Wan 2.2 - Simple i2v Workflow | Prompt Adherence / High Quality / No Extra Nodes
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Model description
A super simple workflow for generating videos from images, with excellent prompt adherence and really solid quality!
The idea here is to keep it beginner-friendly, so no extra nodes are required.
How Wan 2.2 works:
High Noise: Handles the motion in the video. If your movement looks off, just increase the High Noise steps.
Low Noise: Takes care of the details (faces, hands, fine textures). If details look messy, increase the Low Noise steps.
In this example, I kept High Noise without a LoRA — it’s responsible for executing the core prompt. Adding a LoRA here often reduces prompt adherence, so it’s better to let it run slowly and keep things clean.
On the other hand, for Low Noise, I added a 4-step LoRA to speed up detail refinement. If you remove it, expect slower execution and the need for more steps to achieve good quality.
Downloads / Setup
LoRA: Wan2.2-I2V-A14B-4steps-lora-rank64-Seko-V1_Low_Noise.safetensors
Wan 2.2 High Noise: wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors
Wan 2.2 Low Noise: wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors
Text Encoder: umt5_xxl_fp8_e4m3fn_scaled.safetensors
Previews
Workflow Screen: screenshot
Input Image: image
Sample Video: video