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    QWEN Image Edit — High-Res on 12GB - v1.0
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    This is a QWEN Image Edit workflow designed to run large AIO QWEN checkpoints (≈28GB) while still generating high-resolution outputs on 12GB VRAM GPUs.

    The focus here is:

    • Image editing / guided edits

    • Very low step counts

    • Stable results at low CFG

    • Aggressive memory management

    • Clean upscale + post polish

    If you’ve struggled getting QWEN AIO models to behave on smaller cards, this setup is built specifically to solve that.


    Key Features

    • Runs QWEN AIO (GGUF or Safetensors) models on 12GB GPUs

    • Uses Phroots AIO https://huggingface.co/Phr00t/Qwen-Image-Edit-Rapid-AIO (Both NSFW & SFW available)

    • Tested high sampling resolution

    • Works with 1–3 input images for guided edits

    • Extremely low step counts (4–6 steps)

    • CFG-stable at CFG = 1

    • Includes upscaling, resizing, CAS sharpening, and desaturation

    • Cleans GPU memory automatically after runs

    • LoRA-compatible (QWEN-trained LoRAs supported)

    This workflow prioritizes practical generation, not theory — fast previews, predictable edits, and minimal VRAM spikes.


    Required Nodes / Extensions

    Make sure you have all of these installed:

    Core

    • ComfyUI (recent)

    • ComfyUI-GGUF

    • QWEN Image nodes

      • TextEncodeQwenImageEditPlus

      • ClipLoaderGGUF

      • UnetLoaderGGUF

      • VaeGGUF

    Upscaling / Image

    • was-node-suite

    • KJNodes

    • ComfyUI Essentials

    • 4x_foolhardy_Remacri.pth (upscale model)

    Utility / Memory

    • easy-use

      • easy clearCacheAll

      • easy cleanGpuUsed

    If something errors: double-check GGUF + QWEN nodes first — most issues come from mismatched versions.


    These are intentional — higher values usually make QWEN worse, not better.

    Sampler: euler_ancestral
    Scheduler: beta
    Steps: 4–6
    CFG: 1.0
    Denoise: 1.0
    Seed: random or fixed
    

    If you’re coming from SDXL: do not raise CFG. QWEN responds very differently.


    LoRA Notes

    • QWEN-trained style LoRAs do work

    • Load via Model-only LoRA loader

    • Suggested strength range:

      • 0.85 → 1.0

    • Avoid stacking multiple LoRAs unless you know what you’re doing (VRAM spikes fast)


    VRAM & Stability Notes

    • Designed to keep peak VRAM under ~12GB

    • GGUF models strongly recommended for smaller GPUs

    • Cache clearing nodes are intentional — don’t remove them unless you have >24GB VRAM

    • If you OOM:

      • Reduce output resolution slightly

      • Close other GPU apps

      • Avoid second diffusion passes (QWEN doesn’t like them)

    Description

    Base 1.0 workflow

    FAQ

    Workflows
    Qwen

    Details

    Downloads
    276
    Platform
    CivitAI
    Platform Status
    Available
    Created
    2/12/2026
    Updated
    4/28/2026
    Deleted
    -

    Files

    qwenImageEditHighRes_v10.zip

    Mirrors

    CivitAI (1 mirrors)