Krea2 RAW-Turbo High Low Noise Sampling Workflow

This workflow is for Krea2 RAW-Turbo high-noise and low-noise sampling. It is designed to test a more advanced Krea2 rendering strategy: using a RAW model route for early high-noise image formation, then using a Turbo model route for lower-noise refinement and final completion.

The workflow uses krea2_raw_fp8_scaled.safetensors and Krea2-Turbo_fp8_nsfw.safetensors in the same production chain. It also uses qwen3vl_4b_fp8_scaled.safetensors as the Krea2 text encoder and qwen_image_vae.safetensors as the VAE. The base resolution is controlled through ResolutionSelector and is set for a 21:9 ultrawide 2MP route, making it suitable for cinematic panorama images, fantasy key visuals, wide posters, and large-scene concept art.

The workflow is built around multiple RandomNoise, BasicScheduler, SamplerCustomAdvanced, VAEDecode, VAEEncode, and ImageScaleBy stages. The RAW part is responsible for early structure, atmosphere, and high-noise formation. The Turbo part is used for later refinement, cleaner surface, and final image convergence. This gives the creator more control than a normal one-pass Krea2 render.

The purpose of this workflow is not simply speed. It is for testing how Krea2 behaves when different noise levels and model phases are separated. High-noise sampling can help establish stronger global composition and visual direction, while low-noise sampling can help refine texture, detail, and final image quality.

Main features:

• Krea2 RAW-Turbo high/low noise workflow

• RAW model early structure generation

• Turbo model low-noise refinement

• krea2_raw_fp8_scaled.safetensors support

• Krea2-Turbo_fp8_nsfw.safetensors support

• Qwen3-VL Krea2 text encoder

• Qwen Image VAE

• RandomNoise and BasicScheduler control

• SamplerCustomAdvanced multi-stage chain

• VAE decode and re-encode workflow

• 21:9 ultrawide 2MP base resolution

• Suitable for cinematic panoramas, fantasy scenes, and sampler testing

Suggested workflow:

Use this workflow when you want stronger control over the generation process than a normal single KSampler route. Start with a prompt that has clear subject, environment, lighting, and visual direction. Let the RAW phase establish the image foundation, then let the Turbo phase refine the result. If the image becomes unstable, simplify the prompt or reduce the number of visual concepts. If the result is too soft, strengthen texture and lighting details before changing the sampler chain.

⚙️ RunningHub Workflow

Try the workflow online right now — no installation required.
👉 Workflow: https://www.runninghub.ai/post/2074460408995471362?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/BV1nxM56cEta/

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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/2074460408995471362?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/BV1nxM56cEta/

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。