Civitai #144303090 Park Picnic: 2000s Vintage Film Candid Snapshot

Full Resolution

Generation Specs RTX 4070

Sampler euler

Scheduler simple

Steps 10

CFG Scale 1

Seed 2916076897

Target VRAM 12GB

VRAM 10GB - 12GB

GPU Hardware Compatibility

Optimal Ground Truth

Native GPU execution at full throughput with zero memory swapping.

Krea 2 Turbo (Qwen3-VL 4B + Wan 2.1 16-ch VAE) Civitai #144303090 Min 10GB VRAM 832×1152 RTX 4070 Verified

Park Picnic: 2000s Vintage Film Candid Snapshot

Production reproduction of Civitai Red trending #2 artwork #144303090. Authentic vintage 2000s amateur mobile snapshot aesthetic with candid unposed realism in natural midday lighting.

Blueprint Summary RTX 4070 Verified

Reproducible ComfyUI workflow for Civitai #144303090 Park Picnic: 2000s Vintage Film Candid Snapshot using Krea 2 Turbo (Qwen3-VL 4B + Wan 2.1 16-ch VAE) at 832×1152 resolution. Requires minimum 10GB VRAM with sampler euler and scheduler simple (10 steps). Includes 1-click terminal model sync and canvas JSON graph.

Node Graph Pipeline 11 Total Nodes

Verify in Resolver

01 Load Models

UNETLoader

5 loaders (DiT, CLIP, VAE)

02 Adapters

LoraLoader

2 adapters

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

Model & Asset Setup 1-Click Script

Run in your ComfyUI root:

curl -fsSL https://decomfy.com/api/scripts/civitai-park-picnic-candid-krea2.sh | bash

Positive Prompt

A low-resolution photo taken with an early mobile phone; the photo was taken in an amateur, candid manner. A charming 20-year-old woman with messy damp brown hair sits casually on a weathered gray picnic bench in an outdoor park setting. She wears a casual white tank top and denim shorts, laughing with an authentic spontaneous expression. In the background are rustic picnic tables, grassy trees, and soft natural midday sunlight filtered through light clouds. Grainy amateur 2000s snapshot texture, flash glare, casual mobile photography, unposed realism, authentic mood.

Negative Prompt

underage, child, glossy, airbrushed, studio portrait, 3d, illustration, cartoon, plastic, doll, distorted anatomy

LoRA Adapter Stack 2 Adapters

RTX 4070 Calibrated Weights

01 candid_krea2_loraholic.safetensors +0.8

02 snofs_krea_v1_4.safetensors +0.7

Required Models 5 Models

Disk Space Required: 19.0 GB (5 models · DiT/Base: 12.8 GB · Text Encoder: 4.4 GB · LoRAs: 1.6 GB · VAE: 254 MB)

models/diffusion_models/ 12.8 GB Civitai

BSSDesirexKrea2_x2INT8ConvrotFastest.safetensors DesireX Krea2 INT8 ConvRot fastest quantized DiT core

Get

models/text_encoders/ 4.4 GB HuggingFace

krea2_solordz_te_int8.safetensors Qwen3-VL 4B INT8 Text Encoder (Krea 2 Architecture)

Get

models/vae/ 254 MB HuggingFace

wan_2.1_vae.safetensors 16-channel VAE (prevents inverted contrast artifacts)

Get

models/loras/ 14.3 MB Civitai

candid_krea2_loraholic.safetensors Weight: 0.8 (Authentic unposed candid snapshot aesthetic)

Get

models/loras/ 1.56 GB Civitai

snofs_krea_v1_4.safetensors Weight: 0.7 (Photorealistic ambient lighting and noise fidelity)

Get

Field Notes RTX 4070 Benchmark

Benchmark: [object Object]

Reproduction of Civitai Red trending #2 artwork #144303090. Captures the grainy, uncalibrated consumer-grade CCD/CMOS sensor aesthetic of early 2000s digital photography without synthetic plastic sheen.

Frequently Asked Questions FAQ

What GPU and VRAM are required to run Civitai #144303090 Park Picnic: 2000s Vintage Film Candid Snapshot?

This workflow requires a minimum of 10GB VRAM (recommended 12GB VRAM). Tested and verified on NVIDIA GeForce RTX 4070 (12GB VRAM) at 832x1152 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.