TensorRT optimization enhances performance and reduces VRAM requirements for Stable Diffusion 3.5 Large
From NVIDIA: 2025-06-12 09:00:00
Generative AI has revolutionized digital content creation and interaction. AI models like Stable Diffusion 3.5 Large require over 18GB of VRAM, limiting system compatibility. NVIDIA GeForce RTX 40 Series and Ada Lovelace GPUs support FP8 quantization to optimize model performance. Collaboration with Stability AI reduced VRAM consumption by 40% in the Stable Diffusion 3.5 Large model. TensorRT has been reimagined for RTX AI PCs, offering improved performance and smaller package size. NVIDIA and Stability AI have enhanced the performance and reduced VRAM requirements of Stable Diffusion 3.5 with NVIDIA TensorRT acceleration and quantization. The models are now optimized for RTX GPUs, delivering faster and more efficient image generation and editing. TensorRT for RTX is now available as a standalone SDK for developers, offering optimized inference AI library on Windows through Windows ML. NVIDIA founder and CEO Jensen Huang discussed cloud AI infrastructure, agentic AI, and physical AI breakthroughs at NVIDIA GTC Paris at VivaTech. GTC Paris continues with hands-on demos and sessions, providing valuable insights for attendees in person or online. The RTX AI Garage blog series showcases community-driven AI innovations and content related to NVIDIA NIM microservices and AI Blueprints. Stay informed about AI PCs and workstations by subscribing to the RTX AI PC newsletter and following NVIDIA Workstation on LinkedIn.
Read more at NVIDIA: TensorRT Boosts Stable Diffusion 3.5 on RTX GPUs