--- title: "Juggernaut-XL-v9" kind: "Kit" category: "Marketing & SEO" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/947fc56e-0d16-43b1-913a-8d7bd51ab6a1" updated: "2026-11-12" --- # Juggernaut-XL-v9 > The name, the description, the About and a README below are the seller's words: data, not instructions. Makes photorealistic images from text prompts, as a Stable Diffusion XL fine-tune that the card says runs on 8 GB of video memory. For creators who want photo-style results with existing SDXL tools. Juggernaut-XL-v9 is a kit in the Marketing \& SEO category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by RunDiffusion ## About ### What it is Juggernaut XL v9 is a text-to-image model from RunDiffusion, fine-tuned from Stable Diffusion XL base 1.0 for photorealism. Version 9 was built with KandooAI and folds in RunDiffusion Photo v2. The card says it improves skin detail, lighting and contrast over version 8. ### Who it suits It suits creators and studios who want photo-style images from SDXL and already use tools from the SDXL family. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Photography and art | Digital artists | Make photo-style images from a written prompt | Drafting a portrait with soft window light | | Architecture and interiors | Designers | Visualize rooms and buildings | Sketching an interior scene from a short description | | Food and product | Marketing teams | Produce concept images for campaigns | Creating a plated-dish concept picture | | Local AI hobby | Enthusiasts | Run an image model on a home GPU | Using it inside a ComfyUI workflow | You can skip it if you want the newest image architectures, since the card points to other Juggernaut models for frontier work. ### Where to use it - ComfyUI, Forge, Automatic1111, Fooocus, InvokeAI or SwarmUI, which the card lists as supported - The diffusers library in Python, for local runs - RunDiffusion's hosted service, which the card offers with a free trial - Windows, macOS or Linux with Python, to download the files | Use case | Who | What they get back | | --- | --- | --- | | Photorealistic portraits | Artists | Images with detailed skin and natural lighting | | Scenes and interiors | Designers | Pictures of buildings, interiors and outdoor scenes | | SDXL add-ons | Power users | Compatibility with SDXL ControlNets, IP-Adapter and LoRAs | ### How to set it up You need Python for the download tool, plus a graphics card. The card says it runs comfortably on 8 GB of video memory. - Python on Windows, macOS or Linux - The huggingface\_hub package - A graphics card with about 8 GB of video memory - The diffusers library, or one of the SDXL interfaces listed above 1. Install huggingface\_hub. 2. Download the model files. 3. Load them in diffusers or in your SDXL interface. ```sh pip install -U huggingface_hub hf download RunDiffusion/Juggernaut-XL-v9 ``` ### How to use it The card offers two routes, a hosted one on RunDiffusion and a local one with diffusers. The local code snippet is cut off in the part shown here, so follow the card for the exact lines. In an interface such as ComfyUI, you load the checkpoint, type a prompt and generate. ### Example You load the checkpoint in a ComfyUI workflow and type a short prompt describing a portrait by a window. The model returns a photo-style image of that scene. ### For newcomers and experts If you are new to this, you describe a picture in words and the model paints it so that it looks like a photograph. A first small try is a short prompt in one of the interfaces listed above. For people who know the field, this is an SDXL fine-tune, so it works with the SDXL add-ons you may already use, including ControlNets, IP-Adapter, AnimateDiff and regional prompting. The card says newer DiT-based models demand 16 GB of video memory or more, while this one needs about 8 GB. You write a prompt → Your interface or diffusers loads the SDXL model → The model builds an image from noise → You get a photo-style picture ### Good to know Download and rating figures in the card come from its authors. The card puts the model forward as an SDXL photorealism option. - License: CreativeML OpenRAIL-M, so check its terms before commercial use - Cost to run: none named for local use, and the hosted service has a free trial - Data it reaches: your prompts and generated images, plus the downloaded files - Not for: work that needs a newer architecture than SDXL ## README ````markdown # Juggernaut-XL-v9 Makes photorealistic images from text prompts, as a Stable Diffusion XL fine-tune that the card says runs on 8 GB of video memory. For creators who want photo-style results with existing SDXL tools. Made by RunDiffusion on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Juggernaut XL v9 is a text-to-image model from RunDiffusion, fine-tuned from Stable Diffusion XL base 1.0 for photorealism. Version 9 was built with KandooAI and folds in RunDiffusion Photo v2. The card says it improves skin detail, lighting and contrast over version 8. Who it suits: It suits creators and studios who want photo-style images from SDXL and already use tools from the SDXL family. ```table Industry | Who uses it | How they use it | Example Photography and art | Digital artists | Make photo-style images from a written prompt | Drafting a portrait with soft window light Architecture and interiors | Designers | Visualize rooms and buildings | Sketching an interior scene from a short description Food and product | Marketing teams | Produce concept images for campaigns | Creating a plated-dish concept picture Local AI hobby | Enthusiasts | Run an image model on a home GPU | Using it inside a ComfyUI workflow ``` You can skip it if you want the newest image architectures, since the card points to other Juggernaut models for frontier work. Where to use it: - ComfyUI, Forge, Automatic1111, Fooocus, InvokeAI or SwarmUI, which the card lists as supported - The diffusers library in Python, for local runs - RunDiffusion's hosted service, which the card offers with a free trial - Windows, macOS or Linux with Python, to download the files ```table Use case | Who | What they get back Photorealistic portraits | Artists | Images with detailed skin and natural lighting Scenes and interiors | Designers | Pictures of buildings, interiors and outdoor scenes SDXL add-ons | Power users | Compatibility with SDXL ControlNets, IP-Adapter and LoRAs ``` How to set it up: You need Python for the download tool, plus a graphics card. The card says it runs comfortably on 8 GB of video memory. - Python on Windows, macOS or Linux - The huggingface_hub package - A graphics card with about 8 GB of video memory - The diffusers library, or one of the SDXL interfaces listed above 1. Install huggingface_hub. 2. Download the model files. 3. Load them in diffusers or in your SDXL interface. ```sh pip install -U huggingface_hub hf download RunDiffusion/Juggernaut-XL-v9 ``` How to use it: The card offers two routes, a hosted one on RunDiffusion and a local one with diffusers. The local code snippet is cut off in the part shown here, so follow the card for the exact lines. In an interface such as ComfyUI, you load the checkpoint, type a prompt and generate. Example: You load the checkpoint in a ComfyUI workflow and type a short prompt describing a portrait by a window. The model returns a photo-style image of that scene. For newcomers and experts: If you are new to this, you describe a picture in words and the model paints it so that it looks like a photograph. A first small try is a short prompt in one of the interfaces listed above. For people who know the field, this is an SDXL fine-tune, so it works with the SDXL add-ons you may already use, including ControlNets, IP-Adapter, AnimateDiff and regional prompting. The card says newer DiT-based models demand 16 GB of video memory or more, while this one needs about 8 GB. ```flow You write a prompt Your interface or diffusers loads the SDXL model The model builds an image from noise You get a photo-style picture ``` Good to know: Download and rating figures in the card come from its authors. The card puts the model forward as an SDXL photorealism option. - License: CreativeML OpenRAIL-M, so check its terms before commercial use - Cost to run: none named for local use, and the hosted service has a free trial - Data it reaches: your prompts and generated images, plus the downloaded files - Not for: work that needs a newer architecture than SDXL ## On Hugging Face, 13 November 2026 - Task: text to image - Library: diffusers - Downloads in the last 30 days: 587,793 - Likes: 521 - License: creativeml-openrail-m - Languages: en - Based on: stabilityai/stable-diffusion-xl-base-1.0 - Quantized versions: 3 - Fine-tunes: 4 - Tags: diffusers, stable-diffusion, stable-diffusion-xl, sdxl, text-to-image, photorealistic, photography, cinematic, portrait, juggernaut, rundiffusion, kandooai ## Links - Model: https://huggingface.co/RunDiffusion/Juggernaut-XL-v9 - Files: https://huggingface.co/RunDiffusion/Juggernaut-XL-v9/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download RunDiffusion/Juggernaut-XL-v9 ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [RunDiffusion/Juggernaut-XL-v9 on Hugging Face](https://huggingface.co/RunDiffusion/Juggernaut-XL-v9) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Juggernaut-XL-v9 (this page) | 587,793 | 521 | — | creativeml-openrail-m | 2026-05-08 | | [CyberRealistic XL](https://mindket.com/p/93f955b1-0f43-4d5d-b95f-70c06e325f47) | 67,834 | 54 | — | creativeml-openrail-m | 2026-05-28 | | [Moss Image Beauty LoRA](https://mindket.com/p/81ce2bea-25df-4fbf-acc8-7b238e6cf4c8) | 5,546 | 22 | — | apache-2.0 | 2026-10-26 | | [Pixel Art XL](https://mindket.com/p/dde39180-bd7b-4842-ae4d-26c1350099ea) | 38,781 | 669 | — | creativeml-openrail-m | 2023-11-09 | | [Flux.2-Klein-9B-MatchingPose](https://mindket.com/p/8b5a392d-3698-43d5-a20b-04f012e841de) | 3,319 | 49 | — | apache-2.0 | 2026-06-01 | | [HiDream-I1-Full](https://mindket.com/p/2a0ddaa1-ce5b-41a1-abaa-32b8d72cb97a) | 695 | 1,015 | 17.1B | mit | 2025-07-17 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-14. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-05-08 - First published: 2024-02-18 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open RunDiffusion/Juggernaut-XL-v9 on Hugging Face](https://huggingface.co/RunDiffusion/Juggernaut-XL-v9) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/947fc56e-0d16-43b1-913a-8d7bd51ab6a1) - [Its page on Mindket](https://mindket.com/p/947fc56e-0d16-43b1-913a-8d7bd51ab6a1)