/qwen-txt2img

name: qwen-txt2img
description: Build Qwen Image 2512 text-to-image workflows with QwenImageIntegratedKSampler, separate component loading, lightning LoRAs, and fine-tuned model variants
globs:
  - "**/*.json"

Qwen Image 2512 Text-to-Image Workflows

Overview

Qwen Image 2512 is the latest (December 2025) text-to-image model from the Qwen family. It uses a vision-language model (Qwen2.5-VL) as the text encoder and generates high-quality images from natural language prompts. Two workflow approaches:

1. **QwenImageIntegratedKSampler**: All-in-one node (recommended for simplicity) 2. **Separate component loading**: UNETLoader + CLIPLoader + VAELoader + standard KSampler (more flexible)

Models

Standard Components

| Component | Node | Model | Notes | |-----------|------|-------|-------| | **UNET** | `UNETLoader` | `qwen_image_2512_fp8_e4m3fn.safetensors` | FP8, not currently installed — download if needed | | **CLIP** | `CLIPLoader` (type=`qwen_image`) | `qwen_2.5_vl_7b_fp8_scaled.safetensors` | Shared across all Qwen models, in clip/ | | **VAE** | `VAELoader` | `qwen_image_vae.safetensors` | Qwen-specific VAE (242MB) |

Fine-tuned Variants (Installed)

| Model | Path | Focus | |-------|------|-------| | `qwenImageEditRemix_v10` | `diffusion_models/qwenImageEditRemix_v10.safetensors` | General-purpose remix | | `qwenUltimateRealism_v11` | UNETLoader path | Product photography, hyper-realistic | | `copaxTimeless` | UNETLoader path | Ultra-realistic portraits | | `qwnImageEdit_v16Bf16` | UNETLoader path | Abliterated (uncensored) |

Lightning LoRAs

4-Step Lightning (General Qwen / txt2img)

{
  "class_type": "LoraLoaderModelOnly",
  "inputs": {
    "model": ["<unet_node>", 0],
    "lora_name": "Qwen-Image-Lightning-4steps-V1.0.safetensors",
    "strength_model": 1.0
  }
}

**Settings**: steps=4, cfg=1.0, sampler=euler, scheduler=simple, denoise=1.0

8-Step Lightning (Higher Quality)

{
  "class_type": "LoraLoaderModelOnly",
  "inputs": {
    "model": ["<unet_node>", 0],
    "lora_name": "Qwen-Image-Lightning-8steps-V1.0.safetensors",
    "strength_model": 1.0
  }
}

**Settings**: steps=8, cfg=1.0 (or 2.5 for character detail), sampler=euler, scheduler=simple

Sampler Settings

| Preset | Steps | CFG | Sampler | Scheduler | Denoise | LoRA | Notes | |--------|-------|-----|---------|-----------|---------|------|-------| | **Lightning 4-step** | 4 | 1.0 | euler | simple | 1.0 | Lightning-4steps | Fastest, good quality | | **Lightning 8-step** | 8 | 1.0 | euler | simple | 1.0 | Lightning-8steps | Better detail | | **Lightning character** | 8 | 2.5 | euler | simple | 1.0 | Lightning-8steps | Best for portraits | | **Standard** | 50 | 4.0 | euler | simple | 1.0 | none | Official ComfyUI | | **Golden quality** | 50 | 4.5 | euler | simple | 1.0 | none | Community best | | **Character composition** | 30 | 4.0 | euler_ancestral | beta | 1.0 | none | Multi-character scenes | | **CopaxTimeless** | 30 | 4.0 | res_multistep | sgm_uniform | 1.0 | none | Ultra-realistic | | **UltimateRealism** | 30 | 7.5 | euler | simple | 1.0 | none | Product photography |

ModelSamplingAuraFlow

For standard (non-lightning) presets, apply flow matching shift:

{
  "class_type": "ModelSamplingAuraFlow",
  "inputs": { "model": ["<unet_or_lora>", 0], "shift": 3.1 }
}

**Shift=3.1** is the standard value for Qwen Image. Not needed with lightning LoRA (baked into the distillation).

Resolutions

Qwen operates at ~1.6 megapixels natively:

| Aspect | Resolution | Use Case | |--------|-----------|----------| | Square | 1328x1328 | General | | Portrait 3:4 | 1104x1472 | Portraits | | Portrait 2:3 | 1056x1584 | | | Portrait 9:16 | 928x1664 | Phone format | | Landscape 4:3 | 1472x1104 | Landscape scenes | | Landscape 3:2 | 1584x1056 | | | Landscape 16:9 | 1664x928 | Widescreen | | Ultra portrait | 1536x2048 | Tall format | | Video-ready | 832x480 | For WAN 2.2 FLF pipeline |

Approach 1: QwenImageIntegratedKSampler (All-in-One)

The `QwenImageIntegratedKSampler` custom node handles model patching, conditioning, sampling, and output in a single node. Simplest workflow: 4 nodes for model loading + 1 integrated sampler + 1 save.

Node Inputs

Required:
  - model: MODEL (from UNETLoader)
  - clip: CLIP (from CLIPLoader, type=qwen_image)
  - vae: VAE
  - positive_prompt: STRING
  - negative_prompt: STRING
  - generation_mode: "文生图 text-to-image" or "图生图 image-to-image"
  - batch_size: INT (default 1)
  - width: INT (default 0, step 8)
  - height: INT (default 0, step 8)
  - seed: INT
  - steps: INT (default 4)
  - cfg: FLOAT (default 1)
  - sampler_name: euler, dpmpp_2m, etc.
  - scheduler: simple, sgm_uniform, beta, etc.
  - denoise: FLOAT (default 1)

Optional:
  - image1-5: IMAGE (reference images for i2i or multi-ref)
  - latent: LATENT
  - controlnet_data: CONTROL_NET_DATA
  - auraflow_shift: FLOAT (default 3)
  - cfg_norm_strength: FLOAT (default 1)

Outputs:
  [0] IMAGE — generated image
  [1] LATENT — output latent (optional)
  [2] IMAGE — scaled input image (for i2i)

Complete Workflow: Integrated Sampler (Lightning 4-Step)

{
  "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "qwenImageEditRemix_v10.safetensors", "weight_dtype": "default" }},
  "2": { "class_type": "LoraLoaderModelOnly", "inputs": { "model": ["1", 0], "lora_name": "Qwen-Image-Lightning-4steps-V1.0.safetensors", "strength_model": 1.0 }},
  "3": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_2.5_vl_7b_fp8_scaled.safetensors", "type": "qwen_image" }},
  "4": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }},
  "5": { "class_type": "QwenImageIntegratedKSampler", "inputs": {
    "model": ["2", 0],
    "clip": ["3", 0],
    "vae": ["4", 0],
    "positive_prompt": "<detailed natural language prompt>",
    "negative_prompt": "",
    "generation_mode": "文生图 text-to-image",
    "batch_size": 1,
    "wi