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CyberRealistic Krea 2
CyberRealistic Krea 2 is a full finetune of Krea 2 Turbo, Krea.ai's 12.9B diffusion transformer with a Qwen3-VL-4B text encoder and the Qwen Image VAE.
Base Krea 2 is aesthetic first. It explores medium, texture and mood instead of settling on one look. Great for creative work, less useful when you want a photograph.
This finetune moves the default toward photography. Natural skin, believable faces, available light, real materials and camera language, with less of the editorial gloss the base model drifts into.
The creative side didn't go anywhere. The official style LoRAs still work, style reference still works, and the model will leave photography behind when you ask it to. What changed is where it starts.
Base Krea 2 likes to interpret. CyberRealistic Krea 2 leans toward the camera.
What changed
Photographic by default, no stack of realism keywords needed first
Less aesthetic drift on short or simple prompts
More natural skin texture, less plastic rendering
Better consistency in faces and hands
Stronger response to camera, lens, lighting and material descriptions
More predictable when you're trying to lock in a specific look
Still moves into illustration, print or anime when you prompt for it
Works with the official Krea 2 style LoRAs in my testing
Seed variation is still there. I didn't try to remove it, since that's part of what makes Krea 2 interesting. CyberRealistic just makes it easier to stay inside one visual language.
Which version should I download?
CyberRealistic Krea 2 ships in five precision and quantization formats. All five contain the same finetune. What changes is file size, memory use, hardware requirements and, to a smaller extent, the image itself.
If you're not sure: FP8.
BF16 · reference version
The original full-precision release and the version the other four are built from. Highest numerical precision and no quantization loss, but the largest files and the highest memory requirement.
Best for:
Maximum quality
Merging, converting or further training
Systems with plenty of VRAM and RAM
Anyone who wants the master version
For normal image generation you don't need BF16.
FP8 · recommended for most users
FP8 roughly halves the size and memory footprint compared to BF16 while staying very close to it visually. It's the best all-round balance of quality, compatibility, memory use and speed.
Best for:
Most ComfyUI users
GPUs with limited VRAM
Everyday generation
BF16-like results without BF16 requirements
Start here if you don't want to think about it.
INT8 ConvRot · efficient INT8
INT8 quantization combined with ConvRot, a rotation applied before quantizing that flattens outliers and keeps more quality than a plain INT8 conversion. It needs far less memory than BF16 and runs well on hardware that likes INT8. Current ComfyUI builds support it natively on NVIDIA Turing and newer.
Best for:
Low VRAM systems
GPUs with strong INT8 performance
A smaller model without giving up much quality
INT8 isn't automatically faster than FP8. That depends on your GPU and backend, so FP8 stays the safer general-purpose pick.
MXFP8 · Blackwell-optimized FP8
MXFP8 is microscaling FP8. Instead of one large shared scaling range it scales small blocks of values, so the FP8 data keeps more accuracy. The real payoff comes from hardware with native MXFP8 acceleration, mainly NVIDIA Blackwell.
Best for:
RTX 50-series / Blackwell
Setups with native MXFP8 support
Anyone who wants an efficient modern FP8 format
On older cards MXFP8 gets emulated, so expect little or no gain over normal FP8.
NVFP4 · smallest and most aggressive
NVIDIA's 4-bit floating point format for Blackwell. By far the most compact of the five and the lowest memory footprint. It's also the most aggressive quantization here, so differences from BF16 and FP8 turn up more often depending on the prompt and settings.
Best for:
Blackwell / RTX 50-series
Minimum VRAM use
Minimum model size
Efficiency over absolute precision
Don't pick NVFP4 just because the file is small. On hardware that can't use it you lose most of the reason for it.
Quick pick
Plenty of VRAM and want the original: BF16
Not sure what to download: FP8
Need to cut VRAM use further: INT8 ConvRot
RTX 50-series / Blackwell GPU: MXFP8
Blackwell and want the smallest file: NVFP4
Differences between the quantized versions shift with your GPU, backend, workflow, resolution and prompt. No single format wins everywhere.
Recommended settings
These apply to Krea 2 Turbo and CyberRealistic Krea 2.
Sampler: Euler
Scheduler: Simple
Steps: 8
CFG (ComfyUI KSampler): 1.0
Guidance (official Krea code): 0.0
Mu / timestep shift: 1.15
Resolution: 1K to 2K
About that CFG value
Two conventions exist here and they cause a lot of confusion. Krea's own inference code uses guidance 0.0, which means CFG is off. The ComfyUI equivalent of "off" on the standard KSampler is CFG 1.0.
Don't set the regular KSampler to 0.0. That breaks generation.
Turbo runs without CFG, so traditional negative prompts do very little in the standard workflow. The official ComfyUI workflow simply zeroes the negative conditioning.
Steps and resolution
Turbo is an 8-step distilled model. More steps are not automatically better.
Krea 2 Turbo is built for roughly 1K to 2K, so there's no need to generate everything at 1024 first if your hardware can handle more. Useful starting points:
2048 × 20481536 × 20482048 × 15361152 × 20482048 × 11521440 × 1920
Lower resolutions are fine when you want speed or need the VRAM.
Required models
CyberRealistic Krea 2 diffusion model
qwen3vl_4btext encoderqwen_image_vae
Prompting
If you're coming from SDXL, Pony or Illustrious, read this part.
Krea 2 has no CLIP text encoder. It uses Qwen3-VL-4B, so it reads your prompt much more like normal language. You don't have to forget everything you know, but most old Stable Diffusion habits stop paying off here.
Describe, don't tag
Natural language works very well. Comma-separated clauses are fine, and Krea's own examples use them, but each clause should describe something instead of being a loose tag.
Instead of:
woman, street, night, realistic, masterpiece, best quality, 8k, detailed skin
try:
A woman waiting alone on a quiet city street at night, photographed under the warm light of a shop window, with natural skin texture and wet pavement reflecting the streetlights.
The second prompt tells the model what the image actually is.
Quality tags do nothing special
Words like masterpiece, best quality, ultra detailed, absurdres, score_9 and source_anime aren't quality switches here. Qwen reads them as ordinary language. They might nudge the result, but they're usually taking up space you could spend on something useful.
Describe the detail you want instead.
Skip numeric weighting
ComfyUI can parse (rust:1.4) syntax, but I wouldn't build Krea 2 prompts around it. Stronger wording is more predictable:
a heavily rusted iron gate, its hinges covered in rough orange corrosion
If you're running a LoRA, LoRA strength is a much better numeric control.
Put the subject first
Prompt order still matters in practice. If the image is about a brass compass, start with the compass:
A weathered brass compass resting on an old nautical chart...
No need to obsess over exact word order. Just make the subject and the main composition clear early.
Be specific
red dressbecomesdeep oxblood satin dressorange lightbecomeswarm sodium-vapor street lightingold wallbecomessun-bleached plaster wall with hairline cracks and flaking paint
Specific words carry more visual information than repeating "detailed" and "realistic."
Describe the actual light
This is the biggest single win for photographic prompts. Instead of cinematic lighting, say where the light comes from:
soft daylight entering through a north-facing window
a single tungsten bulb hanging above the table
late-afternoon sunlight coming through venetian blinds
cold fluorescent ceiling lights
Keep actions simple
Complex actions work, but if a pose starts breaking, simplify. One clear action per subject is a good rule. Get that working first, then add the secondary details.
Quote your text
If you want words in the image, put the exact text in quotation marks:
a small neon sign reading "OPEN ALL NIGHT"
Krea specifically recommends this.
A structure that works
subject → setting → composition/camera → lighting → mood/style → material and texture
A middle-aged fisherman repairing a red net on a wooden dock, photographed from waist height with a 50mm lens, grey sea behind him, soft overcast morning light, muted natural colors, weathered hands, damp wool sweater and rough salt-stained wood.
It doesn't have to read like literature. Dense descriptive clauses work fine. The point is that the words describe the image instead of listing magic tokens.
How long?
My practical ranges, not model limits:
5 to 20 words: exploration, let the model decide
30 to 80 words: good balance of control and freedom
80 to 150 words: complex scenes, precise styling, detailed composition
Longer prompts work. Length isn't the problem, contradiction is. Ask for soft window light, hard flash, dreamy pastels, deep black shadows and flat commercial lighting in one prompt and the model has to pick a winner. More words only help when they add information.
Example prompts
Available-light documentary
A fishmonger in a yellow rubber apron arranging silver mackerel on crushed ice at a covered market stall in the early morning. Cold blue daylight enters from the open side of the market and mixes with warm tungsten bulbs above the counter. The concrete floor is wet and reflective, with slight motion blur on his hands and natural texture in the skin, rubber and fish scales.
Natural-light portrait
A woman laughing with her eyes closed against a pale blue sky, loose dark hair blowing across her face, wearing a sleeveless white lace top. Photographed from a slightly low angle in soft natural daylight with a minimal background, medium-format color photograph, shallow depth of field and natural skin texture.
Low-light interior
A nervous teenager standing alone in a convenience-store aisle at two in the morning, photographed handheld with a 35mm lens. Harsh fluorescent ceiling lights fall across the shelves and face, with slight motion blur, visible film grain, muted colors and realistic skin texture.
Product photography
A matte black perfume bottle standing on wet obsidian stone, photographed close-up in a dark studio. A single large softbox creates a narrow reflection along the left edge of the bottle while a subtle rim light separates it from the background. Shallow depth of field, crisp glass and stone texture, controlled specular highlights.
A few last things
Short prompts are great for exploring. Turbo is fast enough that generating five directions first and then adding camera, light and material detail to the one you like beats writing a perfect prompt blind.
Text rendering is much better than older diffusion models, but it still isn't a typography engine. Quote the exact text and keep signs short.
And the licensing. Krea 2 is not Apache 2.0. The weights and everything derived from them fall under the Krea 2 Community License, which covers commercial use, redistribution, attribution and derivative naming. Commercial use is free below the stated annual revenue threshold. Above it you need an Enterprise License from Krea. The license also requires derivative model names to start with "Krea", which is why this one is called CyberRealistic Krea 2 and not the other way around.
If you're using or redistributing this model, read the current Krea 2 license instead of assuming the usual open-model terms.
Description
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CyberRealistic Krea2 V2 pushes the model further toward photographic realism while keeping the flexibility and strong prompt understanding of Krea 2.
V2 builds on the first release with additional training and refinement across faces, skin, anatomy, lighting, textures and everyday photographic situations. The goal wasn't to completely change the model, but to make the look more consistent across a much wider range of prompts.
Images should feel less polished-for-the-sake-of-being-polished and more like actual photography - natural skin texture, believable imperfections, better material detail and lighting that feels part of the scene rather than added on top of it.
What's changed in V2
More consistent photographic realism, especially with simple prompts.
Improved skin and facial detail without pushing everything toward beauty photography.
Better anatomy and body consistency across a wider range of compositions.
More natural lighting, shadows and highlights.
Improved textures and small details in clothing, environments and objects.
Less unwanted editorial gloss and aesthetic drift.
Better handling of casual, imperfect and unposed photography.
Broader training coverage, including content on the less sanitized side of photography.
CyberRealistic Krea2 is still primarily intended as a general-purpose photographic model. V2 isn't built around one specific genre or subject. Portraits, people, interiors, street photography, products, landscapes and more experimental or adult-oriented scenes should all live inside the same model rather than requiring separate versions.
Model variants
CyberRealistic Krea2 V2 is available in several formats:
BF16 - full-precision release and the reference version.
MXFP8 - reduced memory usage while staying close to BF16.
FP8 - a practical lower-VRAM alternative.
INT8 - further reduced memory requirements for compatible setups.
NVFP4 - the smallest variant for supported NVIDIA hardware and workflows.
The quantized versions are provided to make the model usable on a wider range of GPUs. Small differences between formats are possible, so BF16 remains the reference if you want the model exactly as released.
Prompting
Krea 2 responds best to clear natural-language descriptions rather than traditional Stable Diffusion tag lists. Describe the subject, environment, composition and lighting as you would describe a photograph.
V2 also responds well to short prompts. You don't need to bury the subject underneath quality tags to get detail - give it something interesting to photograph.
FAQ
Details
Files
cyberrealisticKrea2_v20_txt.safetensors
Mirrors
Qwen3-VL-4B-Instruct.safetensors
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qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
Qwen_Image-VAE.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
akanezora_v055BFP8INT8.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
toonimaSeries_toonimaZest.safetensors
qwen_image_vae.safetensors
qwenImageVAE_qwenImageVAE.safetensors
qwenImageVae_v10.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
jdxanima_illustration.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwenImageVAE_qwenImageVAE.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
Qwen_Image-VAE.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwenImageEdit_qwenImageEditVAE.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
miaomiaoAnimeReality_ani11.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
chosenMixAnima_v10.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
reakrea2Turbo_v10FP8.safetensors
qwen_image_vae.safetensors
qwenImageGGUF3QKM10G_vae.safetensors
seeKrea2_vae.safetensors
qwen_image_vae.safetensors
toonimaSeries_toonimaThirst.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
qwen_image_vae.safetensors
cyberrealisticKrea2_v20_txt.safetensors
Mirrors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
textencoder_qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
model.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
qwen3vl_4b_fp8_scaled.safetensors
loxsUtopicWorldKrea2_v10BF16_txt.safetensors
cyberrealisticKrea2_v10_txt.safetensors
seeKrea2_textEncoders.safetensors
krea2Turbo18For_v1_txt.safetensors
eventHorizon_krea2V10.safetensors
samKrea2_turboV10_txt.safetensors
cyberrealisticKrea2_v20_txt.safetensors
loxsUtopicWorldKrea2_v10Quants_txt.safetensors








