Illustrious Realism
v4 update:
- Everything is a little better than it was
- A vector has been set for the development of pure realism
V3 Early Access on Boosty - Here (4$ or Subscription)
An engineering approach to realism. No random merges, just surgical correction.
The Philosophy
I created Illustrious Realism for a simple reason: I tested many actual realistic models based on the Illustrious architecture, and I was deeply disappointed. Despite the fact that the version numbers reach ridiculously huge numbers, the actual generation quality remains stagnant. Many models suffer from fundamental issues that their authors seem to ignore, repackaging the same flaws over and over.
This model is my answer to that. It is an attempt to create a genuinely stable, high-quality realistic foundation for Illustrious that actually evolves.
The Engineering Method
This model was built using a strict R&D workflow aimed at fixing the architecture's weak points:
Surgical Correction: Instead of blindly merging checkpoints and LoRAs, I trained custom LoRAs and utilized a proprietary workflow with Masked Sliders (both positive and negative weights).
Anatomy & Detail: This allowed me to surgically target and fix specific weights in the UNet. For example, I used masked training to force the model to render anatomically correct eyes at various distances.
Aesthetic Vision: While the fixes are objective, the aesthetic is my personal vision of a versatile, high-fidelity realism. It is designed to be a broad "True Base" rather than a niche model locked into a specific "amateur" or "cinematic" look.
Usage
Resolutions: Works natively with standard Illustrious resolutions.
Samplers: Use whatever works for your workflow. Personally, I prefer:
Euler A for a softer, more natural look.
DPM++ 2M SDE for sharper, highly detailed results.
This is version 1.0. Future updates will only be released when there is a tangible, technical improvement, not just to inflate the version number.
Description
FAQ
Comments (25)
This feels like a very cool realistic illustrious checkpoint, i'll have to test it! 馃槏
NB: Out of curiosity, since you tested several other checkpoints such as this one, did you had any specific problem with my own realistic model? (i know it has issues, i am just curious of your objective feedback).
Thanks for the kind words! I actually spent some time analyzing your work too. I really respect that you are one of the few creators who is transparent about their recipes and shares the actual scripts/methods.
Regarding your feedback request, here is my honest take:
1. The "Base Mismatch" Risk: I suspect that mixing Perfection Realistic with WaiRealism (or base IXL V2) might be introducing hidden conflicts. If Perfection is based on the older Illustrious V1 (or a different lineage) and you merge it with V2 components, you get deep architectural friction. This often leads to the "funkiness" you mentioned in your description.
2. Methodology (Merge vs. Train): Personally, I moved away from complex block merging because it often feels like trying to graft two different species together鈥攜ou inherit the hidden flaws of both parents. I believe the future is in surgical fine-tuning of a single base. Instead of mixing two checkpoints, I prefer to take one solid base and apply Full Fine-Tuning, or train specific LoRAs (and Masked Sliders) to correct its weaknesses. It gives you more control and avoids those NaN errors you had to script fixes for.
But overall, your model definitely has potential, and I appreciate that you are pushing the boundaries of what merging can do! Keep experimenting!
@llikswonskcalb聽Thanks for takinh the time to check! 馃挄
It's nice but damn is it hard to compete with Zit
That鈥檚 a fair observation, ZIT is indeed a powerhouse.
However, comparing them directly is a bit like comparing apples to oranges. My goal wasn't to compete with massive architectures or heavy-duty models like ZIT or Flux.
I chose Illustrious specifically because it鈥檚 much more lightweight and resource-friendly for local use, and frankly, there was a huge gap in the market鈥攖here were simply no high-quality realistic bases for this specific architecture.
So, think of this not as a competitor to ZIT, but as the best optimized realistic option for those who prefer the Illustrious ecosystem and speed
@llikswonskcalb聽I agree. I don't compare ILL with ZIT for one main reason, time. Even though I have a 4070, there is a lot of file shuffling with ZIT so I get an image about every 1:40 whereas with good ILL models, I get an damn close image in about 14 seconds. It's a waste of time if I don't need words. So I appreciate people who continue to work in SDXL and ILL. Thanks
Glad you found the settings that make the model look epic for you!
However, regarding the description鈥攑lease note that it explicitly says: 'Personally, I prefer'. Sampler behavior can vary significantly depending on the environment (A1111, Forge, ComfyUI), the scheduler type, and simply personal aesthetic taste. For my specific workflow and eye, DPM++ 2M SDE provides the exact balance I aim for.
If DPM++ 3M or DEIS works better for your specific setup鈥攖hat鈥檚 great! That is why we have parameters to tweak. But strictly speaking, there is no 'wrong' or 'bad' recommendation here, just different preferences.
@llikswonskcalb聽I didn't say the model was bad; quite the opposite, it's amazing. I'm currently testing its capabilities in various styles. It's just that at first, I felt the details were lacking; that is, I didn't have a perfect picture of what every lace, button, and emblem should look like. I wanted to skip further testing; another model similar to the others... I switched to another sampler, and WOW. I wrote the comment not to discourage, but to encourage.
@PrincesOfDarkness聽I would add that prompting also plays a role and the way and "style" that one does it will have an effect on what samplers and schedulers work best.
What scheduler type do you recommend for DPM++ 2M SDE? Whenever I try to use it I get bizarre extremely colorful saturated images.
@maximus59111527聽Karras. lower the cfg if you see artifacts
@PrincesOfDarkness聽Any examples of images with those settings?
@Sunkarie聽 Look below in the album where I put the pictures
I agree with your sentiment regarding Realism models, merging and the issues of just adding on top of each other. But I also feel that many force REALISM as the default style, I believe Illustrious can do both Realism and Artist styles without issues, that is what I have tried to do with my merging model, and I have succeeded to some extent.
Unfortunately for me Merging is the fasted way I have to test. I want to try the Lora route just like you did, since I have some ideas on how to achieve what I want, also I hope that gives me better and more controlled results than merging.
Anyways, I have a question, is the IL_XL_2.0_Anime model based on Illustrious 2.0 or its just 2.0 for another reason?
You make a valid point regarding versatility. Illustrious definitely has the capacity to handle both styles, and if that is your goal, merging is indeed the fastest prototyping tool.
However, I strongly encourage you to pursue the LoRA/Training route you mentioned. Once you switch from merging to training, you will realize how much more control you have.
Regarding your question: Yes, exactly. That version is built on the Illustrious XL 2.0 base.
@llikswonskcalb Yes, I do hope I can do it. I still need to find a good database of photos, because I'm not sure if I should just focus on humans or add animals and scenery too, etc. Mostly because I want to restore materials quality with it while adding realism. And then try my theories, since I learned a lot while merging my model.
Because besides merging specific Unets, I decided to go deeper and merge only specific elements (attn1.to_out, attn2.to_q, skip_connection, etc) and specific sections of specific unet blocks. That made me see what a small or big changes could happen with minimal areas merged. Tho I had to modify SuperMerger a bit to make it easier for me lol.
Hopefully I can make Loras work well with my 3060 laptop, previous tests either fail or take ages.
Either way, thanks for the clarification in Illustrious 2.0, I thought that was the case, but I wanted to make sure.
Looking forward to seeing the future results of your own experiments tho, the results so far look really promising, it makes me realize that Loras Finetune can produce good results and is a good path to try! 馃憤聽
It's high quality, but when it's nsfw it becomes anime style.
Impressive checkpoint. Thanks for your hard work on it. 馃憤
What denoising strength do you use most often? A higher denoising strength gives a more realistic result, but at the expense of a poorer prompt adherence and risks of deformations and anatomical inconsistencies.
Also i noticed some non-Danbooru tags in your prompts. ILXL can deal with natural language but for the non-Danbooru stuff inside of your prompts they didn't looked like natural language attemps ("slim body" for exemple). Are these trained tags or simply a roll of the dice hoping the coin lands on the right side, since they will change the size of your promp weight, and therefore the final result of the image, but without any guarantee that the change is the result of those tags being understood and not just the result of the tokens weight change?
Thanks! I appreciate the technical deep dive.
1. Denoising Strength: For Hires Fix (or img2img upscaling), my 'sweet spot' is usually around 0.45. You are absolutely right that going higher risks breaking anatomy and prompt adherence. At 0.45, I get enough texture enhancement (skin pores, fabric details) to sell the realism, but the model stays strictly within the boundaries of the original composition.
2. Prompts & Natural Language: Regarding tags vs. natural language: It is definitely not a 'roll of the dice'. While the base is indeed trained heavily on Danbooru tags, let's not forget this is the Illustrious/SDXL architecture. It utilizes powerful Text Encoders (OpenCLIP) that have excellent natural language understanding. Therefore, phrases like "slim body" are interpreted semantically by the model, not just as random noise. I use a hybrid approach: Danbooru tags for strict structural elements and natural language for nuances. The model understands both, and they work together to shape the final vector
@llikswonskcalb聽Thanks for the clarification. I m gonna test your v2 tho v1 is already a masterpiece. 鉂わ笍
So far the only weakness of v1 was its poor facial expression knowledge/representation. No matter the Danbooru tag used, the character facial expression wasn't that much impacted during my tests (over 100 images generated). Tho, i couldn't tell if it was because of a lack of training regarding those facial expression tags or if it was the result of the low CFG score.
@llikswonskcalb聽Thank you for your work on this model, I use it as a refiner for hi-res upscaling.
Almost always makes a woman even if I tell it otherwise.
Don't make men, there are special LoRA and other models for this.
@llikswonskcalb聽so it's like a realism model except men?
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