Get your images shredded and your Generative AI deployments pumped! As GenAI image models bulk up, deploying them efficiently is a challenge. We've got workout routines to whip these models into shape for peak performance. In this session, we explore techniques for slimming down and optimizing generative AI image models for Kubernetes environments. Covering strategies like model pruning, quantization, and efficient serving architectures to reduce memory and computational footprint. Delving into techniques for efficient GPU sharing and data parallelization. Learn best practices for containerizing and deploying optimized models on Kubernetes, ensuring efficient resource utilization and scalability. From lightweight model packaging, multi-stage builds, autoscaling to resource management, we'll share tips and strategies to help you get your AI workouts to the finish line. This session will leave you pumped to tackle Kubernetes deployments with optimized generative AI image models!