Krea 2 is an excellent text-to-image model, but many people are trying to use it as an image editing model in Comfy UI.
In this video, I explain why Krea 2 cannot perform true image-to-image editing, even if you add custom nodes or pass a VAE latent into the workflow. We'll look at how Krea 2 actually works internally, how the Vision Language Model (VLM) influences generation, and why the reference image is converted into text conditioning instead of being directly edited.
I also test several approaches to achieve better consistency, including:
• Standard image-to-image workflows
• Qwen-Image Edit Plus
• Krea-2-Text-Encoder
• Conditioning Rebalance
• Vision Megapixels and Vision Position settings
• Mask-based visual conditioning
• Hybrid Qwen + Krea 2 inference
• Can Krea 2 use ControlNet?
• Practical techniques to improve character consistency
By the end of the video, you'll understand the limitations of Krea 2, what actually happens inside the workflow, and the best methods currently available for reference-based image generation.
In this video, I explain why Krea 2 cannot perform true image-to-image editing, even if you add custom nodes or pass a VAE latent into the workflow. We'll look at how Krea 2 actually works internally, how the Vision Language Model (VLM) influences generation, and why the reference image is converted into text conditioning instead of being directly edited.
I also test several approaches to achieve better consistency, including:
• Standard image-to-image workflows
• Qwen-Image Edit Plus
• Krea-2-Text-Encoder
• Conditioning Rebalance
• Vision Megapixels and Vision Position settings
• Mask-based visual conditioning
• Hybrid Qwen + Krea 2 inference
• Can Krea 2 use ControlNet?
• Practical techniques to improve character consistency
By the end of the video, you'll understand the limitations of Krea 2, what actually happens inside the workflow, and the best methods currently available for reference-based image generation.
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