Running Stable Diffusion on L4 GPUs in the Cloud: A How-To Guide
Blog post from RunPod
Stable Diffusion has transformed AI-generated art by enabling the creation of high-quality images from text prompts, with advanced models like SDXL and ControlNet benefiting from specific hardware configurations for optimal performance. NVIDIA's L4 GPUs are highlighted as a cost-effective and high-performance option for running Stable Diffusion in the cloud, offering 24GB of VRAM, low latency, and energy efficiency, making them suitable for both hobbyists and professional developers. The guide details a step-by-step process for deploying Stable Diffusion on L4 GPUs using the Runpod platform, emphasizing the choice between the Automatic1111 and ComfyUI containers based on user needs, such as real-time generation or complex batch processing. Benchmark tests demonstrate the L4's capability to handle various Stable Diffusion workflows efficiently, while pricing information underscores the affordability of using Runpod's L4 instances for AI art generation. The guide aims to make Stable Diffusion accessible and efficient for a wide range of users, from those experimenting with AI art to those developing sophisticated production pipelines.