We receive a lot of feedback issues, and we find that most of the issues submitted are related to custom nodes. So please ensure that you have read the custom node troubleshooting guide before submitting an error report to ensure that the issue is not caused by ComfyUI core issues.

Custom Node Troubleshooting Guide

Check how to troubleshoot issues caused by custom nodes.

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Common Issues & Quick Fixes

Before diving into detailed troubleshooting, try these common solutions:

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ComfyUI Won’t Start

Symptoms: Application crashes on startup, black screen, or fails to load

Quick fixes:

  1. Check system requirements - Ensure your system meets the minimum requirements
  2. Update GPU drivers - Download latest drivers from NVIDIA/AMD/Intel

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Generation Fails or Produces Errors

Symptoms: “Prompt execution failed” dialog with “Show report” button, workflow stops executing

Quick fixes:

  1. Click “Show report” - Read the detailed error message to identify the specific issue
  2. Check if it’s a custom node issue - Follow our custom node troubleshooting guide
  3. Verify model files - See Models documentation for model setup
  4. Check VRAM usage - Close other applications using GPU memory

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Slow Performance

Symptoms: Very slow generation times, system freezing, out of memory errors

Quick fixes:

  1. Lower resolution/batch size - Reduce image size or number of images
  2. Use memory optimization flags - See performance optimization section below
  3. Close unnecessary applications - Free up RAM and VRAM
  4. Check CPU/GPU usage - Use Task Manager to identify bottlenecks

Performance Optimization Commands:

For low VRAM systems:

# Low VRAM mode (uses cpu for text encoder)
python main.py --lowvram

# CPU mode (very slow but works with any hardware, only use as absolute last resort)
python main.py --cpu

For better performance:

# Disable previews (saves VRAM and processing)
python main.py --preview-method none

# Use optimized attention mechanisms
python main.py --use-pytorch-cross-attention
python main.py --use-flash-attention

# Async weight offloading
python main.py --async-offload

For memory management:

# Reserve specific VRAM amount for OS (in GB)
python main.py --reserve-vram 2

# Disable smart memory management
python main.py --disable-smart-memory

# Use different caching strategies
python main.py --cache-none      # Less RAM usage, but slower
python main.py --cache-lru 10    # Cache 10 results, faster
python main.py --cache-classic   # Use the old style (aggressive) caching.

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Installation-Specific Issues

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Desktop App Issues

For comprehensive desktop installation troubleshooting, see the Desktop Installation Guide.

  • Unsupported device: ComfyUI Desktop Windows only supports NVIDIA GPUs with CUDA. Use ComfyUI Portable or manual installation for other GPUs
  • Installation fails: Run installer as administrator, ensure at least 15GB disk space
  • Maintenance page: Check mirror settings if downloads fail
  • Missing models: Models are not copied during migration, only linked. Verify model paths

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Manual Installation Issues

The documentation may be slightly out of date. If an issue occurs, please manually verify whether a newer stable version of pytorch or any of the listed libraries exists. Refer to resources like the pytorch installation matrix or the ROCm website.

Python version conflicts:

# Check Python version (3.9+ required, 3.12 recommended)
python --version

# Use virtual environment (recommended)
python -m venv comfyui_env
source comfyui_env/bin/activate  # Linux/Mac
comfyui_env\Scripts\activate     # Windows

Package installation failures:

# Update pip first
python -m pip install --upgrade pip

# Install dependencies
pip install -r requirements.txt

# For NVIDIA GPUs (CUDA 12.8)
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu128

# For AMD GPUs (Linux only - ROCm 6.3)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.3

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Linux-Specific Issues

LD_LIBRARY_PATH errors:

Common symptoms:

  • “libcuda.so.1: cannot open shared object file”
  • “libnccl.so: cannot open shared object file”
  • “ImportError: libnvinfer.so.X: cannot open shared object file”

Solutions:

  1. Modern PyTorch installations (most common):
# For virtual environments with NVIDIA packages
export LD_LIBRARY_PATH=$VIRTUAL_ENV/lib/python3.12/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# For conda environments
export LD_LIBRARY_PATH=$CONDA_PREFIX/lib/python3.12/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# Or find your Python site-packages automatically
PYTHON_PATH=$(python -c "import site; print(site.getsitepackages()[0])")
export LD_LIBRARY_PATH=$PYTHON_PATH/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# You may also need other NVIDIA libraries
export LD_LIBRARY_PATH=$PYTHON_PATH/nvidia/cuda_runtime/lib:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$PYTHON_PATH/nvidia/cublas/lib:$LD_LIBRARY_PATH
  1. Find what libraries you have:
# Check installed NVIDIA packages
python -c "import site; import os; nvidia_path=os.path.join(site.getsitepackages()[0], 'nvidia'); print('NVIDIA libs:', [d for d in os.listdir(nvidia_path) if os.path.isdir(os.path.join(nvidia_path, d))] if os.path.exists(nvidia_path) else 'Not found')"

# Find missing libraries that PyTorch needs
python -c "import torch; print(torch.__file__)"
ldd $(python -c "import torch; print(torch.__file__.replace('__init__.py', 'lib/libtorch_cuda.so'))")
  1. Set permanently for your environment:
# For virtual environments, add to activation script
echo 'export LD_LIBRARY_PATH=$VIRTUAL_ENV/lib/python*/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH' >> $VIRTUAL_ENV/bin/activate

# For conda environments
conda env config vars set LD_LIBRARY_PATH=$CONDA_PREFIX/lib/python*/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# For global bashrc (adjust Python version as needed)
echo 'export LD_LIBRARY_PATH=$(python -c "import site; print(site.getsitepackages()[0])")/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH' >> ~/.bashrc
  1. Alternative: Use ldconfig:
# Check current library cache
ldconfig -p | grep cuda
ldconfig -p | grep nccl

# If missing, add library paths (requires root)
sudo echo "/usr/local/cuda/lib64" > /etc/ld.so.conf.d/cuda.conf
sudo ldconfig
  1. Debug library loading:
# Verbose library loading to see what's missing
LD_DEBUG=libs python main.py 2>&1 | grep "looking for"

# Check PyTorch CUDA availability
python -c "import torch; print('CUDA available:', torch.cuda.is_available()); print('CUDA version:', torch.version.cuda)"

For comprehensive model troubleshooting including architecture mismatches, missing models, and loading errors, see the dedicated Model Issues page.

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Network & API Issues

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API Nodes Not Working

Symptoms: API calls fail, timeout errors, quota exceeded

Solutions:

  1. Check API key validity - Verify keys in user settings
  2. Check account credits - Ensure sufficient API credits
  3. Verify internet connection - Test with other online services
  4. Check service status - Provider may be experiencing downtime

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Connection Issues

Symptoms: “Failed to connect to server”, timeout errors

Solutions:

  1. Check firewall settings - Allow ComfyUI through firewall
  2. Try different port - Default is 8188, try 8189 or 8190
  3. Disable VPN temporarily - VPN may be blocking connections
  4. Check proxy settings - Disable proxy if not required

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Frontend Issues

“Frontend or Templates Package Not Updated”:

# After updating ComfyUI via Git, update frontend dependencies
pip install -r requirements.txt

“Can’t Find Custom Node”:

  • Disable node validation in ComfyUI settings

“Error Toast About Workflow Failing Validation”:

  • Disable workflow validation in settings temporarily
  • Report the issue to the ComfyUI team

Login Issues When Not on Localhost:

  • Normal login only works when accessing from localhost
  • For LAN/remote access: Generate API key at platform.comfy.org/login
  • Use API key in login dialog or with --api-key command line argument

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Hardware-Specific Issues

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NVIDIA GPU Issues

“Torch not compiled with CUDA enabled” error:

# First uninstall torch
pip uninstall torch

# Install stable PyTorch with CUDA 12.8
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu128

# For nightly builds (might have performance improvements)
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128

# Verify CUDA support
python -c "import torch; print(torch.cuda.is_available())"

GPU not detected:

# Check if GPU is visible
nvidia-smi

# Check driver version and CUDA compatibility
nvidia-smi --query-gpu=driver_version --format=csv

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AMD GPU Issues

ROCm support (Linux only):

# Install stable ROCm PyTorch (6.3.1 at the time of writing)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.3

# For nightly builds (ROCm 6.4 at the time of writing), which might have performance improvements)
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm6.4

Unsupported AMD GPUs:

# For RDNA2 or older (6700, 6600)
HSA_OVERRIDE_GFX_VERSION=10.3.0 python main.py

# For RDNA3 cards (7600)
HSA_OVERRIDE_GFX_VERSION=11.0.0 python main.py

Performance optimization:

# Enable experimental memory efficient attention (no longer necessary with PyTorch 2.4)
TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1 python main.py --use-pytorch-cross-attention

# Enable tunable operations (slow first run, but faster subsequent runs)
PYTORCH_TUNABLEOP_ENABLED=1 python main.py

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Apple Silicon (M1/M2/M3) Issues

MPS backend setup:

# Install PyTorch nightly for Apple Silicon
# Follow Apple's guide: https://developer.apple.com/metal/pytorch/

# Check MPS availability
python -c "import torch; print(torch.backends.mps.is_available())"

# Launch ComfyUI
python main.py

If MPS causes issues:

# Force CPU mode
python main.py --cpu

# With memory optimization
python main.py --force-fp16 --cpu

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Intel GPU Issues

Option 1: Native PyTorch XPU support (Windows/Linux):

# Install PyTorch nightly with XPU support
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/xpu

# Launch ComfyUI
python main.py

Option 2: Intel Extension for PyTorch (IPEX):

# For Intel Arc A-Series Graphics
conda install libuv
pip install torch==2.3.1.post0+cxx11.abi torchvision==0.18.1.post0+cxx11.abi torchaudio==2.3.1.post0+cxx11.abi intel-extension-for-pytorch==2.3.110.post0+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/

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Getting Help & Reporting Bugs

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Before Reporting a Bug

  1. Check if it’s a known issue:

  2. Try basic troubleshooting:

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How to Report Bugs Effectively

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For ComfyUI Core Issues

Where to report: GitHub Issues

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For Desktop App Issues

Where to report: Desktop GitHub Issues

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For Frontend Issues

Where to report: Frontend GitHub Issues

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For Custom Node Issues

Where to report: Contact the specific custom node developer

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Required Information

When reporting any issue, include:

1

System Information

System Information (can be found in the About page in settings):

  • Operating System (Windows 11, macOS 14.1, Ubuntu 22.04, etc.)
  • ComfyUI version (check About page in settings)
  • Python version: python --version
  • PyTorch version: python -c "import torch; print(torch.__version__)"
  • GPU model and driver version
  • Installation method (Desktop, Portable, Manual, comfy-cli)

2

Desktop App issues

For Desktop App issues, also include:

  • Log files from: C:\Users\<username>\AppData\Roaming\ComfyUI\logs (Windows)
  • Config files from: C:\Users\<username>\AppData\Roaming\ComfyUI (Windows)
3

Problem Details

Problem Details:

  • Clear description of the issue
  • Steps to reproduce the problem
  • Expected vs actual behavior
  • Screenshots or videos if applicable

Error Messages:

  • Full error text from console/terminal
  • Browser console errors (F12 → Console tab)
  • Any crash logs or error dialogs
4

Additional Context

Additional Context:

  • List of installed custom nodes
  • Workflow file (.json) that reproduces the issue
  • Recent changes (new installations, updates, etc.)

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Community Resources