Civitai #144099372: Smartphone POV Candid - Night Market Viewfinder & Krea 2 Turbo

Full Resolution

Generation Specs RTX 4070

Sampler euler

Scheduler simple

Steps 10

CFG Scale 1

Seed 2026092876

Target VRAM 12GB

VRAM 8GB - 12GB

GPU Hardware Compatibility

Optimal Ground Truth

Native GPU execution at full throughput with zero memory swapping.

Krea 2 Turbo (Official Comfy-Org) Civitai #144099372 Min 8GB VRAM 1248×832 RTX 4070 Verified

Smartphone POV Candid - Night Market Viewfinder & Krea 2 Turbo

Authentic smartphone camera POV documentary snapshot rendered on Krea 2 Turbo. Features a first-person phone viewfinder capturing a smiling young woman in a rustic night market artisan stall with direct flash and natural ambient warmth.

Blueprint Summary RTX 4070 Verified

Reproducible ComfyUI workflow for Civitai #144099372: Smartphone POV Candid - Night Market Viewfinder & Krea 2 Turbo using Krea 2 Turbo (Official Comfy-Org) at 1248×832 resolution. Requires minimum 8GB VRAM with sampler euler and scheduler simple (10 steps). Includes 1-click terminal model sync and canvas JSON graph.

Node Graph Pipeline 12 Total Nodes

Verify in Resolver

01 Load Models

UNETLoader

5 loaders (DiT, CLIP, VAE)

02 Adapters

LoraLoader

2 adapters

03 Conditioning

CLIPTextEncode

3 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-smartphone-pov-candid-krea2.sh | bash

Positive Prompt

POV first-person perspective, close-up foreground hand holding up an iPhone smartphone recording video, live camera app viewfinder clearly visible on the glowing phone screen. Framing a smiling beautiful young Thai woman with natural hair and bangs, wearing a tasteful white linen halter top, laughing candidly in a rustic wooden artisan workshop stall at night. Direct camera flash illumination, warm tungsten overhead bulb, hanging woven textiles and pottery in the blurred background, authentic travel documentary photography, film grain, unposed spontaneous happiness, realistic skin texture, 8k crisp details, cinematic amateur snapshot.

Negative Prompt

deformed, bad anatomy, deformed hands, extra fingers, missing fingers, lowres, blurry, distorted proportions, low quality, artifacts, watermark, signature, cartoon, 3d render, plastic skin, CGI, airbrushed, overexposed blown highlights

Custom Prompt Freedom: This workflow is 100% pre-wired. The canvas includes a secondary standby conditioning node (muted 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 Weights

01 Realistic Snapshot (Z-Image-Turbo + Krea 2) +1

02 Krea2 Refusal Reduction V2 (Full Rank) +1

Required Models 5 Models

Disk Space Required: 21.7 GB (5 models · DiT/Base: 12.6 GB · Text Encoder: 4.9 GB · LoRAs: 4.0 GB · VAE: 253 MB)

models/diffusion_models/ 12.56 GB HuggingFace

krea2_turbo_int8_convrot.safetensors Official Krea 2 Turbo INT8 ConvRot Diffusion Transformer core

Get

models/text_encoders/ 4.88 GB HuggingFace

qwen3vl_4b_fp8_scaled.safetensors Official Qwen3-VL 4B FP8 Scaled Text Encoder (CLIPLoader type: krea2)

Get

models/vae/ 253 MB HuggingFace

qwen_image_vae.safetensors Official 16-channel Video & Image VAE

Get

models/loras/ 1.49 GB Civitai

RealisticSnapshotKrea2V2.safetensors Weight: 1.0 (Realistic Snapshot adapter for smartphone camera viewfinder and candid flash realism)

Get

models/loras/ 2.48 GB HuggingFace (Mirror)

refusal_reduction_v2_full_rank.safetensors Weight: 1.0 (Full-rank Refusal Reduction LoRA for photorealistic documentary alignment)

Get

Field Notes RTX 4070 Benchmark

Benchmark: Rendered on NVIDIA GeForce RTX 4070 (12GB VRAM, CUDA 12.4)

1. ARCHITECTURAL REASONING & NESTED VIEWPORT COMPOSITION: Rendering a coherent smartphone screen with a matching live camera viewfinder inside an AI artwork requires exceptional spatial attention. Krea 2 Turbo combined with the Realistic Snapshot LoRA (weight 1.0) achieves nested composition coherence: rendering the user's hand, phone bezel, screen UI, and the framed background subject with accurate optical depth-of-field. 2. LIGHTING TOPOLOGY & SENSOR DYNAMICS: Direct camera flash lighting is balanced against background warm tungsten spill. Textures on the woven wall textiles, wooden rafters, and ceramic jars exhibit authentic documentary grain without artificial plastic skin smoothing. 3. HARDWARE BENCHMARKS & MEMORY PROFILE: Rendered on NVIDIA GeForce RTX 4070 (12GB VRAM). 10 inference steps at 1248x832 complete in ~46 seconds with peak memory well below 10.5GB.

Frequently Asked Questions FAQ

What GPU and VRAM are required to run Civitai #144099372: Smartphone POV Candid - Night Market Viewfinder & 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 1248x832 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.