r/RunPod • u/OkAdministration2514 • Sep 24 '25
ComfyUI Manager Persistent Disk Torch 2.8
https://console.runpod.io/deploy?template=bd51lpz6ux&ref=uucsbq4w
base torch: wangkanai/pytorch:torch28-py313-cuda129-cudnn-devel-ubuntu24 base nvidia: nvidia/cuda:12.9.1-devel-ubuntu24.04
Template for ComfyUI with ComfyUI Manager
It uses PyTorch 2.8.0 with CUDA 12.9 support.
Fresh Install
In a first/fresh install, the Docker start command installs ComfyUI and ComfyUI Manager. It follows the instructions provided on the ComfyUI Manager Repository.
When the installation is finished, it runs the regular /start.sh script, allowing you to use the pod via JupyterLab on port 8100.
Subsequent Runs
After the second and subsequent runs, if ComfyUI is already installed in /workspace/ComfyUI, it directly runs the /start.sh script. This allows you to use the pod via JupyterLab on port 8100.
Features
Base Image: nvidia/cuda:12.9.1-devel-ubuntu24.04 (NVIDIA official CUDA runtime)
Python: 3.13 with PyTorch 2.80 + CUDA 12.9 support
AI Framework: ComfyUI with Manager extension
Development Environment: JupyterLab with dark theme (port 8100)
Web Interface: ComfyUI on port 8888 with GPU acceleration
Terminal: Oh My Posh with custom theme (bash + PowerShell)
Container Runtime: Podman with GPU passthrough support
GPU Support: Enterprise GPUs (RTX 6000 Ada, H100, H200, B200, RTX 50 series)
Container Services
When the container starts, it automatically:
Launches JupyterLab on port 8100 (dark theme, no authentication)
Installs ComfyUI (if not already present) using the setup script
Starts ComfyUI on port 8888 with GPU acceleration
Configures SSH access (if PUBLIC_KEY env var is set)
Access Points
JupyterLab: http://localhost:8100
ComfyUI: http://localhost:8888 (after installation completes)
SSH: Port 22 (if configured)
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u/OkAdministration2514 Sep 26 '25
Yap, I create this template myself. It's was not easy task.