Realistic_Vision_V5.1_noVAE

Realistic_Vision_V5.1_noVAE

Generates realistic images from text prompts as a diffusers checkpoint without a built-in VAE, with recommended samplers, negative prompts and upscale settings. For artists, creators and developers.

Made by SG161222 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 version 5.1 of the Realistic Vision text-to-image model, saved without a built-in VAE. It is stored as Safetensors for the diffusers library and has 860M parameters. The author suggests pairing it with a separate VAE to improve quality and remove artifacts, and gives prompt and sampler settings aimed at realistic output.

Who it suits: It suits people who want photographic-looking images from a text prompt, and developers who load Stable Diffusion style checkpoints through diffusers.

Industry | Who uses it | How they use it | Example
Design | Illustrators and designers | Draft realistic reference images from a prompt | Rendering a photographic scene idea before a shoot
Marketing | Content creators | Make realistic visuals for posts and mockups | Generating a lifelike scene to sketch out a campaign
Hobby | AI image enthusiasts | Run a local checkpoint with a chosen VAE | Comparing results with and without the suggested VAE
Software | Developers | Load the weights through the diffusers library | Adding text-to-image generation to an application

If you want drawings, anime or cartoon looks, you can skip it, since the author's negative prompt pushes against those styles.

Where to use it:

• Python with the diffusers library
• Image generation tools that let you pick a sampler, CFG scale and a Hires. fix upscaler
• Windows, macOS or Linux, for downloading the files

Use case | Who | What they get back
Prompt to image | Creators | A realistic-style picture from a written description
Upscaled renders | Artists | A larger image from Hires. fix with the 4x-UltraSharp upscaler
Model testing | Developers | A checkpoint that reads from the diffusers library

How to set it up:

• Python and the Hugging Face hub package
• Disk space for weights of about 3.4 GB in F32
• A separate VAE, which the author recommends for version 5.1, such as the sd-vae-ft-mse-original one from Stability AI

1. Install the Hugging Face hub package.
2. Download the model files.
3. Get the VAE you want to pair with it.
4. Load both in your image generation tool or in diffusers.

pip install -U huggingface_hub
hf download SG161222/Realistic_Vision_V5.1_noVAE

How to use it: Write your prompt, add the author's recommended negative prompt, and choose the sampler and scale below. The card gives a second, shorter negative prompt as an alternative.

(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime:1.4), text, close up, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck

Setting | Value from the card
Sampler | Euler A or DPM++ 2M Karras
CFG scale | 3,5-7
Hires. fix upscaler | 4x-UltraSharp
Hires steps | 0
Denoising strength | 0.25 to 0.7
Upscale by | 1.1 to 2.0

Example: You describe a photographic scene, paste the negative prompt, pick Euler A and set the CFG scale to 5. Then you turn on Hires. fix with 4x-UltraSharp, a denoising strength of 0.4 and an upscale of 1.5. You get a larger realistic-style image.

For newcomers and experts: A text-to-image model draws a picture from a sentence you write. The negative prompt lists what you do not want to see. A good first try is to copy the suggested negative prompt and the sampler settings from the table, then change only the prompt.

Under the hood, this checkpoint has no VAE baked in, so the decoder comes from a separate file. The author says version 5.1 gives cleaner results with one, which is why a pairing step sits in the flow.

Prompt and negative prompt
Checkpoint without a VAE
Separate VAE decodes the image
Hires. fix upscale

Good to know:

• The model is also offered on Mage.Space, which the card names as its main sponsor.
• The hub lists 3 quantized and 8 fine-tuned versions made by other people.
• License: CreativeML OpenRAIL-M, so read its terms before you use or share the images
• Cost to run: none named
• Data it reaches: none named beyond the files you download and the prompts you give it
• Not for: drawing, anime, cartoon or semi-realistic looks, which the recommended negative prompt pushes against

On Hugging Face, 13 November 2026

• Task: text to image
• Library: diffusers
• Parameters: 860M
• Weights: about 3.4 GB in F32; about 430 MB at 4-bit (estimate)
• Formats: Safetensors
• Downloads in the last 30 days: 212,820
• Likes: 281
• License: creativeml-openrail-m
• Quantized versions: 3
• Fine-tunes: 8
• Tags: diffusers, safetensors

Links

• Model: https://huggingface.co/SG161222/Realistic_Vision_V5.1_noVAE
• Files: https://huggingface.co/SG161222/Realistic_Vision_V5.1_noVAE/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download SG161222/Realistic_Vision_V5.1_noVAE

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