AlbedoBase XL

8152°

#3d #anime #realistic #base #2d #cinematic

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Created by

albedobond

on Civitai

AlbedoBase XL v1.2 model by albedobond

Creator notes

If you've found value in the model, please consider offering your support. Your contribution will be devoted entirely to advancing the SDXL community. ㅤ|ㅤ ㅤ |ㅤ AlbedoBase XL (SFW&NSFW) The refiner is unnecessary, and VAE is included. GOAL Stable Diffusion XL has 3.5 billion parameters (excluding the Refiner), which is about 3.6 times more than the SD v1.5 version. I believe that this is not just a number, but a number that can lead to a significant improvement in performance. It has been a while since we realized that the overall performance of SD v1.5 has improved beyond imagination thanks to the explosive contributions of our community. Therefore, I am working on completing this AlbedoBase XL model in order to optimally reproduce the performance improvement that occurred in v1.5 in this XL version as well. My goal is to directly test the performance of all Checkpoints and LoRAs that are publicly uploaded to Civitai, and merge only the resources that are judged to be optimal after passing through several filters. This will surpass the performance of image-generating AI of companies such as Midjourney. As of now, AlbedoBase XL v3.1 Large has merged about 200 selected checkpoints and 251 LoRAs. LOG v3.1-Large • Merged over 50 selected latest versions of SDXL models using the recursive script employed in V3. The spec grid(370.7 MB): v3-mini I sincerely apologize for keeping you waiting for such a long time. I’ve been dealing with some personal matters, and while working on the new version, I also faced health issues. Even as I write this, I am still struggling with these challenges. I felt it wouldn’t be enough to just provide a brief update, so I kindly ask for your understanding as I share this more detailed message. Since the release of version 2.0, I have been dedicating myself to studying deep learning independently. I don’t have a formal degree, and apart from a modest aptitude for programming, only my background is in the arts. As a result, I lack the mathematical and scientific foundation to achieve significant breakthroughs, given the time and effort I’ve invested. Despite this, the experience of immersing myself in this self-directed study and research has been an invaluable treasure in my life. Recently, I stumbled upon an idea that could potentially be a significant breakthrough. After reworking hundreds of formulas and methods since version 2.0, I managed to develop a rather intriguing and successful algorithm. The model merging process was based on SDXL1.0 and SD1.5, along with other carefully curated models. These were categorized into five primary classifications: “ANIME,” “REALISM,” “ARTISTIC,” “NSFW,” and “BASE,” and fed into the merging algorithm as datasets. This approach has resulted in some fascinating outcomes. However, as challenging as the algorithm development was, nothing has been as daunting as the performance testing phase. My physical and mental health deteriorated significantly during this period, to the point where I realized I couldn’t continue this work on my own. This is what ultimately led me to decide to release this version. And now, I am thrilled to announce the release of the much-anticipated AlbedoBaseXL V3 Mini version. While this model is a smaller-scale merge, it is not limited to any specific area and performs remarkably well across various domains. It has the potential to serve as a new base model for SDXL1.0. (For reference, my merging algorithm is not a “linear merging,” so it can essentially be considered a new fine-tuned model.) This model, along with the existing AlbedoBase models, is versatile and surpasses all previous versions in every aspect. (The NSFW content, while not extreme, offers a broader range of expression compared to previous versions like v2.1. A dedicated NSFW merging model will be released in the future.) On another note, I’ve noticed that many shared models have recently begun to adopt licenses that prohibit merging or external commercialization. This has been a disappointment, as it has prevented me from using some truly excellent models for merging. I would like to express my heartfelt gratitude to the model developers who have provided free licenses, allowing their high-quality models—products of considerable time and effort—to be used for merging. I’ll be back soon. I eagerly look forward to your performance tests across a wide range of areas, including ANIME, REALISM, ARTISTIC, 2.5D, 3D, and NSFW. As model developers, we only plant the seeds. It is ultimately you, the model users and artists, who cultivate them and bring forth the flowers and fruits. Thank you, as always. For those who wish to support my work with a small financial contribution, please consider using the links below. I am currently unable to secure employment and face an uncertain future regarding my livelihood. The spec grid(380.5 MB): v2.1 Re-merge and adjust v0.1 to 2.0 using new merging algorithm and formula. The spec grid(424.5 MB): v2.0 I'd like to thank everyone who helped me on the side. Without you guys, the release date would probably have been much later. Thank you so much! - I have written a custom script to converge the existing AlbedoBase XL models into one. Intricately aligning the row and column weights of all U-NET and CLIP blocks according to a unique formula of mine. - If you encounter a bug in image generation (if nothing is generated), please switch to CLIP SKIP 2 or modify the prompt slightly! There may be combinations of prompts that CLIP does not recognize. In that case, you can change the order of words, use different words, or, most simply, change the CLIP SKIP. I will gradually work on resolving these issues in the future like v1.3. The spec grid(403.5 MB): v1.3 - In order to illustrate the quality associated with the model's randomness, I standardized the seed value at '9' for all showcase images intended for sampling and proceeded with their immediate generation. - Especially with

Trigger words

all in one

photo

anime

game

photorealistic

cinematic

design

base

4,975 downloads · 361 likes on Civitai

SHA256

8A8EFA5AD281317D3656ECE3D4CA81542DDE55DEB2079B2B37B48F145355C935

AlbedoBase XL Popularity Trend

Heat score, last 12 months

Heat score

8,152°

This week

▼

0.6%

8,155° then, 8,152° now

This month

▼

2.5%

8,164° then, 8,152° now

Past year

▼

29.5%

8,300° then, 8,152° now

7,000°

Floor

The scale runs from 0° to 9,999°. Everything below 7,000° is kept for models no source reports on yet, which carry a stand-in number there so lists stay complete. 7,000° is where measured data begins: a model with real data but almost no downloads sits at the floor, and the measurements fill the degrees above it. The floor says nothing about the model; only the degrees above it do, and they are what separates one model from another.

+1,112°

Civitai downloads

4,975 downloads of this exact version on Civitai. Downloads are the heaviest ingredient and are counted on a log scale: ten times the downloads adds the same 300°, so a model with a million downloads is not a thousand times hotter than one with a thousand. The six download sources share that one term, split between them in proportion to their counts.

+384°

Likes

361 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.

+3°

Adoption rate

About 0 downloads a day, measured between two readings of the sources, never guessed from a lifetime average. Speed weighs a quarter of the download term, so a fresh surge shows without letting a one-day spike outrank years of use.

+150°

Full model

+150° because this is a full model: a checkpoint, the weights themselves. A LoRA or an embedding is an add-on to someone else's weights and does not outrank a checkpoint of equal popularity.

−497°

Age

−497° because the SDXL weights came out in 2023. Every model inherits the age of the weights it is built on: 150° a year, up to 750°, and it keeps growing until then. Without it the top of the list would be 2022 and 2023 checkpoints on the strength of downloads that had years to pile up.

Show detailed breakdown

Every number on this site can be checked. This model's heat score is 8,152°, and here it is built one ingredient at a time, with the running total after each: the floor, the degrees each source adds, the bonus for the kind of model and what the age of its weights takes away. The colors are the bands of the chart above. The glossary at the end defines every term.

1
Start at the floor.
Why 7,000° and not zero: the scale runs from 0° to 9,999°, and the part below 7,000° is reserved for models no source reports on yet, which carry a stand-in number there so the lists stay complete and never outrank a model with data. 7,000° is where measured data begins. A model with real data but almost no downloads sits here; everything that follows is measurement, and the room above the floor holds ten tenfold steps in downloads at 300° each. The floor is the same for every model, so it decides nothing; the degrees above it do.
7,000°
running total
2
Add the downloads.
4,975 download-equivalents in all, from Civitai downloads. Ten times the downloads adds the same 300°, so size matters but never runs away with the score.
+1,112°
8,112°
running total
3
Add the likes.
361 likes and thumbs up, at half the weight of a download.
+384°
8,496°
running total
4
Add the adoption rate.
About 0 downloads a day right now, measured between two readings, at a quarter of the weight.
+3°
8,499°
running total
5
Bonus for a full model.
A checkpoint carries the weights themselves; add-ons do not outrank one of equal popularity.
+150°
8,649°
running total
6
Take off the age.
The SDXL weights came out in 2023: 150° a year, up to 750°, growing until then.
−497°
8,152°
running total
=
The heat score.
Where this model stands on every list of this site. Nothing else adjusts it.
8,152°

Glossary: the terms used here

Heat score: One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
Floor: The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
Download-equivalents: Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
Log scale: Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
Likes: Thumbs up and likes from every source, worth half a download each on the log scale.
Adoption rate: How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
Measured and estimated: Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
Seeder: Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
AI Horde: A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
Generation sites: Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
OpenRouter tokens: A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
Full model (checkpoint): The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
LoRA and embedding: Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
Family and weights: The base a model is built on, such as SD 1.5, SDXL, Flux or Wan. Every model inherits the release date of its family's weights.
Age: Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
Family boost: A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
Stand-in score: A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
New! (grace period): A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
Trend: How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
Typical model: The middle of the catalog: half the models with a figure grew faster over the period, half slower.

How this model's popularity has moved against the rest of the catalog: its growth in downloads, likes and usage over each period, measured against the typical model's growth over the same period, with its heat score at the time. Above the typical growth reads as a rise, below it as a fall. The past is reconstructed from today's totals, the model's first day and its measured download speed where two readings exist; a model that did not exist at the start of a period shows n/a.

Example renders

NSFW

Prompts and settings shared by the people who made these renders on Civitai. Pick a render to see how it was made.