Runpod Blog.

Curious about JAX-based diffusion models? This post walks through setting up and running them on Runpod using our GPU pods. It covers environment setup, model launching, and highlights the performance benefits of JAX for image generation workflows.

StyleGAN3 represents a leap forward in GAN-based image generation, offering high-resolution outputs without aliasing artifacts. This post explores how Exploding-cat trained a fork of StyleGAN3—Vision-Aided GAN—on Runpod using 4x A6000 GPUs and a 300K-image dataset. The setup improves quality via CLIP, DINO, and VGG supervision, and demonstrates results at various training milestones.

This guide introduces prompt scheduling in Disco Diffusion, a technique that lets you shift prompts dynamically throughout an image generation run. Learn how to create multi-stage artistic outputs by evolving your prompts over time—ideal for storytelling or animated transitions.

Explore a unique artistic technique using Voronoi noise inits with Disco Diffusion on Runpod. This post walks through setup and tips for generating abstract, stylized results with this custom initialization method—perfect for artists pushing the boundaries of AI-generated visuals.

Compare Google Colab Pro and Runpod across pricing, reliability, and GPU access. Which is the better deal for developers running real AI workloads?

This post compares Runpod’s GPU Cloud with Google Colab Pro and Pro+, highlighting the differences in pricing, compute guarantees, and performance. While Colab offers ease of use via subscription, it lacks guaranteed access to GPUs. Runpod provides consistent access to powerful hardware with flexible, pay-as-you-go pricing.

Runpod now offers encrypted volumes to help secure sensitive data stored in persistent volumes. This post outlines the benefits and tradeoffs of volume encryption, and explains how users can enable it during deployment. Encryption boosts data security but may impact performance.