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Furkan Gözükara
Furkan Gözükara

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Ultimate ComfyUI & SwarmUI on RunPod Tutorial with Addition RTX 5000 Series GPUs & 1-Click to Setup

#ai #beginners #tutorial #opensource

ComfyUI & SwarmUI on RunPod: The Ultimate Installation Guide

This is the ultimate tutorial for anyone looking to install and use ComfyUI or SwarmUI on the RunPod cloud platform. Whether you want to scale your AI generation or you're a "GPU poor" professional needing access to top-tier GPUs, this guide provides a step-by-step process.

Main Tutorial Video: Watch on YouTube

🚀 Overview

This guide, based on the SECourses tutorial, will walk you through:

  1. Installing ComfyUI on RunPod step by step.
  2. Installing SwarmUI on RunPod step by step.
  3. Connecting SwarmUI to your ComfyUI backend to leverage its ultimate performance and optimizations.

The custom installers used in this tutorial come pre-packaged with essential libraries to maximize performance, including:

  • Torch 2.7
  • CUDA 12.8
  • xFormers
  • Sage Attention
  • Flash Attention
  • Accelerate
  • Triton
  • DeepSpeed
  • ComfyUI Manager
  • and more!

⬇️ Required Files & Installers

⚙️ Tutorial Steps (Video Chapters)

0:00 - Introduction to ComfyUI & SwarmUI Installation on RunPod
0:22 - Advanced Features of the One-Click Installer (Sage Attention, xFormers, Blackwell)
1:03 - Demonstration on RTX Pro 6000 GPU & VRAM Optimization
1:52 - Introducing the High-Speed Unified Model Downloader
2:06 - Starting the Tutorial: Downloading & Preparing the Installer Files
2:45 - Registering and Setting Up Your RunPod Account & Billing
3:04 - Selecting the Optimal RunPod GPU (RTX Pro 6000) and Server
3:54 - Critical Step: Configuring the RunPod Pod Template (PyTorch 2.2.0)
4:20 - Setting Volume Disk, Container Disk, and Exposing HTTP Ports
5:09 - Deploying the Pod and Accessing the Jupyter Lab Interface
5:46 - Uploading and Extracting the ComfyUI Installer on RunPod
6:16 - Running the ComfyUI Installation Command in the Terminal
7:22 - How to Start ComfyUI with Custom Launch Arguments (e.g., --gpu-only)
8:13 - Overview of Included Libraries (Manager, Flash Attention, DeepSpeed, Triton)
9:15 - Using Sage Attention vs. xFormers for Optimal Performance
9:42 - Connecting to the Live ComfyUI Web Interface
10:27 - Introducing the Unified Model Downloader for ComfyUI & SwarmUI
11:01 - Running the Model Downloader and Configuring the Download Path
11:43 - Downloading FLUX Models for a ComfyUI Image Generation Test
13:22 - Configuring the ComfyUI Workflow with Newly Downloaded FLUX Models
15:01 - First Image Generation Test: Analyzing the Incredible Speed
15:53 - Terminating ComfyUI and Preparing for SwarmUI Installation
16:25 - Installing SwarmUI and Setting it Up via the Cloudflared Link
16:50 - How to Configure SwarmUI to Use ComfyUI as a Self-Starting Backend
17:50 - Downloading Wan 2.1 Video Generation Models with the Downloader
19:22 - Importing Presets and Setting up a Wan 2.1 Video Generation in SwarmUI
20:21 - First Video Generation Test with Wan 2.1 (GGUF Version)
21:26 - Analyzing GGUF Performance and Deciding to Test the FP16 Model
22:54 - Downloading the FP16 Wan 2.1 Model for a Performance Comparison
24:01 - Installing Extra Features like RIFE Frame Interpolation
24:41 - Re-configuring SwarmUI to Use the FP16 Model with 16-bit Precision
25:52 - Analyzing FP16 Performance and VRAM Usage (57GB)
26:28 - Final Experiment: Using the Official Wan 2.1 Preset for Best Results
27:28 - Final Results, Conclusion, and How to Get Further Help

🧠 What is ComfyUI?

ComfyUI is an open-source, node-based interface for Stable Diffusion, enabling users to create complex generative art and image processing workflows. Its modular design allows for intuitive drag-and-drop connections, making it accessible for artists and developers. With extensive customization, plugin support, and a vibrant community, ComfyUI empowers users to experiment with AI-driven creativity efficiently.

📚 Additional Tutorials & Resources

💬 Community & Support

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