Krea2 Civitai-Style Texture Replication Workflow

Watch the full video first if you want to understand how this Krea2 Civitai-style texture replication workflow works in practice. The video shows how Krea2 Turbo can be used with a tag-driven prompt structure and strong Rebalance conditioning to create images with the kind of polished fantasy texture, character detail, and illustration-style finish often seen in community model galleries.

This ComfyUI workflow is designed for Krea2 Civitai-style image generation. Its purpose is not only to generate a normal Krea2 image, but to reproduce a more tag-based, high-detail, gallery-style visual language. It is especially useful for creators who want stronger character rendering, richer fantasy texture, more detailed costume design, clearer lighting structure, and a more polished illustration finish.

The workflow uses Krea2_Turbov10Fp8.safetensors as the main model. The text encoder route uses qwen3vl_4b_fp8_scaled.safetensors with the Krea2 CLIP type, while the VAE route uses qwen_image_vae.safetensors. This keeps the graph lightweight and fast, while still allowing a strong stylized image output.

The main control module is ConditioningKrea2Rebalance. The workflow uses a custom 12-layer per-layer weight structure:

1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.5, 5.0, 1.1, 4.0, 1.0

The multiplier is set to 4.0, which makes the conditioning drive much stronger than a standard baseline setup. This helps the prompt tags and visual concepts become more visible in the final image, especially for texture, contrast, costume detail, character definition, fantasy atmosphere, and overall style intensity.

The prompt route uses a Civitai-style tag structure, starting with quality tags such as score_9, score_8_up, score_7_up, masterpiece, best quality, absurdres, and highly detailed. This is followed by character tags, subject description, fantasy setting, lighting, atmosphere, and style direction. The example prompt focuses on a white fox priestess, ornate ceremonial clothing, divine armor details, a ruined ancient temple city, colossal deity statues, dragon-shaped mist spirits, burning amber light, dark teal shadows, and a mythic Chinese fantasy atmosphere.

The sampling setup is simple and fast. It uses KSampler with 8 steps, CFG 1, euler sampler, simple scheduler, full denoise, and a fixed seed. This makes the workflow practical for fast testing, prompt comparison, Civitai-style tag experiments, and repeatable visual benchmarking.

The image layout is controlled through FluxResolutionNode. The uploaded workflow is set to a 9:16 vertical format, making it suitable for mobile posters, character covers, fantasy illustration cards, social-media images, RunningHub previews, and vertical AI artwork.

Main features:

• Krea2 Civitai-style texture replication workflow

• Krea2_Turbov10Fp8.safetensors support

• qwen3vl_4b_fp8_scaled.safetensors text encoder

• qwen_image_vae.safetensors VAE

• Civitai-style tag prompt structure

• score_9 / score_8_up / masterpiece-style quality tags

• ConditioningKrea2Rebalance enhancement

• 12-layer custom Rebalance weights

• Multiplier 4.0 strong conditioning drive

• 8-step fast generation

• CFG 1 setup

• euler sampler

• simple scheduler

• Fixed seed for repeatable tests

• 9:16 vertical image format

• Empty negative conditioning route

• VAEDecode final image decoding

• PreviewImage and SaveImage output

• Suitable for fantasy characters, furry characters, stylized portraits, and vertical illustration covers

Suggested workflow:

Start with quality tags first, then add the subject, character type, clothing, pose, background, lighting, atmosphere, and final style direction. Keep the tag structure clear instead of writing a messy prompt. If you want a stronger Civitai-style result, use specific material and texture words such as ornate armor, flowing robe, divine backlight, floating ash, ultra-detailed stone texture, cinematic center composition, and mythic fantasy atmosphere. If the image becomes too crowded, reduce the number of background elements before changing the sampler. If the character loses clarity, make the subject description shorter and move the most important identity tags closer to the front of the prompt.

⚙️ RunningHub Workflow

Try the workflow online right now — no installation required.
👉 Workflow: https://www.runninghub.ai/post/2072175221502734338?inviteCode=rh-v1111

If the results meet your expectations, you can later deploy it locally for customization.

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📺 Bilibili Updates (Mainland China & Asia-Pacific)

If you’re in the Asia-Pacific region, you can watch the video below to see the workflow demonstration and creative breakdown.
📺 Bilibili Video: https://www.bilibili.com/video/BV1FWT76KENn/

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⚙️打开下方链接即可在线体验，无需安装。
👉 工作流： https://www.runninghub.ai/post/2072175221502734338?inviteCode=rh-v1111
如果觉得效果理想，你也可以在本地进行自定义部署。

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📺 Bilibili 更新（中国大陆及南亚太地区）

如果你在中国大陆或南亚太地区，可以通过下方视频查看该工作流的实测效果与构思讲解。
📺 B站视频： https://www.bilibili.com/video/BV1FWT76KENn/

我会在 夸克网盘 持续更新模型资源：
👉 https://pan.quark.cn/s/20c6f6f8d87b
这些资源主要面向本地用户，方便进行创作与学习。