
ComfyUI - an open-source, node-based graphical interface for running and building generative AI workflows for content creation - published major updates this past month, including up to 40% performance improvements for NVIDIA RTX GPUs, and support for new AI models including Wan 2.2, Qwen-Image, FLUX.1 Krea [dev] and Hunyuan3D 2.1.
NVIDIA also released NVIDIA TensorRT-optimized versions of popular diffusion models like Stable Diffusion 3.5 and FLUX.1 Kontext as NVIDIA NIM microservices, allowing users to run these models in ComfyUI up to 3x faster and with 50% less VRAM.
Plus, an update to NVIDIA RTX Remix - a platform that lets modders remaster classic games - launched today, adding an advanced path-traced particle system that delivers stunning visuals to breathe new life into classic titles.
ComfyUI v3.57 Gets a Performance Boost With RTX NVIDIA has collaborated with ComfyUI to boost AI model performance by up to 40%. To put this in perspective, GPU generation upgrades typically only deliver a 20-30% performance boost.
Measured on a GeForce RTX 5090 with Intel Core i9 14900K. All models run on ComfyUI using 20 steps at 1024 1024 resolution. Developers interested in optimizing performance and efficiency of diffusion models on their apps can read more on how NVIDIA helps accelerate these workloads in the developer forum.
State-of-the-Art AI Models, Accelerated by RTX Incredible models for AI content creation have been released in the last weeks, all of which are now available in ComfyUI.
Wan 2.2 is a new video model that provides incredible quality and control for video generation on PCs. It's the latest model from Wan AI - a creative AI platform offering an impressive lineup of AI models, including Text to Image, Text to Video, Image to Video and Speech to Video. GeForce RTX and NVIDIA RTX PRO GPUs are the only GPUs capable of running Wan 2.2 14B models in ComfyUI without major delays in output. Check out the example below created with the single prompt: A robot is cracking an egg, but accidentally hits it outside the bowl.
Qwen-Image is a new image generation foundation model from Alibaba that achieves significant advances in complex text rendering and precise image editing. It excels at rendering complex text, handling intricate editing and maintaining both semantic and visual accuracy in generated images. The model runs 7x faster on a GeForce RTX 5090 vs. Apple M3 Ultra.
Qwen-Image excels in text generation across numerous languages, as well as image generation. Black Forest Labs' new FLUX.1 Krea [dev] AI model is the open-weight version of Krea 1, offering strong performance and trained to generate more realistic, diverse images that don't contain oversaturated textures. Black Forest Labs calls the model opinionated, as it offers a wide variety of diverse, visually interesting images. This model runs 8x faster on a GeForce RTX 5090 vs. Apple M3 Ultra.
Black Forest Labs' new FLUX.1 Krea [dev] model offers more realistic, diverse imagery.Hunyuan3D 2.1 is a fully open-source, production-ready 3D generative system that transforms input images or text into high-fidelity 3D assets enriched with physically based rendering materials. Core components include a 3.3-billion-parameter model for shape generation and a 2-billion-parameter model for texture analysis to quickly generate more realistic materials. It all runs faster on Blackwell RTX GPUs.
Go from image to 3D model quickly with Hunyuan3D 2.1. Get Started With Advanced Visual Generative Techniques Visual generative AI is a powerful tool, but getting started can be difficult even for technical experts and learning to use more advanced techniques typically takes months.
ComfyUI makes it easy to get started with advanced workflows by providing templates or preset nodes that achieve a specific task, like keeping a character constant throughout different generations, adjusting the light of an image or loading a fine-tuning. This allows even non-technical artists to easily use advanced AI workflows.
These are 10 key techniques to get started with generative AI:
Guide video generation by defining the start frame and end frame: Upload a start and end frame, as well as how a video clip should begin and end. Wan 2.2 can then generate a smooth, animated transition, filling the in-between frames to create a coherent animation. It's ideal for making animations, scene shifts or defining poses.
Edit images with natural language: Use FLUX.1 [dev] KONTEXT to edit specific text sections of an image.
Upscale images or videos: Take image or video at a lower resolution and increase its resolution and detail quality by adding realistic, high-frequency details.
Control area composition: Assume more granular control over image generation by controlling the arrangement and layout of visual elements within specific regions of an image.
Restyle images: Use FLUX Redux to create different variations of images while preserving core visual elements and details.
Tap image-to-multiview-to-3D models: Use multiple images of an object captured from different angles to create a high-fidelity, textured 3D model.
Transform sound to video: Create video clips or animations directly from audio inputs such as speech, music or environmental sounds.
Control video trajectory: Automatically guide the motion of objects, camera or scenes within videos.
Edit images with inpainting: Fill in or alter missing or unwanted parts of a digital image in a visually seamless, contextually consistent way with surrounding areas.
Expand the canvas with outpainting: Generate new image content to extend the boundaries of an existing image or video footage, add detail to cropped sections or complete a scene.
Follow ComfyUI on X for updates to creative templates and workflows.
Expand Your ComfyUI Zone ComfyUI plug-ins enable users to add generative AI work
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