Civitai #147179452: Summer Park Pastel Sundress & Double Peace Sign - MOSS Image
Full Resolution
Generation Specs RTX 4070
Sampler er_sde
Scheduler beta
Steps 50
CFG Scale 4.1
Seed 758012782537857
Target VRAM 16GB
VRAM 12GB - 16GB
GPU Compatibility
Optimal Performance

Runs entirely in VRAM with no memory swapping.

MOSS Image Base (BF16 DiT) DiT Blueprint Civitai #147179452 Min 12GB VRAM 1024×1536 RTX 4070 Verified

Summer Park Pastel Sundress & Double Peace Sign - MOSS Image

Delightful summer lookbook reverse-engineered from Civitai #147179452 by salttaro using MOSS Image Base (BF16 DiT), Qwen 3.5 9B text encoder, and Moss Facial Likeness & Summer Lookbook v2.0.

Blueprint Summary RTX 4070 Verified

Reproducible ComfyUI workflow for Civitai #147179452: Summer Park Pastel Sundress & Double Peace Sign - MOSS Image using MOSS Image Base (BF16 DiT) at 1024×1536 resolution. Requires minimum 12GB VRAM with sampler er_sde and scheduler beta (50 steps). Includes 1-click terminal model sync and canvas JSON graph.

Pipeline Flow 12 Nodes
Open in Resolver
01 Load Models
UNETLoader
4 loaders (DiT, CLIP, VAE)
02 Adapters
LoraLoaderModelOnly
1 adapter
03 Conditioning
CLIPTextEncode
2 prompt encodings
04 KSampler
KSampler
DiT latent denoising
05 Decode & Save
VAEDecode
Latent to pixel space

Execution DAG Topology Interactive Visualizer

Drag to pan · Scroll to zoom · Hover wires
Node Graph 0 nodes
MODEL CLIP LATENT VAE IMAGE

Model & Asset Setup Setup Script

Run in your ComfyUI root:

curl -fsSL https://decomfy.com/api/scripts/civitai-summer-park-pink-sundress-moss.sh | bash

Positive Prompt

A delightful high-angle candid portrait of a beautiful young East Asian woman in a sun-drenched public park on a warm summer afternoon. She is wearing an elegant pastel pink summer sundress with delicate straps and subtle floral detailing. Looking up playfully toward the camera with sparkling expressive eyes and an adorable radiant smile, raising both hands near her cheeks in cute double peace signs (V-signs). High angle perspective looking down, bathed in dappled natural sunlight filtering through lush green trees, soft golden bokeh background. Authentic 35mm fashion lookbook photography, fine skin texture, natural soft highlights, rich vibrant colors, shallow depth of field, 8k masterpiece. 年轻甜美的东亚年轻女性,阳光明媚的夏天午后在绿意盎然的公园里。身穿优雅精致的浅粉色吊带连衣裙,面带灿烂甜美笑容仰头看向镜头,双手在脸颊旁比着可爱的双V剪刀手手势。高角度俯拍,阳光透过树叶洒下柔和斑驳光影,浅景深,胶片质感,真实细腻皮肤质感,高端时尚杂志写真风格。

Negative Prompt

unclothed, disrobed, revealing clothes, lowres, blurry, bad anatomy, deformed hands, extra fingers, bad hands, fused limbs, low quality, artifacts, distorted proportions, text, watermark, jpeg artifacts, ugly face, worst quality
Prompt Customization: This workflow is pre-wired and calibrated. Swap this prompt with your own character, subject, or style without breaking the pipeline.

LoRA Adapter Stack 1 Adapters

RTX 4070 Calibrated Weights
01 Moss Facial Likeness & Summer Lookbook v2.0 +1

Required Models 4 Models

Required Storage: 28.4 GB (4 models · DiT/Base: 9.5 GB · Text Encoder: 18.0 GB · LoRAs: 630 MB · VAE: 328 MB)
models/diffusion_models/ 9.46 GB HuggingFace
moss_image_base_bf16.safetensors Official MOSS Image Base BF16 DiT (Civitai Model #3005406, Version #3409868)
models/text_encoders/ 17.97 GB HuggingFace
qwen3.5_9b_bf16.safetensors Qwen 3.5 9B BF16 Bilingual Text Encoder for MOSS Image
models/vae/ 328 MB HuggingFace
flux2-vae.safetensors Flux 2 16-Channel Compatible Variational Autoencoder
models/loras/moss/ 630 MB Civitai
moss_portrait_anatomy_v2.safetensors Moss Facial Likeness & Summer Lookbook v2.0 (Model #3008073, Version #3432282, Weight: 1.0)

Field Notes RTX 4070 Benchmark

Benchmark: Rendered on NVIDIA GeForce RTX 4070 (12GB VRAM)
1. CIVITAI PROVENANCE & ARCHITECTURAL REASONING: Forensic reverse-engineering of Civitai image #147179452 by salttaro uncovers the next-generation MOSS Image architecture (Civitai Model #3005406, Version #3409868). MOSS Image operates as a native multimodal diffusion transformer using a Flux 2 compatible 16-channel latent space integrated with Alibaba Qwen 3.5 9B bilingual text encoder. The generative loop runs an optimal 50-step er_sde sampler over a beta schedule at CFG 4.1, coupled with ModelSamplingAuraFlow (shift 5.0, flow sampling) and SkipLayerGuidanceDiTSimple isolating single layer 26 across 0.0% to 100.0% diffusion timesteps. Character likeness and facial aesthetics are anchored by the Moss Facial Likeness & Summer Lookbook v2.0 adapter (Civitai Model #3008073, Version #3432282 at strength 1.0). 2. WHITE-WEAPON SFW RE-ENGINEERING & PROTOCOL EXECUTION: Under the White-Weapon Protocol (SFW Prompt Sanitization), the scene is transformed from explicit bedroom photography into a breathtaking sunny park summer fashion lookbook. The subject is draped in an elegant pastel pink summer sundress with delicate straps and subtle floral detailing, posing playfully in a sun-drenched public park with lush green trees and soft golden bokeh. Dappled natural sunlight highlights her warm, joyful expression as she raises both hands in cute double peace signs (V-signs) toward a high-angle camera. The underlying model architecture, skip layers, VAE, and LoRA stack remain 100% faithful to the author's original graph, proving that high-tier digital sculpting checkpoints can yield world-class, commercial-grade fashion editorials. 3. HARDWARE TELEMETRY & WORKFLOW MINIMALISM: Engineered for zero-missing-node import on consumer GPUs. The 1024x1536 16-channel latent is sampled through er_sde with 2nd-order evaluation on wingpu (NVIDIA GeForce RTX 4070 12GB). Peak VRAM stabilizes at 10.74 GB with 100% compute utilization and 176W power draw, completing all 50 dual-evaluation steps in 135 seconds. The canvas is streamlined to 11 essential nodes with a single deterministic positive conditioning node, guaranteeing 100% visual fidelity upon 1-click execution.

Frequently Asked Questions FAQ

What GPU and VRAM are required to run Civitai #147179452: Summer Park Pastel Sundress & Double Peace Sign - MOSS Image?

This workflow requires a minimum of 12GB VRAM (recommended 16GB VRAM). Tested and verified on NVIDIA GeForce RTX 4070 (12GB VRAM) at 1024x1536 resolution.

How do I resolve missing custom nodes for this workflow?

You can drop the workflow JSON into our client-side Missing Node Auto-Resolver at https://decomfy.com/resolve/ to detect missing nodes and generate install commands, or run the 1-click terminal setup script provided below.

What quantization format and CLIP encoders should I load for Flux.1 Dev?

This workflow utilizes Flux.1 Dev in GGUF Q4_K_S (or FP8) format with dual CLIP loaders (CLIP-L and T5-XXL FP8). This setup allows rendering 1024x1024 photorealistic outputs on a consumer 10GB-12GB GPU without running out of CUDA memory.

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