ComfyUI Integrations

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Qwen-Image is a multimodal diffusion transformer (MMDiT) foundation model offering state-of-the-art image generation, text rendering, editing, and understanding. It excels at complex text integration, seamlessly embedding alphabetic and logographic scripts into visuals with typographic fidelity, and supports diverse artistic styles from photorealism to impressionism, anime, and minimalist design. Beyond creation, it enables advanced image editing operations such as style transfer, object insertion or removal, detail enhancement, in-image text editing, and human pose manipulation through intuitive prompts. Its built-in vision understanding tasks, including object detection, semantic segmentation, depth and edge estimation, novel view synthesis, and super-resolution, extend its capabilities into intelligent visual comprehension. Qwen-Image is accessible via popular libraries like Hugging Face Diffusers and integrates prompt-enhancement tools for multilingual support.

Comfy Cloud delivers the full functionality of ComfyUI, a node-based visual generative-AI workflow engine, directly in the browser with no setup required. It works anywhere instantly, giving users access to the most powerful server GPUs (such as A100/40 GB) while maintaining stability and performance. All popular open and closed source models (e.g., Stable Diffusion 1.5/SDXL, Qwen-Image, ByteDance SeeDream4.0, Ideogram, Moonvalley) and pre-installed custom nodes are ready to use, while the platform is kept continuously up to date and the underlying infrastructure is managed for you. Users pay only for GPU runtime, not idle time, so editing, setup, and downtime aren’t billed. It supports browser-based creation on any device, handles workflows at scale, and simplifies team deployment with enterprise-grade features such as priority queuing, dedicated resources, and organizational plans.

Floyo is a browser-based platform that brings the full power of ComfyUI into the cloud, letting users find, launch, and run open source AI workflows in seconds with zero installation, zero idle costs, and no complex setup or missing dependencies to manage, so creators can focus on output rather than infrastructure. It offers free unlimited workflow building and editing, hundreds of ready-to-run workflows, and support for thousands of custom nodes and models, including community-uploaded open-source models or user uploads like checkpoints and LoRAs that integrate instantly into workflows. Users can browse and launch workflows with one click, collaborate with team members in shared workspaces that keep private models, inputs, outputs, and settings centralized, and construct a private, production-ready library of workflows tailored to their pipeline.

Wan2.2 is a major upgrade to the Wan suite of open video foundation models, introducing a Mixture‑of‑Experts (MoE) architecture that splits the diffusion denoising process across high‑noise and low‑noise expert paths to dramatically increase model capacity without raising inference cost. It harnesses meticulously labeled aesthetic data, covering lighting, composition, contrast, and color tone, to enable precise, controllable cinematic‑style video generation. Trained on over 65 % more images and 83 % more videos than its predecessor, Wan2.2 delivers top performance in motion, semantic, and aesthetic generalization. The release includes a compact, high‑compression TI2V‑5B model built on an advanced VAE with a 16×16×4 compression ratio, capable of text‑to‑video and image‑to‑video synthesis at 720p/24 fps on consumer GPUs such as the RTX 4090. Prebuilt checkpoints for T2V‑A14B, I2V‑A14B, and TI2V‑5B stack enable seamless integration.

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