Get Big Love Eryn1, Ultra5, Photo6, Zuna1 or Zia1 for $5.50 and Gwen1 or Hyper1 for $10 on Fanvue. Click 'Follow', buy a post, check your Fanvue DMs! You can get Klein2 for $10 on Tensor Art. A subscription includes the latest release and new ones within 30 days.
To create up to 85 free images per day in highest quality you can use Big Love here. For discussing photorealistic image generation join me on Discord.
Big Love Gwen is a finetune of Qwen Edit 2511 and can do NSFW image editing. It produces more realistic and sharp images with better skin texture & genitals than other Qwen checkpoints/loras. Txt2img is less reliable, but generates nice results too.
Big Love Gwen1 allows commercial usage without additional fees (if no auto-generation involved) unlike Big Love Klein. With its better anatomy it is easier to get good editing results. As fast at 6 steps as Klein at 4 steps.
The fp8 mixed version is for 24+ GB VRAM (highest quality), the nf4 version is for 12 and 16 GB VRAM (25% faster), the GGUF Q5_K_M version is for 16 GB VRAM (softest) and the nvfp4 version requires 24+ GB VRAM (on RTX 5090 2-3x faster, otherwise 2x slower, lower quality than fp8 mixed, less saturation, textured).
It is recommended to use ComfyUI. The Gwen1 workflows offer a skin enhance feature that is not available in Forge Neo. Move the Gwen1 model file into the diffusion_model sub folder of the models folder of ComfyUI, qwen_2.5_vl_7b_fp8_scaled.safetensors into the text_encoder sub folder and qwen_image_vae.safetensors into the vae sub folder.
Settings are 6 steps (3 steps for upscaling), cfg1, Euler sampler, Beta scheduler, 832x1216 or 1024x1536 pixels.
Big Love Eryn is a fine-tune of Ernie-Image(-Turbo). You can run it locally with ComfyUI and Forge Neo. The fp8 version works with 8 & 12 GB VRAM. Use the (pruned) bf16 version if you have 16 GB VRAM or more. The "Full" versions are only meant for training a lora (coming soon!). Put the downloaded model into the diffusion models sub folder of ComfyUI or the StableDiffusion sub folder of Forge Neo. You additionally need to place ministral-3-3b.safetensors in the text_encoder sub folder and flux2-vae.safetensors in the VAE sub folder.
Settings are 4-6 steps (3-4 steps for upscaling), cfg1, Euler sampler, Beta scheduler, 832x1216 or 1024x1536 pixels.
Big Love Hyper supports generating at image sizes of 1664x2232 (4 megapixel) and higher with SDXL. Can be easily upscaled to 9 megapixel unlike the normal low-res images. Hyper currently has not fully stable anatomy, so needs more runs. Some prompts work better than others. It produces highly detailed and life-like images close to real photos. It has a special quality that cannot be achieved by just upscaling. The Hyper versions of Big Love are pay-only and special license conditions apply (see below).
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1, clip skip 2, 1664x2432 or 1536x2240. Upscale with img2img with DMD2 lora with strength 1.0, same prompt, LCM Exponential, 1.25-1.5x, 4-8 steps, cfg 1, 0.3-0.5 denoise, clip skip 2.
Big Love Klein is a fine-tune of Flux 2 klein. It can do txt2img but also edit images with prompts. Txt2img is currently experimental and requires more prompt & seed hunting. Image editing works stable. It only needs 4 steps, so is quite fast (5 sec on 5090, 15 sec on 5070). You can run it locally with ComfyUI and online on Tensor Art. Use the GGUF Version with 8 GB VRAM, the fp8 version with 12-16 GB VRAM and the (pruned) bf16 version with 24+ GB VRAM. The nvfp4 version (full nf4) renders 2-4x faster on RTx 5xxx GPUs with the latest CUDA drivers. The base version (full fp32 or full bf16) is meant for training a lora only. Put the downloaded model into the diffusion models sub folder of ComfyUI. You also need qwen_3_8b_fp8mixed.safetensors in the text_encoders sub folder (Qwen3-8B-Q5_K_M.gguf wth 8 GB VRAM) and flux2-vae.safetensors in the vae sub folder. Forge Neo is not recommended, because it currently produces too low image quality with Klein, which will hopefully change soon.
Settings are 4 steps (2 steps for upscaling), cfg1, Euler sampler, Beta scheduler, 832x1216, 1024x1536, 1280x1920 or 1536x2240 pixels
Big Love ZT, Zia or Zuna are fine-tunes of Z-Image(-Turbo) on the Big Love dataset. You can run it locally with ComfyUI and Forge Neo. The fp8 version works faster with 8 GB VRAM but produces more noise so may sometimes look more realistic, but details are not as good. Use the (pruned) bf16 version if you have 12 GB VRAM or more. The "Full" version is only meant for training a lora. Put the downloaded model into the diffusion models sub folder of ComfyUI or the StableDiffusion sub folder of Forge Neo. To make Big Love ZT/Zia/Zuna work you additionally need to place qwen3_4b.safetensors in the text_encoder sub folder and ae.saftendors in the VAE sub folder.
Settings are 8 steps, cfg1, Euler or DPM++ 2s a RF sampler, Normal or Simple or Beta scheduler, 832x1216, 1024x1536 or 1280x1920 pixels. For upscaling 8 steps, cfg1, Euler sampler, Normal or Simple or Beta scheduler, 1.5x upscale.
Big Love Ultra supports generating at image sizes of 1280x1870, 1360x1984 and higher. Can be easily upscaled to 6 megapixel unlike the normal low-res images. More photorealistic and detailed. A special quality that cannot be achieved by just upscaling. Ultra produces more details & sharpness when upscaling and detailing low-res images. The Ultra versions of Big Love are pay-only and special license conditions apply. See below.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1, clip skip 2, 1280x1864 or 1360x1984. Upscale with img2img with DMD2 lora with strength 1.0, same prompt, LCM Exponential, 1.25-1.5x, 4-8 steps, cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2.
Big Love Photo and Insta1 are finetuned versions of XL. Lust1 is a finetuned version of Lustify merged with Photo. They were trained on thousands of images and dozens of new concepts. Why they are the most realistic and versatile. For more details and prompting Photo1 read this article.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1, clip skip 2, 832x1216 or 1024x1496. Upscale with img2img with DMD2 lora, same prompt, LCM Exponential, 1.25-1.5, 4-8 steps, cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2.
Big Love XL is a combination of 5 different training branches of SDXL: original SDXL, bigASP, NatVis, Anteros and Pony. With a bit of Pony in it, some Pony loras (poses, characters) work too. It outputs a more photorealistic & creative look than the Pony versions and can also do paintings & cartoon.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1-1.5, clip skip 2, 832x1216 or 1024x1496. Upscale with img2img with DMD2 lora, same prompt, LCM Exponential, 1.5-2x, 8-12 steps (XL1/XL2), 4-8 steps (XL2.5-XL4), cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2.
Big Love Pony produces different images than both Pony & SDXL-based models. Pony tags are understood, but interpreted a bit differently. Some images lean more in the one or other direction depending on the prompt. It works with Pony loras as well as normal SDXL ones. It can turn anime/cartoon into photorealistic images in img2img. Pony3 includes a bit of Illustrious.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1-1.5, clip skip 2, 832x1216 or 1024x1496. Upscale with img2img with DMD2 lora, same prompt, LCM Exponential, 1.5-2x, 8-12 steps, cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2.
ComfyUI Workflow:
Download one of the following images and drag'n'drop it onto Comfy:
Klein, Eryn and Gwen workflows are embedded in the showcase images.
Z-Turbo/Z-Base txt2img & Upscale Workflow (recommended)
SDLX DMD2 txt2img & Upscale Workflow (recommended)
SDXL DMD2 txt2ing & Upscale for Big Love Ultra
SDXL DMD2 img2img Workflow
SDXL Lightning Workflow
Trained Concepts
Newer versions of Big Love include the concepts of older versions, e.g. Photo4 can do everything that Photo1 to Photo3 can do and more. The only exception are the Insta concepts, but they have been partially added to never versions too.
Photo6/Ultra5: ai-style, bodyscape, butt plug, candid amateur, cumshot, illustrious-style, outdoor sex, partner fingering, photoart, innie pussy, ray-style, rebellious, reflection, sensual, sexy ass, sweetheart, wedgie
Photo5/Ultra4/Hyper1: alluring, anal sex, artistic photo, artistic pinup, charming, cum portrait, cute asian, cute pinup, cute portrait, double oral, dreamy-style, face pov, fantasy pinup, fantasy-style, kai-style, lowkey, mj-style, outdoor flashing, photo art, pole dance, public indecency, public nudity, rock climbing, scify-style, sword pose, vaginal sex
Photo4/Photo4.5/Ultra2/Ultra3: 2girls kissing, acrobatic sex, average face, beautiful face, amateur pinup, anal fingering, artistic portrait, cuddling, cum swapping, doggystyle pov, even skin color, fashion photo, female masturbation, female pov, finger licking, food porn, footjob, french kiss, full nelson, funny movie, funny tongue out, insta cute, legs pov, low contrast, mirror portrait, nude pose, oral pov, orgasm face, outdoor nude, penis licking, pinup photo, pro photo, pro portrait, pussy licking, sex pov, sexy portrait, vaginal fingering, waterfall
Photo3/Lust1/Ultra1: 360 degree photo, 3d selfie, 69 position, adorable, alt beauty, anal gape, anal sex, average face, beach life, beautiful, beautiful face, candidness, cum, cute, deepthroat, dildo insertion, double exposure, enthusiastic, extreme pose, faces, fashion photo, female pov, fisting, follow me pov, girl next door, gorgeous, handjob, heroin chic, huge feet, huge hands, huge nipples, light rays, light streaks, lighting, low/mid/high contrast, lowkey/midkey/highkey, low/mid/high saturation, middle finger, motion blur, object insertion, detailed eyes, teeth, pro photo, pussy gape, real life, rooftop, round ass, sad, sexy pose, skin texture, skin tone, spread pussy, squirting, street portrait, testicle licking, testicle sucking, vaginal sex, voluminous hair, water splash
Insta1: amateur photo, fashion photo, insta selfie, pinup photo, pro photo, real life, big ass, bimbo, cute, luxurious, adorable, enthusiastic, average face, beautiful face, detailed eyes, sexy legs.
Photo2: 3d selfie, 69 position, adorable, alt beauty , amateur photo, ball licking, ball sucking, beach life, bubble butt, low/mid/high contrast, dildo insertion, double exposure, enthusiastic, extreme pose, female pov, follow me pov, forced perspective, girl next door, gorgeous, handjob, heroin chic, huge feet, huge hands, huge nipples, light rays, light streaks, lighting, middle finger, motion blur, no tan lines, object insertion, pussy gape, rooftop, sad, low/mid/high saturation, sexy pose, squirting, street portrait, water splash.
Photo1: amateur photo, pro photo, lighting, lowkey, midkey, highkey, beautiful, cute, candid, real life, average face, remarkable face, voluminous hair, skin tone, skin texture, 360 degree photo, spread pussy, deepthroat, fisting, anal gape, anal sex, vaginal sex.
Training a (character) lora
My advice is this: Take 10-30 high quality images (at least 50-100 for styles or poses), download OneTrainer, click the SDXL lora preset, choose Big Love as the base checkpoint, add your images as a concept, add tags on the Tools tab, and start training. If you train on Big Love Ultra change the training resolution to 1536 and provide 1248x1832 images.
You will only get the full Big Love quality by training on real photos or extremely photorealistic images, which is usually not the case with a fictional character. It is all about image quality and not choosing boring images. Don't add posing images to a character lora, because Big Love provides the posing later for it. Focus mainly on good portraits with a few upper and full body images. Rather fewer higher quality images than a lot of average images. Read here for traing a lora on Big Love ZT2, ZT3, Zia1, Zuna1 or Eryn1.
Fixing Anatomy
If you want to keep the seed and repair anatomical problems in an image, activate the Extra checkbox in A1111/Forge and set Variation Strength to 0.01 to 0.1. Then generate until anatomy is fine. In Comfy there are sampler nodes that support variation seed (e.g. Inspire Pack), which do the same thing. Also possible to change steps or add commas to the prompt, but I do not recommend it. Extra/Variation Seed is more powerful and convenient as it gives you endless variations with just one click. There is always a variation which looks similar or even better with great anatomy.
You don't need negative prompts for this. They are rather ineffective. You can also change the positive prompt to suppress things. Anatomy problems are also created by the prompt if you prompt contradicting poses that the model cannot combine. Better to fix the prompt first then.
Reducing Saturation, Warm Colors and Sharpness
These SDXL loras reduces the saturation and change the color temperature without reducing image quality. The lora strength defines the effect. Negative values increase saturation or add more warmth. To make an image softer use a lower strength for the DMD2 lora, e.g. 0.95, 0.9, 0.85.
Big Love Hyper/Ultra/Photo Sizes
Big Love Hyper supports these image sizes:
1664x2432 (recommend)
1536x2240
Big Love Ultra supports these image sizes:
1360x1984
1280x1872 (recommend)
Big Love Photo supports these image sizes:
1024x1496 (recommend)
832x1216
You can also use the 16:9 or 2:3 versions of these image sizes as well as landscape orientation, but the above should be more reliable.
The higher the image size, the lower the probability of good results. If you get too many problems with a higher image size, switch to the lower one. Some prompts do higher sizes fine, some do not. Do not use a lower image size than the recommended one, otherwise image quality will be lower. With higher image sizes anatomy problems occur too often.
Remove fill words and unusual tags in the prompt. They can cause a quality reduction with Big Love Ultra/Hyper as they were not trained. Shorter prompts should work better as it is less likely that bad or untrained tags are in it.
SFW Output - No Tits Please
"Is there a trick so that Big Love doesn't always generate raised shirts or visible breasts?" I get this asked so often, while it is so obvious. Big Love knows what men want so it gives it to them. Negatives don't work that well for it. So you got to speak to it in the positive prompt like you were taking to a nun. "Breasts? How dare you speak such an obscene word to me." Don't mention breasts or any of these sexy parts. Instead describe clothes a lot. Don't write down your impure thoughts. God forbid! Yeah, I know, so hard. Describe her body shape, which also implies certain tits underneath the clothes.
XL Prompting Advice
SDXL prompts & prompts from various SDXL checkpoints work with it. Pony prompts too, but they create a more photorealistic look. Natural language prompts tend to create artistic glamour images with less skin detail while normal tags do more photo-style images. Big Love XL gives individual words more attention, so you don't need to rework prompts like Big Love Pony requires sometimes.
XL1/XL2 has a tendancy towards cuteness and bright skin. If you get too much of it, remove words like cute, sweet, pale/fair skin & flash from the prompt. It also creates realistical analog photos with reduced image quality. Sometimes better to remove terms like analog or grain to increase quality. Decrease cfg to get a more natural look.
XL2.5 can sometimes get too sharp. Reduce cfg or use less steps in img2img to make images softer.
Pony Prompting Advice
Pony prompts & prompts from other checkpoints work with it. Score tags and fill words like masterpiece or perfect skin have as good as no effect usually. A negative prompt is often unnecessary unless you want to make something vanish or avoid underage, but it can also change the style of the image.
Pure booru tags and some other samplers may produce Pony style. Photographic terms or a simple prompts ensure a photo look. Sometimes it refuses to produce medium shots, portraits or close-ups unless you weigh the term heavily or remove feet, shoes, high heels, boots etc. from the prompt. wavy hair sometimes does not look so great.
If it refuses to do porn, try simplifying the prompt. If you want to do a portrait, don't describe surroundings too much. If you want to do porn, describe the action mainly and don't focus on the people or surroundings in the prompt. The largest part of the prompt should be about the main subject of the image.
If a prompt does not produce the intended image, you often only need to modify it a bit to make it work perfectly.
Using Character Loras
Big Love Pony supports Pony characters, but they look like real humans. There were some complaints about them not working, but the problem was not the model itself so far. So here are some tips:
* Try Pony as well as SDXL character loras
* Use a lora weight up to 1.5 if it does not reduce quality
* If it is a well known character, add the name in the prompt and also give it a higher weight if necessary.
* Check your negative prompt for problems. Delete it if necessary and rewrite it from scratch.
* Render a lot of images to be able to pick those with the best resemblance.
More SDXL Photorealism:
You can highly improve the images generated with this model by using img2img, upscaling, detailing etc. The SDXL Lightning lora enhances the look and constrast despite only 8 steps. Alternatively, the SDXL DMD2 lora produces a sharp, but more natural look with less contrast. Also check out the Subtle Style loras, which nicely enhance images.
Big Love License
Big Love SDXL versions are licensed under CreativeML Open RAIL++M (dated July 26, 2023), the Big Love Z-Image and Ernie versions are licensed under Apache 2.0, and the Big Love Klein versions are licensed under the FLUX Non-Commercial License (Black Forest Labs Inc.), with the following additional terms:
For clarity, the following version tiers are defined:
Restricted versions: Ultra, Hyper, Klein, Zia, Zuna, Eryn, Gwen
Open versions: Pony, XL, Photo, Insta, Lust, ZT
1. You may use Big Love without crediting the creator.
2. You may sell the images that it generates.
3. You may only run the official Big Love versions of the SubtleShader account on Civitai and Tensor Art. Running it on other public or shared servers commercially (including other Civitai and Tensor Art accounts) requires a separate license or permission from the creator.
4. You may not sell this model or merges of this model.
5. You may not merge, share merges of, or share LoRA extractions incorporating Restricted versions. You may merge and share merges of Open versions.
6. When sharing the allowed merges of Open versions, as well as finetunes of them, you must apply these same additional license terms.
7. Redistribution of Restricted versions is prohibited. They may only be obtained from official sources designated by the creator.
8. All use-based restrictions of the CreativeML Open RAIL++M license apply to SDXL versions and their derivatives. All use-based restrictions of the FLUX Non-Commercial License apply to Klein versions and their derivatives.
9. Any restrictions in these additional terms may be waived only with explicit written permission from the creator.
TLDR: This is basically the same license as before (just stated more clearly), so nothing changes for the Pony, XL, Photo, Insta, Lust and ZT versions of Big Love. However, restrictions were added for Ultra, Hyper, Klein, Zia, Zuna, Eryn and Gwen versions (no merging, no redistribution). The "Share merges" condition below the license on the right hand side was only deactivated because of the restricted versions. Merging is still allowed for the open versions.
Many thanks to the creators of SDXL, Z, Flux klein, Pony, bigAsp and Lustify for making their wonderful models available. Big thanks to RaymondLuxuryYacht for allowing me to train on his fabulous images.
Description
Please note: The Klein versions of Big Love are pay-only and special license conditions apply. See description!
Big Love Klein2 is better at NSFW image editing. Less tries needed. Anatomy improved, even in txt2img (but still far from perfect). Klein2 is more photorealistic & the harsh bright lighting was fixed. Various NSFW editing concepts that keep character consistency were trained.
Download the GGUF version (Pruned nf4) with 8 GB VRAM, fp8 with 12-16 GB VRAM and bf16 with 24+ GB VRAM. nvfp4 version (Full nf4) for 2-4x faster rendering with Nvdia 5xxx gpus. Base version (Full bf16) for training loras. You also need qwen_3_8b_fp8mixed.safetensors in the text_encoders sub folder (Qwen3-8B-Q5_K_M.gguf wth 8 GB VRAM) and flux2-vae.safetensors in the vae sub folder.
Use ComfyUI with the workflows from the showcase images. Forge Neo produces too low quality.
FAQ
Comments (83)
Absolutely fantastic v2 of Big Love Klein. Does many more NSFW things easier, with better accuracy.
Any advice on how to prompt breast size without having the checkpoint make the breasts bare? I often will want to enhance the bust of the subject, while keeping the clothing intact.
Either describe clothes at the same time or express it more indirectly like curvy or heavy chest.
@SubtleShader Yeah, I swapped out one of my prompt templates for a different one and got around the nipple issue, Thanks for the great work as always.
you have sold me with some of those Img editing showcase images for Klein2 so I will be grabbing that from your Kofi account. however I noticed there are 2 load image nodes do I use both or just one ?
If you want to use a second image (actually up to 8 images are possible), you have to activate the switch. Then refer to image 1 and image 2 in the prompt and tell it what to do with each image. See the Klein1 showcase for examples.
@SubtleShader How would one add additional Images since you mentioned up to 8?
@user081525 Needs replicating some nodes in the Sampling box of my workflow. But would slow down the rendering if you only use only 1 or 2 images. Maybe someone posted such a workflow. Try googling or ask an AI.
why most of these checkpoints are overwhelmed with female photos? is it not capable of creating male figures?
They can do male. Just no fun for me to do male images. Sorry.
I love when people arrives and on a "free!" checkpoint start to argue.... :D say thanks and go on. Wants male? Train it.
@lendasta Actually they just need to prompt it themselves. Not even train it.
@lendasta "free" uhm where?
@lendasta oh by free you mean 20 dollars. gotcha. i must be living in some weird country where free means something else.
You have to prpmpt the male characters first and put plus 3-4 weight on them
If you want full on dudes..... try a different checkpoint
Oh i love this very good model, you should try if you did not yet.
i keep getting the same girl's face on almost every gen... why
Probably too generic prompt. Or a lora is used without you noticing. A lot of people wished they had this problem, by the way.
@SubtleShader lol its not the most attractive girl...
@NUGGZ1616 I hear about this problem again and again, but never experienced it myself in 3 years. Sorry, I'm clueless if it is not the prompt.
Klein's girls all look exactly the same. In fact,
@SubtleShader subtle you're a god. thank you for always responding to idiotic comments with class.
@JetterJack Always trying to help if people ask nicely.
Well, got also sold on Klein2 for the image editing and got it via Ko-fi subscription. Great work. Got it to run in the Mac Comfy App. My Mac is not that slow but an Klein2 edit will take some minutes. Any chance to get a quicker preview by altering something in the workflow?
In the ImageScaleToTotalPixels node(s) set the megapixels value lower for faster results. But it will look a bit different than the higher resolution end result.
BIG Love Klein 2. is the best realistic model after Chroma. ! this thing is too powerful
Still all of them pretty much suck at NSFW. SDXL seems to be the best for it. I can get and even better NSFW results with big love sdxl or lustify, not to mention sdxl is performance friendly and easier on my card.
@chrisss1 SDXL: Best at skin texture & genitals. Z: Best at anatomy & composition. Klein: Best at image editing. They complement each other.
@SubtleShader one day we won't need 5 different models and one will do it all perfectly, one day
@kekekekekekAI I hope so, but I don't think so.
CHroma is like very good at NSFW the only problem is you cant just type it. it works best image to image
Is there fp32 version for ZT3?
Also seems like for Zia both 16 and 32 have same file size, at least that's what site shows.
Yep, there is no fp32. Just using Civitai's limited naming scheme for more distinctice names. If you want to train on ZT3, read here.
bro please... so many of us are poor. please don't ever forget about us stuck on SDXL.... your work is so appreciated
Yep, I'm still a SDXL fan too. There will be a new Photo6 release next month.
@SubtleShader cool thanks. also, do you have any plans to make any new loras?
@JetterJack Not really. I'm building everything directly into the checkpoints.
Flux.2 Klein 9B Is there a GGUF 8Q version available instead of the Pruned Model nf4 (6.04 GB)?
That is GGUF. It even says GGUF there. Look closer. Civitai just does not allow me to name it correctly.
@SubtleShader My point is that I am aware it is in GGUF format. However, since NF4 is an extremely aggressive 4-bit quantization with significant loss, as I mentioned, I am specifically requesting “8Q” instead of NF4...... 8Q is that it significantly reduces VRAM usage while maintaining very low loss.
@sarnara2 Civitai only lets me name it "nf4". Totally silly. Ignore that it says nf4!
Sorry, I only offer Q5_K_M. It is not that much different from Q8. If you can run Q8 you should also be able to to run fp8.
Please have mercy with me! I don't want to upload several additional GGUF checkpoints.
Should one train LoRA on the BF16?
The full bf16 or full fp32 download is always the training version for Z and klein.
Any advise on using the full version with ai-toolkit? It only supports diffusers format, not safetensors files
@xcession Please always mention if you mean Z or klein. Saves me writing about all possible cases. For Z you need Diffusers format, for Klein a safetensors file works with AI-Toolkit.
So how is Flux.2 Klein 9b censored vs something like z-image-turbo? Do fine tunes and LoRAs make it more unrestricted?
The original versions of both were not trained on NSFW images (or few only). So they just lack the knowledge. Of course, training NSFW concepts makes them reproduce them. The Big Love versions of Z and Klein are just as uncensored as the SDXL versions (check out the showcase images & galleries here). Just that SDXL has a lot more NSFW training after 2.75 years than Klein and Z, which are much younger.
@SubtleShader So I've been learning to produce renders with z-image-turbo and base and getting used to LoRAs for them. Every so often I get weird results though. Now, I want to see how Flux.2 Klein 9B fine tunes perform. I hear from Gemini and Chatgpt that generally 9B is better at creating humans. I guess we'll see. Looking forward to when your 9B fine tune becomes available.
@olternaut Actually Z has the best anatomy and composition. SDXL the best skin texture and genitals. Klein is great at editing.
@SubtleShader Still going to test your 9B BigLove when it comes out. What do you mean better at editing? Do you mean prompting that it uses more natural language? I wish there was a super model that combines the best of everything.
@olternaut Big Love Klein is pay-only. Maybe I will make Klein1 free in a few months or so. Have to see. With editing I mean that you give it one or more images and a prompt that tells it how to change the image or how to combine them. See the images with text overlays in the Klein galleries above.
Not liking the initial results with 9B. Not your fault. I think it's the model itself. So I'm going to let the community work on that for a few months. I love your BigLove z-image-turbo models 1,2 and 3 though. But don't forget to give z-image-base some love too. Thanks.
@olternaut A Z Base version of Big Love will come next. It will look more like Z Turbo though 😆
Info
The Create option for Klein2 only lets you generate images with the the original Flux 2 klein and not Big Love Klein2. Previously it did not work at all. Sorry, I have no influence on this. Complain to Civitai or use TensorArt/TensorHub.
Hi,
Thank you for sharing.
Which model should be used to train character LoRa for BigLove (Klein)?
Full Model bf16 (16.91 GB)
OK. do you think LoRas trained with Flux.2 Klein base will also work with BigLove models?
@bien622 Yep, should work. Klein seems to be more robust in this regard than Z.
I confirm that character LoRas trained with Flux.2 Klein base 9b work fine with BigLove Klein2. Could you point out why am i getting blurry, distorted, deformed images while using the your example workflows with BigLove bf16 version? When using the purned version the images are good even at 4 steps (no LoRa,, doesnt metter if i use qwen_3_8b_fp4mixed.safetensors or qwen_3_8b.safetensors text encoder),
@bien622 Thanks for confirming. Sounds like you use the base version (Full bf16). It is meant for training and requires 20-30 steps and cfg 5 to produce normal images, which are still softer.
@bien622 hi, I'm going to train a flux klein lora to test on big love also. Can you share which toolkit you used to train(I often use ostris AI Toolkit) and the parameters that worked for you?
@elenazuclair I'm training Z and klein with AI-Toolkit and SDXL with OneTrainer. I do 35-60 epochs for finetuning and 70-100 epochs for loras. I use AdamW 8bit or Adafactor. I explained how to calculate steps & learning rate in this comment. Applies to klein too.
Hi, where to download Zia1?
Look below the showcase images
Big Love Klein Poll
You have the chance to win 1 of 5 copies of the future Big Love Klein3 by participating in a poll about what image editing features you would like to see trained on Big Love Klein.
Enter your Civitai user name at the bottom under "Name" to participate in the drawing. The poll will run for 1 month.
Vote here:
https://strawpoll.com/wAg3Qbqp1y8
i don't understand the concept. You put an image and it's worst than the photo before and nothing change... So the prompt is useless... Tested photo 4
Sorry, I'm not sure what you mean. I have to guess because various people had the same misconception. You tried Photo4 in img2img and expected it to edit the image? Photo4 or SDXL cannot do image editing. Img2img only "paints" over existing pixels which is nice for upscaling, improving skin or turning anime into photorealism. For image editing you need to use Qwen or Klein.
@SubtleShader oj ok sorry then
@Djbone No problem. Asking & learning is the way to go!
Using Klein2 model and workflow from one of the sample images I am getting mangled results. Any idea what I could be missing?
I probably added the wrong seed. The next seed higher might be the right one. In general, anatomy is not perfect yet. Still more training needed for NSFW. Just try more seeds. If that does not work, try modifying the prompt.
I’m really impressed with your new Zia1 model! I purchased it via Tensorhub and have been testing it quite a bit.
The flexibility in terms of lighting and posing is excellent. Also, all of my LoRAs that were trained for ZT3 work perfectly with it, which is a huge plus.
A small tip for others: I’m using DPM-2 as the sampler and Simple as the scheduler, and I’m getting very nice results — high contrast, realistic images, and the skin no longer looks rubbery.
Keep up the great work!
Thanks for the review! Appreciated.
Hi ! Yeah, Zia1 is great and produces really cute girls out of the box... Speaking of cute girls, love your "Bavarian" ones ! ;-)
@BretChampagne Hi! Thanks a lot for the kind words – really appreciate it 😊
I’ve been meaning to release an update for quite a while. After the PONY version, I originally planned to move to a Big Love SDXL-version, but I was never fully satisfied with the results – especially in terms of flexibility, which just didn’t meet my expectations.
I’ll take this as motivation to dive back in and work on a Zia1/ZT3-based version next. Let’s see where that goes!
Heya, I bought the Klein checkpoint and I tried it with your workflows. For the T2I workflows I keep getting errors because of supposedly some wrong configuration in the KSampler (inspire) node -
variation_strength, increment, could not convert string to float: 'increment'
variation_method: '0' not in ['linear', 'slerp']
internal_seed, linear, invalid literal for int() with base 10: 'linear'
And I could guess, but it would be best if you could let me know what are the actual correct values since you got amazing results according to what you shared!
As for the I2I flows... Image editing... I'm getting photos in terrible quality! It is very hard to believe the images you shared were really created from the workflows embedded into them! There doesn't seem to even be any upscaling in those workflows... could you please share the actual workflows used to make those very impressive image edit results? I bought this checkpoint for the sole purpose of getting better results with I2I editing while keeping facial and body details, but currently it is completely unusable with the quality that I am getting...
Thank you!
Please download one of the Pruned versions not Full. You downloaded the base version of Klein2 that is meant for training (and requires 25 steps with cfg 5). Of course, it looks terrible when used with only 4 steps and cfg1.
You probably use an older version of the Inspire Pack. Please update it to fix the problem.
The embedded workflows are what I used. In two cases I used txt2img and then a image editing workflow. As an image cannot have 2 workflows, the txt2img one is embedded. Of course, the editing workflows require certain images to replicate the results which I don't provide. But they are meant as examples and Inspiration, not for reproduction.
@SubtleShader Hey, thanks for your fast response!
I double checked and I did try both the PRUNED bf16 and fp8 variants - both gave me poor results somehow...
As for the Inspire Pack, I just tried again after updating it and making sure it is up to date but the values in the fields itself are still mismatching and I'm getting the same errors even with the most recent version...
@talafek96 Right click on the node and choose "Fix Node" or "Recreate Node". You can also replace it with a normal sampler and recreate the connections & settings. I used the Inspire sampler because it offers variation seed for easily fixing problems.
What do you mean with poor results? Can you upload an image somewhere for me to see?
@SubtleShader I can send you privately?
@talafek96 So the main point of our conversation was: Only use high quality input images as the model will replicate the low quality in the output. If you do not have better images, try to improve them with SVR2, img2img or other methods.
WOW! Why didn't I try this sooner? Klein2 is absolutely fantastic! Great details and composition, fantastic pussies! Cum looks good, but placement is erratic. And I see what you're talking about the instability of text-to-image. Well, still fantastic and can't wait for the future updates!
Big Love Zuna1 Lora Training
If you want to use your lora with Big Love Zuna1, don't train on Z-Base or another Z-Base checkpoint. Train on Big Love Zuna1. Z is not as flexible as SDXL in this regard.
OneTrainer Instructions
Download the Full Model bf16 version above to train a lora with One-Trainer. Choose the z-Image LoRA preset in OneTrainer. On the model tab click the ... button next to Override Transformer / GGUF and choose the downloaded safetensors file. Add your concept and click Start Training.
Please note: OneTrainer has 512 resolution set on the training tab. If you have 24 GB VRAM, you may want to set resolution to 1024. If you want to train 1024 resolution with 16 GB VRAM, use the z-Image LoRA 8 GB preset and set resolution to 1024. In both cases it will take longer to train.
AI-Toolkit Instructions
Contact me for the Zuna1 de-turbo diffusers zip file. Unzip it. Choose the Z-Image option in AI-Toolkit. Then in the "Name or Path" text box replace Tongyi/Z-Image with the file path to the unzipped folder.
General formula for steps:
Image count 100 epochs / batch size
So, 25 images 100 epochs / batch size 2 = 1250 steps. Save every 10 epochs (every 125 steps here) and compare the last few saved versions.
With a batch size above 1 calculate a new learning rate as
lr = base_lr sqrt(batch size)
For example: 0.0001 sqrt(batch size 2) = 0.00014
















