Please read our in-depth Guideline for prompting at Cagliostrolab Blog

Overview

Animagine XL 4.0, also stylized as Anim4gine, is the ultimate anime-themed finetuned SDXL model and the latest installment of Animagine XL series. Despite being a continuation, the model was retrained from Stable Diffusion XL 1.0 with a massive dataset of 8.4M diverse anime-style images from various sources with the knowledge cut-off of January 7th 2025 and finetuned for approximately 2650 GPU hours. Similar to the previous version, this model was trained using tag ordering method for the identity and style training.

With the release of Animagine XL 4.0 Opt (Optimized), the model has been further refined with an additional dataset, improving stability, anatomy accuracy, noise reduction, color saturation, and overall color accuracy. These enhancements make Animagine XL 4.0 Opt more consistent and visually appealing while maintaining the signature quality of the series.

Changelog

• 2025-02-13 – Added Animagine XL 4.0 Opt and Animagine XL 4.0 Zero

• Better stability for more consistent outputs

• Enhanced anatomy with more accurate proportions

• Reduced noise and artifacts in generations

• Fixed low saturation issues, resulting in richer colors

• Improved color accuracy for more visually appealing results

• 2025-01-24 – Initial release

Model Details

• Developed by: Cagliostro Research Lab

• Model type: Diffusion-based text-to-image generative model

• License: CreativeML Open RAIL++-M

• Model Description: This is a model that can be used to generate and modify specifically anime-themed images based on text prompt

• Fine-tuned from: Stable Diffusion XL 1.0

Usage Guidelines

The summary can be seen in the image for the prompt guideline.

1. Prompt Structure

The model was trained with tag-based captions and the tag-ordering method. Use this structured template:

1girl/1boy/1other, character name, from which series, rating, everything else in any order and end with quality enhancement

2. Quality Enhancement Tags

Add these tags at the end of your prompt:

masterpiece, high score, great score, absurdres

3. Recommended Negative Prompt

lowres, bad anatomy, bad hands, text, error, missing finger, extra digits, fewer digits, cropped, worst quality, low quality, low score, bad score, average score, signature, watermark, username, blurry

4. Optimal Settings

• CFG Scale: 4-7 (5 Recommended)

• Sampling Steps: 25-28 (28 Recommended)

• Preferred Sampler: Euler Ancestral (Euler a)

5. Recommended Resolutions

6. Final Prompt Structure Example

1girl, firefly \(honkai: star rail\), honkai \(series\), honkai: star rail, safe, casual, solo, looking at viewer, outdoors, smile, reaching towards viewer, night, masterpiece, high score, great score, absurdres

Special Tags

The model supports various special tags that can be used to control different aspects of the image generation process. These tags are carefully weighted and tested to provide consistent results across different prompts.

Quality Tags

Quality tags are fundamental controls that directly influence the overall image quality and detail level. Available quality tags:

• masterpiece

• best quality

• low quality

• worst quality

Score Tags

Score tags provide a more nuanced control over image quality compared to basic quality tags. They have a stronger impact on steering output quality in this model. Available score tags:

• high score

• great score

• good score

• average score

• bad score

• low score

Temporal Tags

Temporal tags allow you to influence the artistic style based on specific time periods or years. This can be useful for generating images with era-specific artistic characteristics. Supported year tags:

• year 2005

• year {n}

• year 2025

Rating Tags

Rating tags help control the content safety level of generated images. These tags should be used responsibly and in accordance with applicable laws and platform policies. Supported ratings:

• safe

See the full description on the original page