✅ this one → Minimalist T2I Workflow for WAN Video 2.2 (Hugging Face)
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✅ this one → Minimalist T2I Workflow for WAN Video 2.2 (Hugging Face)
✅ Minimalist First-Last Frame to Video Workflow for WAN Video 2.2 (Hugging Face)
🔜 Minimalist FMLF (First-Middle-Last Frame) + Multi Frame Ref To Video Workflow for WAN Video 2.2 (Coming Soon)
🔜 Join Videos (Snippets) – Track Operations, Python Scripting: Be a Storyteller - Seamless Narrative Chain (Coming Soon)
Minimalist T2I Workflow for Wan Video 2.2
A streamlined text-to-image workflow utilizing WAN Video 2.2's High and Low Noise models (14B fp8) for static image generation. This setup deliberately omits the Lighting LoRAs to focus on the base models' capabilities...
AI-generated commentary
AI-generated explanation based on source and configuration details. Suggestions are clearly labeled.
Minimalist T2I Workflow for WAN Video 2.2 is for generating static images from text prompts with WAN Video 2.2 high- and low-noise 14B FP8 models.
The listed components include PreviewImage and SaveImage for the described static-image output.
Input: a text prompt describing the image to generate.
Output: a static image, with PreviewImage and SaveImage listed among the components.
GegenDenTag publishes it on Civitai at https://civitai.com/models/2163207.
The page classifies it as Workflows and lists Wan Video 2.2 T2V-A14B as the base model.
The listed model files are umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors, wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors, and wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors.
Core component names include CLIPLoader, CLIPTextEncode, EmptySD3LatentImage, GetNode, KSampler, ModelSamplingSD3, SetNode, and UNETLoader.
Additional component names are MarkdownNote, KSamplerAdvanced, PreviewImage, SaveImage, VAEDecode, and VAELoader.
The published setup omits Lighting LoRAs and additional conditioning through LoRAs and CNet.
It is described for evaluating how the base models represent artistic styles, techniques, and compositions.
Before using it, verify that your environment includes the named model files and components, including wan_2.1_vae.safetensors.
Suggestion · not verified
No release version is provided for this workflow.
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Sources
1 sourceSource excerpts
1 excerptSource context: 197 downloads · Type Workflows · Base model Wan Video 2.2 T2V-A14B
Dare to click the image — opens fixed-size copy.
... Optimized for evaluating the ability to represent artistic styles, techniques, and compositions, without the complexity of additional conditioning through LoRAs and CNet.
Prompting, showcase of different art styles tested with this workflow
Dare to click — opens Civitai Collection .
Estimated VRAM requirement
Estimate unavailable
Model file sizes are not complete enough to calculate this requirement yet.
Requirements
18 requirementsCLIPLoader
PossibleText encoder · Unknown
umt5_xxl_fp8_e4m3fn_scaled.safetensors
File unverifiedText encoder · Hugging Face · Comfy-Org/Wan_2.1_ComfyUI_repackaged · Comfy-Org/Wan_2.1_ComfyUI_repackaged · Hugging Face
VAEDecode
PossibleVAE · Unknown
VAELoader
PossibleVAE · Unknown
VAE · Hugging Face · Comfy-Org/Wan_2.2_ComfyUI_Repackaged
wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors
File unverifiedCheckpoint · Hugging Face · Comfy-Org/Wan_2.2_ComfyUI_Repackaged · Wan Video 2.2
wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors
File unverifiedCheckpoint · Hugging Face · Comfy-Org/Wan_2.2_ComfyUI_Repackaged · Wan Video 2.2
CLIPTextEncode
PossibleNode pack · Unknown
EmptySD3LatentImage
Not resolvedNode pack · Unknown
GetNode
Not resolvedNode pack · Unknown
KSampler
Node pack · Unknown
KSamplerAdvanced
PossibleNode pack · Unknown
MarkdownNote
Not resolvedNode pack · Unknown
ModelSamplingSD3
Not resolvedNode pack · Unknown
PreviewImage
PossibleNode pack · Unknown
SaveImage
PossibleNode pack · Unknown
SetNode
Not resolvedNode pack · Unknown
UNETLoader
PossibleNode pack · Unknown