RealVisXL V5.0 GGUF

RealVisXL V5.0 GGUF

Generates pictures from text on your own computer using GGUF copies of RealVisXL V5.0 with stable-diffusion.cpp. For people who want local image generation with a lighter or a higher quality file.

Made by off-grid-ai 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: This is a set of GGUF files of SG161222's RealVisXL V5.0 image model, converted by off-grid-ai so it can make pictures on your own device with stable-diffusion.cpp. The conversion used the converter built into that program, so the tensors carry the right names and load directly. The card says other community GGUF quants of this model were exported wrongly and fail to load.

Who it suits: It suits people who want text to image on their own computer instead of a cloud service. The files were built for the Off Grid AI Desktop app, and they also work from a terminal.

Industry | Who uses it | How they use it | Example
Design | Designers and illustrators | Generate pictures from a text prompt on their own computer | A 1024 by 1024 picture written to out.png
Software | App developers | Ship a local image model inside a desktop app | Off Grid AI Desktop, the app these files were built for
Hobby | Hobbyists with modest hardware | Pick the lighter file to use less RAM | The Q4_K_S file in place of the Q8_0 file

You can skip it if you want the original full precision model or anything other than image generation.

Where to use it:

• A terminal running the sd program from stable-diffusion.cpp, on Windows, macOS or Linux
• Off Grid AI Desktop, a private app that runs AI on your own device

Use case | Who | What they get back
Make a picture from a prompt | Designers and hobbyists | An image file at the size you set
Run image generation inside an app | App developers | A local model file the app can load
Save memory on a small machine | Anyone with limited RAM | A lighter quantized file

How to set it up:

• Python and pip, to download the files
• The sd program from stable-diffusion.cpp, which does the image generation
• Enough memory for the file you pick, about 1.7 GB at 4-bit by estimate

1. Install the Hugging Face hub package.
2. Download the model files to your computer.
3. Choose a file: Q8_0 for best quality, or Q4_K_S for lower RAM use.

pip install -U huggingface_hub
hf download off-grid-ai/realvisxl-v5.0-GGUF

How to use it: Run the sd program with the file you chose and your prompt. This command writes one 1024 by 1024 picture to out.png.

sd -M img_gen -m realvisxl-v5.0-Q8_0.gguf -p "your prompt" -o out.png \
  -W 1024 -H 1024 --steps 24 --cfg-scale 5 --sampling-method dpm++2m

Tool | What it does
sd -M img_gen | Runs the program in image generation mode
-m | Points to the GGUF model file
-p | Holds your text prompt
-o | Names the output picture
-W and -H | Set the width and height in pixels
--steps, --cfg-scale, --sampling-method | Set the number of steps, how closely the picture follows the prompt, and the sampler

Example: Put a prompt such as "a red bicycle leaning on a brick wall at sunset" where the command says your prompt. When it finishes, out.png holds the generated picture at 1024 by 1024.

For newcomers and experts: GGUF is a file format for running models on your own machine. Start with the Q4_K_S file if your computer has little RAM, and switch to Q8_0 when you want the best quality. Run the command above with one prompt and look at out.png.

In the Q4_K_S file, stable-diffusion.cpp wrote the weight tensors as Q4_K and left the other tensors as F16, BF16 or F32. Q4_K_S is the closest standard label, so Hugging Face can list it. Hugging Face counts 3.5B parameters. This is a format conversion only.

You write a text prompt
The sd program loads the GGUF file
The model runs the sampling steps
A picture is written to out.png

Good to know: Nothing here is a new model. All credit for the image model belongs to its original creators, and the same license terms apply to this copy.

• License: openrail++, inherited from the original model together with its usage limits
• Cost to run: none named, you use your own hardware
• Data it reaches: files on your computer, and the picture file you tell it to write
• Not for: other tasks than image generation, or anyone who needs the original unconverted model

On Hugging Face, 13 November 2026

• Task: text to image
• Parameters: 3.5B
• Weights: about 1.7 GB at 4-bit (estimate)
• Formats: GGUF
• Downloads in the last 30 days: 6,316
• Likes: 3
• License: openrail++
• Based on: SG161222/RealVisXL_V5.0
• Tags: gguf, stable-diffusion, sdxl, image-generation, quantized, off-grid, text-to-image

Links

• Model: https://huggingface.co/off-grid-ai/realvisxl-v5.0-GGUF
• Files: https://huggingface.co/off-grid-ai/realvisxl-v5.0-GGUF/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download off-grid-ai/realvisxl-v5.0-GGUF

Then follow the usage in its model card. Nothing in this kit runs by itself.