DreamShaper

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Juggernaut-XL-v9

RunDiffusion

The SDXL ecosystem is the single most mature corner of open image generation, and v9 is its most refined photorealism checkpoint. Choose Juggernaut XL v9 when you want: - Photorealism that holds up under scrutiny — skin texture, micro-contrast, and natural lighting that translates from concept to print. - Reasonable hardware — runs comfortably on 8 GB of VRAM, unlike newer DiT-based models that demand 16+ GB. - The full SDXL toolbox — drop-in compatibility with the thousands of SDXL ControlNets, IP-Adapter variants, AnimateDiff, regional prompting tools, and LoRAs already in your workflow. - Battle-tested reliability — 26+ months in production, used in agencies, studios, and shipping…

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Qwen-Image-Lightning

Lightx2v

Please refer to Qwen-Image-Lightning github to learn how to use the models. make sure to install diffusers from main (pip install git+https://github.com/huggingface/diffusers.git)

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Z-Image-Lora

nphSi

+ Always use full LoRa name with "vrtlxxxx" trigger in prompt like "Alba Baptista (vrtlalbabaptista) in a swimming pool". "Woman" or "1girl" will NOT work due to my way i do captions. + Add the gender to the prompt for confusing names like "Alex Jones". + Remove the name when internal model knowledge is bad or censored or is confusing to model like "Sandy Cheeks" or "Kate Middleton". + When using a Lora with multiple triggers (vrtlxx,vrtlyy) do not use the real character name but only trigger or a combination of it. "vrtlMain" always combines all trigger-words. Angourie Rice, January Jones, Julianna Guill, Ursula Corbero, Judith Rakers, Alina Merkau, Kiernan Shipka, Leslie Bibb, Marie…

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Flux2-Klein-9B-True-V2

Wikee Yang

Recommend smthemex/ComfyUIUniBlockSwap plugin for LOW VRAM users, it only requires 4-6GB of VRAM to run the full bf16 model. 您可以尝试一下全新的 ComfyUI GGUF 模型加载插件 smthemex/ComfyUIDifGGUF，它能适配更多的 GGUF 文件格式，并且将很快集成低显存(4-8GB)显卡的 GGUF 模型块卸载管理能力。 Recommend to try the new GGUF ComfyUI loader plugin, smthemex/ComfyUIDifGGUF, it compatible with more GGUF format, and will add low VRAM (4-8GB) management for GGUF soon. 1. 图像的真实感和质感进一步改善，基本接近香蕉(Nano Banana)的水平。 2. 提示词遵循和还原能力，参数适配性和LoRA兼容性进一步改善，。 The V2 version of this model has undergone a full fine-tuning based on FLUX.2-Klein-9B-True-V1. Compared to the V1 version, it has some improvements and enhancements as below: 1. The realism and texture of images…

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Z-Image-Turbo-GGUF

Unsloth AI

Welcome to the official repository for the Z-Image（造相）project! Z-Image is a powerful and highly efficient image generation model with 6B parameters. Currently there are three variants: - Z-Image-Turbo – A distilled version of Z-Image that matches or exceeds leading competitors with only 8 NFEs (Number of Function Evaluations). It offers sub-second inference latency on enterprise-grade H800 GPUs and fits comfortably within 16G VRAM consumer devices. It excels in photorealistic image generation, bilingual text rendering (English & Chinese), and robust instruction adherence. - Z-Image-Base – The non-distilled foundation model. By releasing this checkpoint, we aim to unlock the full potential…

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FLUX.1-dev-gguf

City

This is a direct GGUF conversion of black-forest-labs/FLUX.1-dev As this is a quantized model not a finetune, all the same restrictions/original license terms still apply. The model files can be used with the ComfyUI-GGUF custom node. Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions. Please refer to this chart for a basic overview of quantization types.