Native GPU execution at full throughput with zero memory swapping.
Morning Bed Selfie - Overhead Candid & Krea 2 Turbo
Hyperrealistic 1:1 square candid overhead selfie photograph rendered on Krea 2 Turbo. Features a relaxed young woman reclining on crisp white cotton bedding with soft morning window light and authentic dewy skin textures.
Reproducible ComfyUI workflow for Civitai #144128215: Morning Bed Selfie - Overhead Candid & Krea 2 Turbo using Krea 2 Turbo (Official Comfy-Org) at 1024×1024 resolution. Requires minimum 8GB VRAM with sampler euler and scheduler simple (10 steps). Includes 1-click terminal model sync and canvas JSON graph.
Execution DAG Topology Interactive Visualizer
Drag to pan · Scroll to zoom · Hover wiresModel & Asset Setup 1-Click Script
Run in your ComfyUI root:
curl -fsSL https://decomfy.com/api/scripts/civitai-morning-bed-selfie-krea2.sh | bash Loading bash setup script... Loading PowerShell setup script... import modal
app = modal.App("comfyui-civitai-morning-bed-selfie-krea2")
vol = modal.Volume.from_name("comfy-weights-cache", create_if_missing=True)
image = (
modal.Image.debian_slim(python_version="3.11")
.apt_install("git", "wget", "curl", "libgl1-mesa-glx", "libglib2.0-0")
.pip_install("torch", "torchvision", "--index-url", "https://download.pytorch.org/whl/cu124")
.pip_install("transformers", "accelerate", "safetensors", "aiohttp")
.run_commands(
"git clone https://github.com/comfyanonymous/ComfyUI.git /root/ComfyUI",
"cd /root/ComfyUI && pip install -r requirements.txt",
)
)
@app.function(
gpu="T4",
image=image,
volumes={"/root/ComfyUI/models": vol},
timeout=900,
)
def generate():
# Headless serverless execution for Krea 2 Turbo (Official Comfy-Org)
print("Executing Civitai #144128215: Morning Bed Selfie - Overhead Candid & Krea 2 Turbo on ephemeral T4 GPU...")
return {"status": "success", "slug": "civitai-morning-bed-selfie-krea2"}
runpodctl create pod \
--name "comfy-civitai-morning-bed-selfie-krea2" \
--gpu-type "NVIDIA RTX 4070 Ti" \
--image "runpod/comfyui:latest" \
--volume-in-gb 50 \
--ports "8188/http" # ComfyUI Model Batch Ingestion for Civitai #144128215: Morning Bed Selfie - Overhead Candid & Krea 2 Turbo
# Run with: aria2c -i models-civitai-morning-bed-selfie-krea2.txt -j4 -x4
https://huggingface.co/Comfy-Org/Krea-2/resolve/main/diffusion_models/krea2_turbo_int8_convrot.safetensors
dir=models/diffusion_models
out=krea2_turbo_int8_convrot.safetensors
https://huggingface.co/Comfy-Org/Krea-2/resolve/main/text_encoders/qwen3vl_4b_fp8_scaled.safetensors
dir=models/text_encoders
out=qwen3vl_4b_fp8_scaled.safetensors
https://huggingface.co/Comfy-Org/Krea-2/resolve/main/vae/qwen_image_vae.safetensors
dir=models/vae
out=qwen_image_vae.safetensors
https://civitai.com/api/download/models/3371723
dir=models/loras
out=RealisticSnapshotKrea2V2.safetensors
https://huggingface.co/hoangyellcom/decomfy-loras/resolve/main/loras/refusal_reduction_v2_full_rank.safetensors
dir=models/loras
out=refusal_reduction_v2_full_rank.safetensors Positive Prompt
Negative Prompt
mode: 2). When importing into ComfyUI, you can unmute it or freely write any custom prompt, characters, or aesthetic styles. The underlying model checkpoint, LoRA adapter stack, and sampling pipeline will faithfully execute your vision.
LoRA Adapter Stack 2 Adapters
RTX 4070 Calibrated WeightsRequired Models 5 Models
Field Notes RTX 4070 Benchmark
Frequently Asked Questions FAQ
What GPU and VRAM are required to run Civitai #144128215: Morning Bed Selfie - Overhead Candid & Krea 2 Turbo?
This workflow requires a minimum of 8GB VRAM (recommended 12GB VRAM). Tested and verified on NVIDIA GeForce RTX 4070 (12GB VRAM) at 1024x1024 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.
Which VAE and conditioning text encoders are required for Krea 2 DiT?
Krea 2 DiT single-stream models strictly require the 16-channel Wan2.1 VAE and Qwen3-VL text encoder. Using standard Flux or SDXL VAE causes inverted checkerboard artifacts. Also pair with RescaleCFG for high-contrast portrait clarity.