How to Install and Use ComfyUI and SwarmUI on Massed Compute and RunPod Private Cloud GPU Services

If your GPU is not strong enough to run Generative AI models this is the tutorial that you need. Or you want to scale your generation speed by using multiple GPUs at the same time again this is excellent tutorial. In this tutorial I will show how to setup ComfyUI and SwarmUI literally 1-click on Massed Compute and RunPod and use your most liked best image and video generation models like Qwen, FLUX, Wan 2.2 and more. 🔗 Important Links: Download ComfyUI Installer: https://www.patreon.com/posts/105023709 Download SwarmUI Installer and Model Downloader: https://www.patreon.com/posts/114517862 Previous Detailed Windows Tutorial (Recommended Watch): https://youtu.be/c3gEoAyL2IE ⏰ TIMESTAMPS / CHAPTERS 0:00 Introduction & Tutorial Goals 0:39 Downloading the ComfyUI Installer & Reading Update News 1:06 Downloading the SwarmUI Installer & Checking Changelogs 1:25 Extracting ComfyUI & Opening the Massed Compute Instructions 1:48 Deploying on Massed Compute: GPU Selection 2:03 Applying the 'SECourses' Coupon Code 2:30 Choosing a Multi-GPU Machine for the Demo 2:55 Installing the ThinLinc Remote Desktop Client 3:12 Crucial: Configuring ThinLinc Local Devices & Shared Drives 3:52 Connecting to the Massed Compute Desktop 4:13 Transferring Installer Files to the Remote Machine 5:18 Installing ComfyUI via Terminal Command 6:31 Updating the Pre-Installed SwarmUI on the Machine 7:00 Preparing the SwarmUI Model Downloader 7:48 Launching the Downloader & Downloading Model Bundles 8:46 Launching SwarmUI with a Public Cloudflare Link 9:11 Configuring the First Backend (GPU 0) with Sage-Attention 10:04 Adding and Configuring the Second Backend (GPU 1) 10:33 Importing the 'Amazing Swarm' Presets 11:04 Live Demo: Generating Realistic Images 12:48 Monitoring the Multi-GPU Generation Process 13:32 How to Download Your Generated Images (Two Methods) 14:12 IMPORTANT: How to Stop Billing by Deleting the Machine 15:07 Part 2: Starting the RunPod Installation 15:26 Deploying a RunPod Pod: