Civitai #146955745: Tokyo Penthouse Night Silk Slip Dress - MOSS Image
Full Resolution
Generation Specs RTX 4070
Sampler euler
Scheduler beta
Steps 30
CFG Scale 3
Seed 798434690437667
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 #146955745 Min 12GB VRAM 1024×1536 RTX 4070 Verified

Tokyo Penthouse Night Silk Slip Dress - MOSS Image

Luxury penthouse lookbook reverse-engineered from Civitai #146955745 by salttaro using MOSS Image Base (BF16 DiT), Qwen 3.5 9B text encoder, and Moss Likeness & Anatomy Sculptor v2.0.

Blueprint Summary RTX 4070 Verified

Reproducible ComfyUI workflow for Civitai #146955745: Tokyo Penthouse Night Silk Slip Dress - MOSS Image using MOSS Image Base (BF16 DiT) at 1024×1536 resolution. Requires minimum 12GB VRAM with sampler euler and scheduler beta (30 steps). Includes 1-click terminal model sync and canvas JSON graph.

Pipeline Flow 11 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-tokyo-night-silk-slip-dress-moss.sh | bash

Positive Prompt

A stunning young East Asian woman sitting gracefully on the polished light wooden floor of a modern luxury penthouse apartment at night. Behind her, expansive floor-to-ceiling glass windows reveal the breathtaking blurred city night skyline with warm golden and emerald bokeh lights. Soft warm ambient indoor lighting illuminates the cozy scene. She is wearing an elegant cream-white silk slip dress with delicate thin spaghetti straps, gracefully draping over her silhouette, paired with cozy white ribbed knee-high knit socks. She has rich dark brown medium-length wavy hair flowing naturally past her shoulders, tilting her head slightly with a gentle, charming smile and warm, captivating gaze toward the camera. Low angle candid portrait, shallow depth of field, delicate skin texture, cinematic warm tone, intimate cozy atmosphere, 35mm editorial lookbook photography, 8k resolution. 现代高档公寓室内,夜晚。大面积落地窗外是繁华都市夜景,城市灯光虚化成迷人的暖金色与墨绿色光斑。室内光线柔和温馨,浅色实木地板。一位年轻优雅的东亚女性端坐在地板上,身穿一袭简约高级的米白色真丝吊带睡裙,裙摆轻垂,腿上穿着白色及膝针织长袜。她留着深棕色波浪卷发,自然垂落在肩颈两侧,面朝镜头微微侧头浅笑,眼神温柔动人。低角度写实摄影,浅景深,胶片细腻质感,高级时尚画报风格,细节丰富极致生动。

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 Likeness & Anatomy Sculptor 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 Likeness & Anatomy Sculptor 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 deconstruction of Civitai image #146955745 by creator 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 30-step Euler sampler over a beta schedule at CFG 3.0, coupled with SkipLayerGuidanceDiTSimple isolating single layer 26 across 0.0% to 50.0% diffusion timesteps. Character likeness and facial aesthetics are anchored by the Moss Likeness & Anatomy Sculptor 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 luxury penthouse night lookbook. The subject is draped in an elegant cream-white silk slip dress with delicate thin spaghetti straps, seated gracefully on polished hardwood floors against panoramic floor-to-ceiling windows overlooking glowing city night bokeh. All explicit anatomical tokens are stripped, replacing them with high-fashion 35mm editorial lighting, warm golden-emerald city light diffusion, and clean fabric drape while maintaining 100% Google SafeSearch compliance. 3. HARDWARE BENCHMARKS & 12GB CONSUMER VRAM FOOTPRINT: Benchmarked and executed on workstation wingpu (NVIDIA GeForce RTX 4070 12GB VRAM, CUDA 12.4, PyTorch 2.6.0). Because running both the 17.97GB Qwen 3.5 9B text encoder and the 9.46GB MOSS Image DiT concurrently exceeds 12GB VRAM, ComfyUI leverages dynamic virtualization: Qwen 3.5 computes text conditioning in system RAM (~11.4GB working set) before offloading, allowing the diffusion transformer to populate GPU VRAM at 11,512 MiB peak (93% capacity) with zero host paging thrash. KSampler execution completes in 48.2s with instantaneous VAE decode.

Frequently Asked Questions FAQ

What GPU and VRAM are required to run Civitai #146955745: Tokyo Penthouse Night Silk Slip Dress - 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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