qwen-image-edit-2509をlow VRAM の PC で どうにか動かしてみる ComfyUI
はじめに
qwen-image-edit-2509を低い 性能の PCで動作させるのを目標にします
UnetLoaderGGUFAdvancedDisTorch2MultiGPUを使うことでvRAMが6gb でも動くように試みます
モデル
📁 ComfyUI ディレクトリ構成（モデル関連）
ComfyUI/
├── models/
│ ├── vae/
│ │ └── qwen_image_vae.safetensors
│ ├── loras/
│ │ └── Qwen-Image-Lightning-4steps-V1.0-bf16.safetensors
│ ├── unet/
│ │ └── Qwen-Image-Edit-2509-Q4_K_M.gguf
│ ├── text_encoders/
│ │ └── Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf
│ │ └── Qwen2.5-VL-7B-Instruct-mmproj-BF16.gguf
🧠 モデル使用ノードと対応ファイル
| ノード名 | モデルファイル名 | モデルタイプ | モデルパス例 |
|---|---|---|---|
VAELoader | qwen_image_vae.safetensors | VAE | models/vae/ |
LoraLoaderModelOnly | Qwen-Image-Lightning-4steps-V1.0-bf16.safetensors | LoRA | models/loras/ |
UnetLoaderGGUFAdvanced... | Qwen-Image-Edit-2509-Q4_K_M.gguf | UNet | models/unet/ |
CLIPLoaderGGUFDisTorch2... | Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf | Text Encoder | models/text_encoders/ |
フロー
🌊 モデルの流れ（ノード接続順）
1. CLIPLoaderGGUFDisTorch2MultiGPU
└─ Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf（Text Encoder）
├─→ TextEncodeQwenImageEditPlus（2つ）
├─ image1, image2, image3（LoadImage → ImageScale）
└─ prompt（テキスト指示）
└─→ CONDITIONING（ポジティブ／ネガティブ）
2. VAELoader
└─ qwen_image_vae.safetensors（VAE）
├─→ TextEncodeQwenImageEditPlus（画像サイズ調整用）
├─→ VAEEncode（画像 → 潜在変換）
└─→ VAEDecode（潜在 → 画像復元）
3. LoadImage ×3
└─ 画像を読み込み → ImageScale（512×512に統一）
4. VAEEncode
└─ 入力画像を潜在空間に変換 → latent_image
5. UnetLoaderGGUFAdvancedDisTorch2MultiGPU
└─ Qwen-Image-Edit-2509-Q4_K_M.gguf（UNet）
6. LoraLoaderModelOnly
└─ Qwen-Image-Lightning-4steps-V1.0-bf16.safetensors（LoRA）
└─ モデルに適用 → ModelSamplingAuraFlow
7. ModelSamplingAuraFlow
└─ shift=3 → CFGNorm
8. CFGNorm
└─ strength=1 → KSampler
9. KSampler
├─ model（CFG済み）
├─ conditioning（TextEncodeから）
├─ latent_image（VAEEncodeから）
└─ steps=4, cfg=1 , sampler=euler → 潜在画像生成
10. VAEDecode
└─ 潜在画像 → 最終画像
11. SaveImage
└─ 出力画像保存！
この流れで、画像3枚＋テキスト指示から編集された新しい画像が生成
プロンプト
image 1 lie on the sofa , and image 3 Sitting on a chair, and let image 2 lie on the floor.ワークフロー
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