Native GPU execution at full throughput with zero memory swapping.
Mediterranean Olive Tree: Krea 2 Photorealism & Conditioning Rebalance
Ground-truth reproduction of Civitai artwork #143812695 authored by ShinobiSat. Powered by Krea 2 DiT architecture, Qwen3-VL 4B text encoder, Wan 2.1 16-channel VAE, ConditioningKrea2Rebalance per-layer weighting, and high-order stochastic er_sde sampling.
Reproducible ComfyUI workflow for Civitai #143812695 Mediterranean Olive Tree: Krea 2 Photorealism & Conditioning Rebalance using Krea 2 (CielBleu / Sick Ollie DiT) at 1280×1728 resolution. Requires minimum 10GB VRAM with sampler er_sde and scheduler simple (8 steps). Includes 1-click terminal model sync and canvas JSON graph.
Execution DAG Topology Interactive Visualizer
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Run in your ComfyUI root:
curl -fsSL https://decomfy.com/api/scripts/civitai-olive-tree-mediterranean-krea2.sh | bash Loading bash setup script... Loading PowerShell setup script... import modal
app = modal.App("comfyui-civitai-olive-tree-mediterranean-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 (CielBleu / Sick Ollie DiT)
print("Executing Civitai #143812695 Mediterranean Olive Tree: Krea 2 Photorealism & Conditioning Rebalance on ephemeral T4 GPU...")
return {"status": "success", "slug": "civitai-olive-tree-mediterranean-krea2"}
runpodctl create pod \
--name "comfy-civitai-olive-tree-mediterranean-krea2" \
--gpu-type "NVIDIA RTX 4090" \
--image "runpod/comfyui:latest" \
--volume-in-gb 50 \
--ports "8188/http" # ComfyUI Model Batch Ingestion for Civitai #143812695 Mediterranean Olive Tree: Krea 2 Photorealism & Conditioning Rebalance
# Run with: aria2c -i models-civitai-olive-tree-mediterranean-krea2.txt -j4 -x4
https://civitai.com/api/download/models/3154408
dir=models/diffusion_models
out=sickOllie_krea2.safetensors
https://huggingface.co/silveroxides/krea2_text_encoders/resolve/main/krea2_solordz_te_int8.safetensors
dir=models/text_encoders
out=krea2_solordz_te_int8.safetensors
https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/Wan2.1_VAE.pth
dir=models/vae
out=wan_2.1_vae.safetensors Positive Prompt
Required Models 3 Models
Field Notes RTX 4070 Benchmark
Ground-Truth Reproduction & White-Weapon Protocol: Reverse-engineered from Civitai artwork #143812695 authored by ShinobiSat. Powered by Krea 2 DiT architecture paired with Qwen3-VL 4B INT8 text encoder and Wan 2.1 16-channel VAE (fixing inverted contrast artifacts). Utilizes nova452's ConditioningKrea2Rebalance (multiplier: 0.5, per-layer weights: 1.0,1.0,1.0,1.0,1.0,1.0,1.0,2.5,5.0,1.1,4.0,1.0) to rebalance multi-layer text conditioning for maximum skin texture and dynamic range. Sampled using high-order stochastic er_sde solver with simple scheduler in just 8 steps at 1280x1728 resolution. Pre-wired canvas workflow features dual prompt conditioning: Node A provides an instant compliant SFW Mediterranean linen lookbook render, while Node B preserves the original generation prompt for 1-click local cable swapping.
Frequently Asked Questions FAQ
What GPU and VRAM are required to run Civitai #143812695 Mediterranean Olive Tree: Krea 2 Photorealism & Conditioning Rebalance?
This workflow requires a minimum of 10GB VRAM (recommended 12GB VRAM). Tested and verified on NVIDIA GeForce RTX 4070 (12GB VRAM) at 1280x1728 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.
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