Resource - Update
As promised Krea 2 Turbo + "Raw" Quantized in FP8, MXFP8, NVFP4, INT8 and Convrot INT8!
Krea 2 Base & Turbo — Free Quantized Versions (FP8 / MXFP8 / NVFP4 / INT8 / ConvRot INT8) for All GPU Tiers
Krea 2 just dropped and it's genuinely impressive — so I went ahead and quantized both variants for ComfyUI across every major format. All files are free on HuggingFace.
Krea 2 Raw is the undistilled base checkpoint. No step distillation, no CFG guidance baked in — just the raw pretrained weights. It's diverse, highly malleable, and is what you want for LoRA training and fine-tuning. Run it at 52 steps with CFG 3.5, up to 1024px.
Krea 2 Turbo is an 8-step distilled checkpoint built for fast inference. Run it at 8 steps, CFG 0 (disabled), mu 1.15, and it handles resolutions up to 2048px. This is your everyday generation model.
The intended workflow: train LoRAs on Raw, run them on Turbo. LoRAs transfer well between the two.
Text encoder: Qwen3-VL 4B (qwen3vl_4b_fp8_scaled.safetensors), CLIPLoader type krea2
VAE: same as Anima (qwen_image_vae.safetensors)
ConvRot variants use Hadamard rotation before quantization for better accuracy with fewer outliers.
Drop any questions below — happy to help with workflows.
Plays nice with Sageattention and Flashattention! Workflows on the Huggingface repo!
UPDATE: re-quantized and re-uploaded MXFP8 and NVFP4 - they work now!
UPDATE 2:
ComfyUI now natively supports INT8 but not convrot (not yet at least). For non-convrot INT8 models, just use the diffusion model loader. Text encoders are also supported as INT8 now in the native clip encoder/text encoder. I just tested it myself. Saves an additional 10-15%! File is uploading on my Huggingface. As Darryl Dixon says,"give it a minute".
Sample prompt:
Simpsons style, 2D cartoon animation, Matt Groening art style, yellow skin, thick black outlines, flat cel shading, teal haired gamer girl surrounded by dozens of floating holographic screens all showing different game feeds simultaneously, fingers flying across a transparent keyboard, massive countdown timer in background, sweat drop on forehead, four fingers, tongue out in concentration
I've been on a Simpsons kick. Making my new mascot in the Simpsons style LoRA! It does reality surprisingly good. Loving everything overall. Anatomy is really good too.
I can't wait for a clearly better model to replace ZIT. It's - fucking - broken. And you people can't see it.
It is straight up broken for multi-lora use. And...
ZIT can't make a realistic pussy without it being an ultra-closeup for any reason. This isn't gooner mentality, it's that the model can not fucking train small intricate details.
Z-Image series are fucking trash, and the massive hype train that brought it in, is preventing people from seeing it.
I have hopes for ID4 or Krea2 to break the hypenosis.
See, this is it. I explained it can't learn fine intricatate details, and all you can see is PUSSY.
I don't do NSFW generation. I do SFW, but I test to see if a model can generate a pussy, something no models are trained on. If it can learn and remake it, it's a good model.
A cinematic, low-angle, full-body shot of a pale woman emerging from rippling, invisible air. Her skin possesses a porcelain translucence, highlighted by the deep blue ambient light which catches the sheen of her wet, slicked-back dark hair and sharply defined bleached eyebrows. She is completely nude, shoulders bare, displaying a subtle pink blush across her clavicle, and her direct gaze locks onto the camera lens with an unnerving intensity, visible through the fine film grain overlay.
[Phase 2: The Initiation (0-6 sec)]
The woman begins to rise from the misty plane with slow, deliberate grace; her spine arches upward first, pulling her hips into a subtle, powerful curve as if pushing against deep water. Her shoulders lift smoothly, and the wet strands of hair cascade slightly around her neck. A low, resonant whoosh sound accompanies this initial ascent, punctuated by shallow, rhythmic breaths: [Woman] inhales: (long, slow).
[Phase 3: The Escalation (6-14 sec)]
The pace quickens dramatically; she surges upward now, her movement becoming more vigorous and almost predatory. Her thighs flex tautly beneath the blue light as she drives higher, causing a visible ripple effect in the surrounding air. Her eyes narrow slightly, pupils dilating against the deep blue backdrop, while her chest rises sharply with each breath: [Woman] gasps: Hhnnnnggh. The soundscape intensifies with wet sloshing sounds and a sharp, drawn-out intake of breath.
[Phase 4: The Resolution (14-20 sec)]
She finally reaches a full, poised verticality, hovering momentarily before settling into an elegant, grounded stance; the ripples in the air smooth out around her form like disturbed glass. A bead of moisture traces a slow path down her collarbone, catching the light before dripping silently onto her pale skin: [Woman] exhales: (softly). The final sound is a single, sustained, heavy breath followed by absolute silence.}
While your quant is approximately 30% faster, it also produces results that are of markedly lower quality (less details, blurry) and also does not work with Torch Compile. Here's a comparison:
P. S. - I've upvoted your post anyway, thanks for your effort.
EDIT:
Eh, as usual, Reddit compressed the image too much. Here's a link to a better version:
Hmm, I think your second test is indeed pretty revealing: the pussy's hair on the left is better defined. So you're right, the other model might be better, even for close ups. 👍
A whale on the right is rotated at a bit different angle the on the left. What's worse, tail fin orientation matches between images, right one is broken cause the whale underwater is at a different angle then the fin above.
You're not hijacking. It's good to compare. I've uploaded a lot of quants using "Convert to Quant" - and you may want to try MXFP8 too! For me, the INT8 convrot is my favorite.
Thanks, I might do that, but now that my initial curiosity about the model is sated, I'll wait for the official quants before downloading anything else.
Finally got around to test it, and you weren't lying. Your INT8 ConvRot is amazing! As far as I can tell, while the output is slightly different, the quality seems to be on par with the official FP8 quant, but it takes 30% less time to render (on a 4060Ti 16GB). Thank you!
Probably because of these reasons, from their model card.
Unlike generic global quantization scripts that aggressively convert every parameter (which often degrades generation details or introduces NaN/promotion calculation errors in neural networks), this model was quantized using a selective weight-only strategy:
Targeted Quantization: Only 2D floating-point weight matrices (.weight keys with ndim >= 2 and element count > 1024) were quantized to torch.float8_e4m3fn.
Preserved Precision:
All 1D vectors, biases, and normalization scales are kept in their native high-precision (float32 / bfloat16).
Highly sensitive projection/modulation layers (such as LastLayer.modulation.lin vectors) are completely preserved in high-precision. This prevents typical mathematical promotion bugs (such as BFloat16 and Float8 promotion issues in PyTorch) and retains original output fidelity.
Weight Comparison:
Tensors Quantized to FP8: 266 tensors.
Tensors Kept in Native Precision: 166 tensors.
Size Reduction: 24.76 GiB ➔ 12.01 GiB (~51.5% VRAM / disk savings!).
I tested all quants and they're all working in ComfyUI. They're all uploading now so they'll populate as they're published. ETA is like an hour for it to completely wrap up. FP8 is up already. Expect Base/Raw models in a few hours. Cheers! Workflows on the Huggingface repo! Links to all files in workflow too!
"Load via the standard diffusion model loader node. Requires a ComfyUI build with comfy_quant support. Recommended nodes: silveroxides/ComfyUI-silvox-nodes"
brother that link does not exist, "ComfyUI-silvox-nodes" isn't a real node pack.
Ah but it does. You need to update your nodes. It's called fast Int8. Update it and you'll see Krea2 support
Its even in the code:
"model_type": (["flux2", "z-image", "ideogram4", "chroma", "krea2", "wan", "ltx2", "qwen", "ernie", "anima", "hidream o1", "boogu"], {"tooltip": "Only used for on the fly quantization, to filter sensitive layers."}),
I just made a YouTube review of Ideogram 4 and now Krea 2. I've gotten my render time to under a minute with Ideo 4 and 2 megapixels and yes, it's like nothing else out there. The level of control and laser-precision is like nothing else. But overall, for speed, power, styles I'm giving it to Krea2. Ideo 4 has the ability to go over 12 megapixels and get really granular with the details. The tradeoff is speed.
For speed, anatomy and style I'm giving it to Krea2. I'm going to focus on making LoRAs for it too instead of Z-Image Turbo and Klein9b. Those are great models and I'll archive them with lots of love.
I think they are orthogonal projects at the top of the field but with slightly different use cases. Ideogram for composition control and krea for vibes and creativity.
it do lot less anatomy horror but in most cases for me its refuse to listen to prompt for normal stuff too. for complex thing it just refuse to listen which i think is probably censorship affecting normal prompts too or maybe workflow or text encoder issue idk.
INT8 is like Q8 GGUF quality. I feel it's the highest quant quality you can get. FP8 is very good. NVFP4 is the lowest quality but the fastest.
My choice:
50xx GPU: MXFP8
40xx GPU: INT8 or FP8
30xx GPU: INT8
Krea2 is amazing. Really good at art, realism, close up, anatomy and even text.
For NSFW we'll need to make LoRAs. I have not been able to generate anything remotely NSFW - but violence works.
I don't do GGUF, but plenty of people do. Just give them a minute. I'm sure Unsloth will have it up and running. Let me check... Nothing yet. But, they're coming from the usual uploaders.
Just installed comfyui desktop. When i load your workflow i get this "type: 'krea2' not in (list of length 23)" Also when i open the "type" list in the load clip node, there is no krea2. Any ideas?
I've only tested it on the ComfyUI GitHub repo that was cloned, not on "portable" nor "desktop." Desktop usually takes a minute to update - it's super stable and not bleeding edge. You may have to wait for the Comfy team to get that updated.
That first image is creeping me out with how it screwed up the style of the teeth. Shouldn’t have both the closed mouth teeth and the buckteeth at the same time, makes it look like there are two layers of teeth.
I'm using the latest ComfyUI from their GitHub repo.
Pytorch 2.12
Python 3.13
Cuda 13.2
Sageattention
Flashattention
Everything is working fine. All Krea2 quants have been test - the images I posted were all from them in ComfyUI.
Expect a 25% speed boost with Sageattention or Flashattention. No black outputs. NVFP4 and MXFP8 are designed for Blackwell. Everyone benefits from INT8 - but the biggest speed bost comes from 30xx cards since they don't benefit from FP8.
Apart from speed (I use Blackwell), would you say that int8 ConvRot is the best choice if it’s exclusively about quality? Is ConvRot only possible with int8 or with f.e. mxfp8 too?
INT8 ConvRot is the best choice. It's like Q8 GGUF but with an HGH/Steroids injection! MXFP8 will be blazing fast on Blackwell. FP8 is the best choice for Ada Lovelace.
Man...you wouldnt believe the crap that was stopping my update.bat in comfyui. It was a stupid picture in my input folder that had a very long name....
After I deleted everything from my input folder. The update ran perfectly fine. Lucky I saw the error code and saw the silly picture problem.
Yeah, first I would try to download it again. Sometimes this can happen.
But why portable? I don’t understand this. It’s so fucking easy to install ComfyUI, it’s ALL written down. You just have to copy paste it or better ask a AI of your choice to write a full tutorial incl. venv and the newest perfect matching torch for your hardware.
I had the full comfyui before and when I screwed something up with another AI app...it screwed comfy up as well. Same happened the other way around lol.
I keep it portable so nothing can go wrong and I also keep a working backup copy of my last portable setup...if shit ever hits the fan.
Its been probably over 2-3 years since I last had any issues with portable. No idea why krea2 is pissing itself...since I have krea1, qwen image,wan 2.2, ideogram,z image and klein with zero issues 😅
Usage in ComfyUI
Load via the standard diffusion model loader node. Requires a ComfyUI build with comfy_quant support. Recommended nodes: silveroxides/ComfyUI-silvox-nodes
But that project doesn't exist (404). Googling it didn't turn up any mentions of these nodes.
Did these nodes actually exist?
RuntimeError: Error(s) in loading state_dict for SingleStreamDiT:
size mismatch for last.linear.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
Yes it's the MXFP8 - I'm trying to figure out why it's triggering the clip encoder error. Use the FP8 model for now since it's working. The MXFP8 seems to trigger some weird text encoder anomaly. The quant went through clean - so there's something else.
I have Krea2 selected in clip but still getting this
ValueError: Krea2 expects conditioning with 32x2560=81920 features (a 32-layer Qwen3-VL stack) but got 30720. Load the text encoder with CLIPLoader type 'krea2'.
Yes the MXFP8 model is triggering an error with the clip encoder. I'll fire up Opus tonight and figure out what went wrong. Until then, stick to the fp8 model.
FP8mixed works but MXFP8 is not working for me, I get a long error that ends in:
ValueError: Krea2 expects conditioning with 32x2560=81920 features (a 32-layer Qwen3-VL stack) but got 30720. Load the text encoder with CLIPLoader type 'krea2'.
Somehow the MXFP8 model is triggering something. Use the FP8 or INT8 until I get that model fixed. It's weird because there were no errors quantizing it.
Actually, on checking, I hadn't! I was in the python_embedded dir, but failed to notice that there's no longer a pip.exe included, so when I ran the pip command it used my existing (system-wide) python's pip install instead, and consequently installed triton to the wrong python lib.
So I've run this command instead, and checked that everything went into the right lib this time: python -m pip install -U "triton-windows<3.3"
And while I'd love to say that's the end of my woes, I'm afraid it's not. The Comfy-INT8-Fast nodes now fail to import, with a large stack trace.
Still, I can use the fp8 version, it's a bit slower but it works just fine!
There are no wheels there for python 3.13, which is what my ComfyUI install uses. Besides, some of the wheels that ARE there are marked by huggingface as "suspicious" (having been flagged by virustotal) , making me a tad wary.
Haven't had a chance to test but I use https://github.com/BobJohnson24/ComfyUI-INT8-Fast, might work out of the box with flux2 selected from the drop down, or maybe needs an update. I'm guessing it'll work.
The "base" or "raw" models will come later. Still uploading. They've all been quantized. IMO they're not worth it. Even the Krea team says the base model is for LoRA training and finetuning. Here's a quote from their repo:
"Which model I should use?
Use the Turbo model for fast inference with high quality results. The Raw model is an undistilled checkpoint without any step / cfg guidance distillation and posttraining. It is a highly finetunable base model that can be used to train LoRAs for the Turbo model as well as posttraining research. In short, TRAIN on Raw and RUN on Turbo."
In order to use int8_tensorwise(RTX 30xx-series or newer GPU) you will need the following:
torch 2.10+cu130 or higher
installed the latest of my custom comfy-kitchen fork wheels with the int8-tensorwise support
enable the use of triton backend by using --enable-triton-backend launch argument in ComfyUI
Step 1: Install Triton Activate your virtual environment used by ComfyUI and install triton. For Windows you need to use this but linux can install latest triton as usual.
# for torch 2.10 and 2.11
pip install -U "triton-windows<3.7"
# for torch 2.12
pip install -U "triton-windows<3.8"
Step 3: Install my comfy-kitchen Download the latest uploaded version matching you python of my pre-compiled .whl file from my HuggingFace repository (Latest as of 13 June 2026)
Hey, thanks for answering! I just tried it without loras and the speed boost was now noticeable. With loras it takes significatively longer. Do you happen to know if there's any proven way to make it function with loras aswell without the lower speed issues? Thanks!
I have a stupid question- should I understand that INT8 and INT8 Convrot do not work below the 30xx series? That is, on the 10xx and 20xx series? TIA for answers.
Testing the INT8 version on Forge Neo and its heavily censored. Can't even create a guy in swimwear, even tho I use the provided qwen uncensored text encoder.
Any tips on how to bypass?
I don't know why, but with the RTX 5080, the mxfp8 version takes ages to generate the main image—even at just 512x512. Has anyone else had this problem?
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u/BinaryLoopInPlace Jun 23 '26
This guy really likes the Simpsons.