Watch the full video first if you want to understand how this Krea2 strong-drive portrait enhancement workflow works in practice. The video shows how a simple Krea2 Turbo image-generation route can be pushed harder through Rebalance conditioning, producing stronger composition, more intense lighting, clearer detail, and a more cinematic vertical portrait result.

This ComfyUI workflow is designed for Krea2 Turbo portrait and character-image generation with stronger Rebalance-driven conditioning. Compared with a basic Krea2 benchmark workflow, this version is more aggressive. It is built to make the prompt signal more forceful, especially when the creator wants stronger subject presence, sharper visual hierarchy, heavier atmosphere, richer lighting, and a more dramatic final image.

The workflow uses krea2_turbo_bf16.safetensors as the main model. The text encoder route uses qwen3vl_4b_fp8_scaled.safetensors with the Krea2 CLIP type, and the VAE route uses qwen_image_vae.safetensors. This keeps the graph lightweight while still allowing a high-impact Krea2 render style.

The key node in this workflow is ConditioningKrea2Rebalance. It uses a custom 12-layer per-layer weight setup:

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, making this version much stronger than a moderate Rebalance setup. This is why the workflow is positioned as a “strong-drive” portrait enhancement version. It is useful when the normal Krea2 output feels too restrained, too flat, or not visually intense enough.

The sampling route is still simple and fast. The workflow uses KSampler with 8 steps, CFG 1, euler sampler, sgm_uniform scheduler, full denoise, and a fixed seed. This makes it easy to test prompt changes and Rebalance behavior under stable conditions. The fixed seed also makes the workflow useful for before-and-after comparisons, parameter testing, and prompt benchmark experiments.

The resolution section uses FluxResolutionNode with a 9:16 vertical layout. This makes the workflow suitable for mobile-first visuals, vertical posters, character portraits, fantasy covers, short-video thumbnails, social-media images, and RunningHub app previews. The latent route is connected to EmptyLatentImage, then decoded through VAEDecode and exported through PreviewImage and SaveImage.

This workflow is especially useful for cinematic fantasy portraits, dramatic character shots, vertical poster images, game-style key visuals, AI influencer portraits, and stylized social-media covers. It is not a complex multi-stage upscaling workflow. Its value is speed, clarity, and strong conditioning pressure.

Main features:

• Krea2 Turbo strong-drive portrait workflow

• Rebalance-enhanced conditioning

• 12-layer custom Conditioning control

• Multiplier 4.0 for stronger prompt response

• krea2_turbo_bf16.safetensors support

• qwen3vl_4b_fp8_scaled.safetensors text encoder

• qwen_image_vae.safetensors VAE

• 8-step fast image generation

• CFG 1 setup

• euler sampler

• sgm_uniform scheduler

• Fixed seed for repeatable testing

• 9:16 vertical image layout

• Positive-prompt-focused generation

• Empty negative conditioning route

• VAEDecode final image output

• PreviewImage and SaveImage support

• Suitable for cinematic portraits, character posters, and vertical fantasy visuals

Suggested workflow:

Start with a focused portrait or character prompt. Describe the subject first, then add clothing, pose, lighting, background, atmosphere, camera angle, and style direction. Since this workflow uses a strong Rebalance multiplier, avoid overloading the prompt with too many conflicting ideas. If the image becomes too harsh, too sharp, or too visually crowded, simplify the prompt before changing model settings. If the output is still not strong enough, strengthen the subject hierarchy and lighting language. This workflow works best when you want a fast Krea2 render with more intensity than the standard baseline.

⚙️ 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。