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 "revision": 0,
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  {
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   "title": "Downloads",
   "properties": {
    "Node name for S&R": "MarkdownNote"
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   "widgets_values": [
    "## Downloads — put each file in the ComfyUI folder shown\n\n**Comfy-Org/Qwen-Image-2.1** — https://huggingface.co/Comfy-Org/Qwen-Image-2.1\n\n| ComfyUI folder | File | Size |\n|---|---|---|\n| `models/diffusion_models/` | [qwen_image_2.1_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/diffusion_models/qwen_image_2.1_int8_convrot.safetensors) | 7.3 GB |\n| `models/text_encoders/` | [qwen3vl_8b_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/text_encoders/qwen3vl_8b_int8_convrot.safetensors) | 9.4 GB |\n| `models/vae/` | [qwen_image_2.1_vae_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/vae/qwen_image_2.1_vae_bf16.safetensors) | 0.68 GB |\n\n**Viggle/Qwen-Image-2.1-viggle-turbo** — only for the TURBO group — https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo\n\n| ComfyUI folder | File | Size |\n|---|---|---|\n| `models/loras/` | [Qwen-Image-2.1-viggle-turbo-v0.2.1-6step-lora-r256.safetensors](https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo/resolve/main/Qwen-Image-2.1-viggle-turbo-v0.2.1-6step-lora-r256.safetensors) | 1.4 GB |\n\n**Needs ComfyUI 0.37 or newer** (native Qwen Image 2.1 + the Comfy Kitchen attention node). **No custom nodes.**\n\nOptional: `qwen_image_2.1_bf16.safetensors` (14.2 GB, same repo) is a drop-in swap for the int8 model. On my RTX 3060 at 2K it measured 6 min 10 s vs 3 min 57 s (25 steps) with 10.6 GB peak system RAM vs 3.0 GB — same-seed images looked the same.\n"
   ],
   "widgets_values_named": {
    "text": "## Downloads — put each file in the ComfyUI folder shown\n\n**Comfy-Org/Qwen-Image-2.1** — https://huggingface.co/Comfy-Org/Qwen-Image-2.1\n\n| ComfyUI folder | File | Size |\n|---|---|---|\n| `models/diffusion_models/` | [qwen_image_2.1_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/diffusion_models/qwen_image_2.1_int8_convrot.safetensors) | 7.3 GB |\n| `models/text_encoders/` | [qwen3vl_8b_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/text_encoders/qwen3vl_8b_int8_convrot.safetensors) | 9.4 GB |\n| `models/vae/` | [qwen_image_2.1_vae_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/vae/qwen_image_2.1_vae_bf16.safetensors) | 0.68 GB |\n\n**Viggle/Qwen-Image-2.1-viggle-turbo** — only for the TURBO group — https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo\n\n| ComfyUI folder | File | Size |\n|---|---|---|\n| `models/loras/` | [Qwen-Image-2.1-viggle-turbo-v0.2.1-6step-lora-r256.safetensors](https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo/resolve/main/Qwen-Image-2.1-viggle-turbo-v0.2.1-6step-lora-r256.safetensors) | 1.4 GB |\n\n**Needs ComfyUI 0.37 or newer** (native Qwen Image 2.1 + the Comfy Kitchen attention node). **No custom nodes.**\n\nOptional: `qwen_image_2.1_bf16.safetensors` (14.2 GB, same repo) is a drop-in swap for the int8 model. On my RTX 3060 at 2K it measured 6 min 10 s vs 3 min 57 s (25 steps) with 10.6 GB peak system RAM vs 3.0 GB — same-seed images looked the same.\n"
   },
   "color": "#432",
   "bgcolor": "#653"
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   "type": "MarkdownNote",
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   "flags": {},
   "order": 3,
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   "outputs": [],
   "title": "How to use · tested on RTX 3060",
   "properties": {
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   "widgets_values": [
    "## How to use\n\n1. **Step 1** — models are set (int8 = best fit for 12 GB).\n2. **Step 2** — size. Default **4 MP = 2048×2048** (Qwen 2.1's native 2K). 1 MP = 1024×1024.\n3. **Step 3** — write your prompt. cfg stays **1** (negative prompt is unused at cfg 1).\n4. **Run.** QUALITY is on; TURBO is bypassed. To switch: click a group title → **Ctrl+B**.\n\n## Tested on RTX 3060 12 GB · Ryzen 5 5600X · 32 GB DDR4 (ComfyUI 0.37.1)\n\n| This workflow, 2048×2048 (Comfy Desktop, SageAttention on) | Time per image |\n|---|---|\n| QUALITY · 40 steps · Comfy Kitchen attention | **4 min 07 s** |\n| TURBO · Viggle 6-step · SageAttention (Desktop default) | **47 s** |\n\nFirst run after starting ComfyUI adds a few seconds for loading (4 min 11 s / 48 s).\n\nFrom my benchmark (2048×2048, same seed): template 25 steps with PyTorch attention **3 min 57 s** ·\nComfy Kitchen attention **2 min 40 s** · SageAttention **3 min 00 s** · bf16 model **6 min 10 s**.\n\n**Why 40 steps:** at 2K the template's 25 steps left the subject faded on one of my test prompts; 40 steps (the official 40–50) fixed it.\n**TURBO:** much faster, but visibly softer fine detail at 2K than the base model.\n**Seeds vary:** of my two test seeds, TURBO double-exposed the player's head on one, and QUALITY printed the date line twice on one. Re-roll the seed if you see that.\n**Don't add Comfy Kitchen attention to TURBO:** with the 6-step LoRA it ghosted the subject in my test — PyTorch and SageAttention were clean.\n**Text encoder:** `qwen3vl_8b_w4a8` runs at the same speed but changes the picture with the same seed — int8 kept.\n"
   ],
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    "text": "## How to use\n\n1. **Step 1** — models are set (int8 = best fit for 12 GB).\n2. **Step 2** — size. Default **4 MP = 2048×2048** (Qwen 2.1's native 2K). 1 MP = 1024×1024.\n3. **Step 3** — write your prompt. cfg stays **1** (negative prompt is unused at cfg 1).\n4. **Run.** QUALITY is on; TURBO is bypassed. To switch: click a group title → **Ctrl+B**.\n\n## Tested on RTX 3060 12 GB · Ryzen 5 5600X · 32 GB DDR4 (ComfyUI 0.37.1)\n\n| This workflow, 2048×2048 (Comfy Desktop, SageAttention on) | Time per image |\n|---|---|\n| QUALITY · 40 steps · Comfy Kitchen attention | **4 min 07 s** |\n| TURBO · Viggle 6-step · SageAttention (Desktop default) | **47 s** |\n\nFirst run after starting ComfyUI adds a few seconds for loading (4 min 11 s / 48 s).\n\nFrom my benchmark (2048×2048, same seed): template 25 steps with PyTorch attention **3 min 57 s** ·\nComfy Kitchen attention **2 min 40 s** · SageAttention **3 min 00 s** · bf16 model **6 min 10 s**.\n\n**Why 40 steps:** at 2K the template's 25 steps left the subject faded on one of my test prompts; 40 steps (the official 40–50) fixed it.\n**TURBO:** much faster, but visibly softer fine detail at 2K than the base model.\n**Seeds vary:** of my two test seeds, TURBO double-exposed the player's head on one, and QUALITY printed the date line twice on one. Re-roll the seed if you see that.\n**Don't add Comfy Kitchen attention to TURBO:** with the 6-step LoRA it ghosted the subject in my test — PyTorch and SageAttention were clean.\n**Text encoder:** `qwen3vl_8b_w4a8` runs at the same speed but changes the picture with the same seed — int8 kept.\n"
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   "outputs": [],
   "title": "TURBO · sigmas for other sizes",
   "properties": {
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   "widgets_values": [
    "## TURBO sigmas depend on the image size\n\nThe Viggle 6-step schedule is shifted by resolution. The ManualSigmas node is set for **2048×2048**.\nIf you change the size in Step 2, paste the matching line into **TURBO sigmas**:\n\n| Size | Pixels | Sigmas |\n|---|---|---|\n| 1:1 · 1 MP | 1024×1024 | `1.000000, 0.967754, 0.933358, 0.857192, 0.666756, 0.400096, 0.000000` |\n| 1:1 · 2K (default) | 2048×2048 | `1.000000, 0.982380, 0.962989, 0.917701, 0.787999, 0.553369, 0.000000` |\n| 16:9 · 1 MP | 1376×768 | `1.000000, 0.967805, 0.933459, 0.857389, 0.667114, 0.400483, 0.000000` |\n| 9:16 · 1 MP | 768×1376 | `1.000000, 0.967805, 0.933459, 0.857389, 0.667114, 0.400483, 0.000000` |\n| 16:9 · 2K area | 2720×1536 | `1.000000, 0.982324, 0.962873, 0.917457, 0.787459, 0.552571, 0.000000` |\n| 9:16 · 2K area | 1536×2720 | `1.000000, 0.982324, 0.962873, 0.917457, 0.787459, 0.552571, 0.000000` |\n| 1:1 · 1536 | 1536×1536 | `1.000000, 0.974905, 0.947724, 0.885970, 0.721439, 0.463316, 0.000000` |\n\nMaths from Viggle's own node: raw nodes 1, 0.9375, 0.875, 0.75, 0.5, 0.25 shifted with mu from (W/16)·(H/16), final 0.\n"
   ],
   "widgets_values_named": {
    "text": "## TURBO sigmas depend on the image size\n\nThe Viggle 6-step schedule is shifted by resolution. The ManualSigmas node is set for **2048×2048**.\nIf you change the size in Step 2, paste the matching line into **TURBO sigmas**:\n\n| Size | Pixels | Sigmas |\n|---|---|---|\n| 1:1 · 1 MP | 1024×1024 | `1.000000, 0.967754, 0.933358, 0.857192, 0.666756, 0.400096, 0.000000` |\n| 1:1 · 2K (default) | 2048×2048 | `1.000000, 0.982380, 0.962989, 0.917701, 0.787999, 0.553369, 0.000000` |\n| 16:9 · 1 MP | 1376×768 | `1.000000, 0.967805, 0.933459, 0.857389, 0.667114, 0.400483, 0.000000` |\n| 9:16 · 1 MP | 768×1376 | `1.000000, 0.967805, 0.933459, 0.857389, 0.667114, 0.400483, 0.000000` |\n| 16:9 · 2K area | 2720×1536 | `1.000000, 0.982324, 0.962873, 0.917457, 0.787459, 0.552571, 0.000000` |\n| 9:16 · 2K area | 1536×2720 | `1.000000, 0.982324, 0.962873, 0.917457, 0.787459, 0.552571, 0.000000` |\n| 1:1 · 1536 | 1536×1536 | `1.000000, 0.974905, 0.947724, 0.885970, 0.721439, 0.463316, 0.000000` |\n\nMaths from Viggle's own node: raw nodes 1, 0.9375, 0.875, 0.75, 0.5, 0.25 shifted with mu from (W/16)·(H/16), final 0.\n"
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     "name": "noise_seed_25",
     "type": "INT",
     "widget": {
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   "title": "Qwen Image 2.1 (12 GB)",
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