

If these solutions don’t work:

1. Gather Information:

  • Copy your error logs (see top of this page)
  • Note your system specifications
  • Describe what you were trying to do when the problem occurred

2. Get Community Support:

  • Join our Discord
  • Post in the #🆘|jan-help channel
  • Include your logs and system info

3. Check Resources: