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Update workflow examples to match Comfy Core guidelines

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John Pollock
2025-10-13 01:52:20 -05:00
parent 161174266c
commit 01b41f4514
46 changed files with 8182 additions and 14615 deletions
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example_workflows/ComfyUI-Florence2 detailed_caption to flux.jpg
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example_workflows/ComfyUI-Florence2 detailed_caption to flux.json
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example_workflows/ComfyUI-GGUF flux unet dual_clip loaders.jpg
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example_workflows/distorch2/flux_dev_DisTorch2.json → example_workflows/ComfyUI-GGUF flux unet dual_clip loaders.json
+443 -261
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@@ -1,22 +1,97 @@
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"A towering technological monolith in a cyberpunk cityscape at night, with \"GGUF\" emblazoned across its surface in massive neon blue-green mixed with purple letters that illuminate the surrounding buildings. The text occupies the central third of the frame, crafted from glowing plasma tubes and crackling energy. Rain-slicked streets below reflect the brilliant signage, while holographic advertisements and flying vehicles populate the background. Moody atmospheric lighting, heavy contrast, photorealistic textures, cinematic color grading. "
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"A standard FLUX.dev workflow with GGUF UNet and CLIP to test ComfyUI-GGUF integration. In this case we are using standard MultiGPU-wrapped nodes to move model components to their own device.\n## Custom Node\n- [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF)\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-GGUF/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [flux1-dev-Q4_K_S.gguf](https://huggingface.co/city96/FLUX.1-dev-gguf/resolve/main/flux1-dev-Q4_K_S.gguf)\n\n**CLIP**\n- [t5-v1_1-xxl-encoder-Q4_K_S.gguf](https://huggingface.co/city96/t5-v1_1-xxl-encoder-gguf/resolve/main/t5-v1_1-xxl-encoder-Q4_K_S.gguf)\n- [clip_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors)\n\n**VAE**\n- [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/ae.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── t5-v1_1-xxl-encoder-Q4_K_S.gguf\n│ │ └── clip_l.safetensors\n│ ├── 📂 unet/\n│ │ ├── flux1-dev-Q4_K_S.gguf\n│ ├── 📂 vae/\n│ │ └── ae.safetensors]\n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── flux1-dev-Q4_K_S.gguf\n├── 🟣 cuda:1\n│ └── ae.safetensors\n├── ⚙️ cpu\n └── t5-v1_1-xxl-encoder-Q4_K_S.gguf\n └── clip_l.safetensors\n```"
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example_workflows/distorch2/qwen_image_basic_DisTorch2.json → example_workflows/ComfyUI-GGUF qwen_image unet distorch2 cliploader.json
+314 -315
View File
@@ -1,153 +1,9 @@
{
"id": "91f6bbe2-ed41-4fd6-bac7-71d5b5864ecb",
"revision": 0,
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"last_link_id": 134,
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{
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"type": "IMAGE",
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"links": [
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]
}
],
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"properties": {
"Node name for S&R": "SaveImage"
},
"widgets_values": [
"ComfyUI"
]
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}
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"Node name for S&R": "EmptySD3LatentImage"
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],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
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]
}
],
"title": "CLIP Text Encode (Negative Prompt)",
"properties": {
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
" "
],
"color": "#322",
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"type": "KSampler",
@@ -160,7 +16,7 @@
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{
@@ -195,10 +51,12 @@
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],
"properties": {
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"ver": "0.3.64",
"Node name for S&R": "KSampler"
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"randomize",
20,
2.5,
@@ -208,87 +66,117 @@
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"id": 66,
"type": "ModelSamplingAuraFlow",
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"name": "MODEL",
"type": "MODEL",
"links": [
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]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.64",
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"name": "CLIP",
"type": "CLIP",
"links": [
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]
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"properties": {
"cnr_id": "comfyui-multigpu",
"ver": "0d6dfc7524472943ba912a6ec3088757edba15c3",
"Node name for S&R": "CLIPLoaderGGUFMultiGPU"
},
"widgets_values": [
"Qwen2.5-VL-7B-Instruct-Q4_K_S.gguf",
"qwen_image",
"cuda:1"
],
"color": "#008181",
"bgcolor": "rgba(24,24,27,.9)"
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"name": "CLIP",
"type": "CLIP",
"slot_index": 0,
"name": "VAE",
"type": "VAE",
"links": [
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]
}
],
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"Node name for S&R": "CLIPLoader"
"cnr_id": "comfyui-multigpu",
"ver": "0d6dfc7524472943ba912a6ec3088757edba15c3",
"Node name for S&R": "VAELoaderMultiGPU"
},
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"qwen_2.5_vl_7b_fp8_scaled.safetensors",
"qwen_image",
"cpu"
"qwen_image_vae.safetensors",
"cuda:1"
],
"color": "#223",
"bgcolor": "#335"
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"Increase the shift if you get too many blury/dark/bad images. Decrease if you want to try increasing detail."
],
"color": "#432",
"bgcolor": "#653"
},
{
"id": 67,
"type": "Note",
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],
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"Set cfg to 1.0 for a speed boost at the cost of consistency. Samplers like res_multistep work pretty well at cfg 1.0\n\nThe official number of steps is 50 but I think that's too much. Even just 10 steps seems to work."
],
"color": "#432",
"bgcolor": "#653"
"color": "#008181",
"bgcolor": "rgba(24,24,27,.9)"
},
{
"id": 6,
@@ -308,7 +196,7 @@
{
"name": "clip",
"type": "CLIP",
"link": 74
"link": 136
}
],
"outputs": [
@@ -323,122 +211,233 @@
],
"title": "CLIP Text Encode (Positive Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.64",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
"A towering technological monolith in a cyberpunk cityscape at night, with \"DisTorch 2\" emblazoned across its surface in massive neon blue-green mixed with purple letters that illuminate the surrounding buildings. The text occupies the central third of the frame, crafted from glowing plasma tubes and crackling energy. \"now with .safetensors!\" in same styling but smaller, italic version of the font splashed in the lower right-hand corner of the image. Rain-slicked streets below reflect the brilliant signage, while holographic advertisements and flying vehicles populate the background. Moody atmospheric lighting, heavy contrast, photorealistic textures, cinematic color grading. "
"A towering technological monolith in a cyberpunk cityscape at night, with \"GGUF DisTorch 2\" emblazoned across its surface in massive neon blue-green mixed with purple letters that illuminate the surrounding buildings. The text occupies the central third of the frame, crafted from glowing plasma tubes and crackling energy. Rain-slicked streets below reflect the brilliant signage, while holographic advertisements and flying vehicles populate the background. Moody atmospheric lighting, heavy contrast, photorealistic textures, cinematic color grading. "
],
"color": "#232",
"bgcolor": "#353"
},
{
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"type": "VAELoaderMultiGPU",
"id": 8,
"type": "VAEDecode",
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"name": "samples",
"type": "LATENT",
"link": 128
},
{
"name": "vae",
"type": "VAE",
"link": 130
}
],
"outputs": [
{
"name": "IMAGE",
"type": "IMAGE",
"slot_index": 0,
"links": [
110
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.64",
"Node name for S&R": "VAEDecode"
},
"widgets_values": []
},
{
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"type": "CLIPTextEncode",
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],
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},
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"mode": 0,
"inputs": [
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"type": "CLIP",
"link": 135
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
52
]
}
],
"title": "CLIP Text Encode (Negative Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.64",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
" "
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"color": "#322",
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"type": "LATENT",
"links": [
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]
}
],
"properties": {
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"ver": "0.3.64",
"Node name for S&R": "EmptySD3LatentImage"
},
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},
{
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"type": "UnetLoaderGGUFDisTorch2MultiGPU",
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],
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],
"properties": {
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"ver": "0d6dfc7524472943ba912a6ec3088757edba15c3",
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{
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"type": "MarkdownNote",
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"mode": 0,
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{
"name": "VAE",
"type": "VAE",
"links": [
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]
}
],
"properties": {
"Node name for S&R": "VAELoaderMultiGPU"
},
"outputs": [],
"title": "ComfyUI-MultiGPU Note - ComfyUI-GGUF UNETDisTorch2Loader, DualClipLoader Workflow",
"properties": {},
"widgets_values": [
"qwen_image_vae.safetensors",
"cuda:1"
"A DisTorch2 FLUX.dev workflow with GGUF UNet DisTorch2 and CLIP to test ComfyUI-GGUF integration. In this case we are using the DisTorch2 node to statically allocate approximately half of the main UNet model to the cpu.\n\n## Custom Node\n- [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF)\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-GGUF/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [qwen-image-Q3_K_S.gguf](https://huggingface.co/city96/Qwen-Image-gguf/resolve/main/qwen-image-Q3_K_S.gguf)\n\n**CLIP**\n- [Qwen2.5-VL-7B-Instruct-Q4_K_S.gguf](https://huggingface.co/unsloth/Qwen2.5-VL-7B-Instruct-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-Q4_K_S.gguf)\n\n**VAE**\n- [qwen_image_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/blob/main/split_files/vae/qwen_image_vae.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── Qwen2.5-VL-7B-Instruct-Q4_K_S.gguf\n│ ├── 📂 unet/\n│ │ ├── qwen-image-Q3_K_S.gguf [🟩🟩🟩🟩🟩⚙️⚙️⚙️⚙️⚙️]\n│ ├── 📂 vae/\n│ │ └── qwen_image_vae.safetensors\n```\n\n```\n🖥️ Device Mapping\n├── 🟢 cuda:0\n│ └── qwen-image-Q3_K_S.gguf [🟩🟩🟩🟩🟩]\n├── 🟣 cuda:1\n│ └── Qwen2.5-VL-7B-Instruct-Q4_K_S.gguf\n│ └── qwen_image_vae.safetensors\n├── ⚙️ cpu\n│ └── qwen-image-Q3_K_S.gguf [⚙️⚙️⚙️⚙️⚙️]\n\n```"
],
"color": "#233",
"bgcolor": "#355"
"color": "#008181",
"bgcolor": "rgba(24,24,27,.9)"
},
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"type": "ModelSamplingAuraFlow",
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"type": "SaveImage",
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"mode": 0,
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"type": "MODEL",
"link": 134
}
],
"outputs": [
{
"name": "MODEL",
"type": "MODEL",
"links": [
125
]
"name": "images",
"type": "IMAGE",
"link": 110
}
],
"outputs": [],
"properties": {
"Node name for S&R": "ModelSamplingAuraFlow"
"cnr_id": "comfy-core",
"ver": "0.3.64",
"Node name for S&R": "SaveImage"
},
"widgets_values": [
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"MultiGPU"
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"widgets_values": [
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""
],
"color": "#233",
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}
],
"links": [
@@ -458,22 +457,6 @@
2,
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@@ -527,13 +526,13 @@
"config": {},
"extra": {
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"scale": 0.9229599817706498,
"scale": 0.7627768444385551,
"offset": [
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},
"frontendVersion": "1.24.4",
"frontendVersion": "1.27.10",
"VHS_latentpreview": false,
"VHS_latentpreviewrate": 0,
"VHS_MetadataImage": true,
example_workflows/ComfyUI-WanVideoWrapper wanvideo2_2 I2V A14B GGUF.jpg
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example_workflows/wannvideowrapper/wanvideo2_2_I2V_A14B_example_WIP_Multigpu.json → example_workflows/ComfyUI-WanVideoWrapper wanvideo2_2 I2V A14B GGUF.json
+679 -913
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example_workflows/ComfyUI-WanVideoWrapper wanvideo_1_3B control_lora.jpg
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example_workflows/wannvideowrapper/wanvideo_1_3B_control_lora_example_01_MultiGPU.json → example_workflows/ComfyUI-WanVideoWrapper wanvideo_1_3B control_lora.json
+473 -581
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example_workflows/ComfyUI-WanVideoWrapper wanvideo_1_3B control_lora.webm
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example_workflows/wannvideowrapper/wanvideo_T2V_example_MultiGPU.json → example_workflows/ComfyUI-WanVideoWrapper wanvideo_T2V.json
+373 -562
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example_workflows/distorch/flux1dev_gguf_distorch.json
-597
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@@ -1,597 +0,0 @@
{
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{
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],
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{
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{
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{
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],
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example_workflows/florence2/florence2_flux1dev_ltxv_cpu_2gpu.json
-4182
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example_workflows/multiGPU/flux_dev_example_MultiGPU.json → example_workflows/flux unet dual_clip vae loaders.json
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example_workflows/gguf/flux1dev_2gpu_gguf.json
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example_workflows/gguf/hunyuan_cpu_1gpu_gguf.json
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example_workflows/hunyuanvideo distorch DEPRECATED.jpg
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example_workflows/distorch2/hunyuan_gguf_DisTorch2.json → example_workflows/hunyuanvideo distorch DEPRECATED.json
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@@ -408,92 +281,18 @@
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"title": "ComfyUI-MultiGPU Note - THIS WORKFLOW IS DEPRECATED. USE DISTORCH2 NODES",
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"widgets_values": [
"###THIS WORKFLOW IS DEPRECATED. USE DISTORCH2 NODES\n\nA DisTorch Hunyuan Video workflow with GGUF UNet DisTorch to test Hunyuan Video integration. In this case we are using the DisTorch2 node to statically allocate approximately half of the main UNet model to the cpu.\n\n## Custom Node\n- [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF)\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-GGUF/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [fast-hunyuan-video-t2v-720p-Q4_K_M.gguf](https://huggingface.co/city96/FastHunyuan-gguf/resolve/main/fast-hunyuan-video-t2v-720p-Q4_K_M.gguf)\n\n**CLIP**\n- [llava-llama-3-8B-v1_1-Q4_K_M.gguf](https://huggingface.co/city96/llava-llama-3-8b-v1_1-imat-gguf/resolve/main/llava-llama-3-8B-v1_1-Q4_K_M.gguf)\n\n**VAE**\n- [hunyuan_video_vae_bf16.safetensors](https://huggingface.co/Kijai/HunyuanVideo_comfy/resolve/main/hunyuan_video_vae_bf16.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── llava-llama-3-8B-v1_1-Q4_K_M.gguf\n│ │ └── clip_l.safetensors\n│ ├── 📂 unet/\n│ │ ├── fast-hunyuan-video-t2v-720p-Q4_K_M.gguf [🟩🟩🟩🟩🟪🟪🟪🟪🟪🟪]\n│ ├── 📂 vae/\n│ │ └── hunyuan_video_vae_bf16.safetensors\n```\n\n```\n🖥️ Device Mapping\n├── 🟢 cuda:0\n│ └── fast-hunyuan-video-t2v-720p-Q4_K_M.gguf [🟩🟩🟩🟩]\n├── 🟣 cuda:1\n│ └── fast-hunyuan-video-t2v-720p-Q4_K_M.gguf [🟪🟪🟪🟪🟪🟪]\n│ └── qwen_image_vae.safetensors\n├── ⚙️ cpu\n └── llava-llama-3-8B-v1_1-Q4_K_M.gguf\n └── clip_l.safetensors\n```"
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example_workflows/distorch2/ltxv_text_to_video_MultiGPU.json → example_workflows/ltxvideo checkpointloadersimple distorch2.json
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example_workflows/distorch2/default_advanced_DisTorch2.json → example_workflows/mochi checkpointloaderadvanced distorch2.json
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example_workflows/qwen_image unet clip distorch2.json
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example_workflows/sd15 checkpoint loader simple.jpg
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example_workflows/distorch2/default_simple_DisTorch2.json → example_workflows/sd15 checkpoint loader simple.json
+307 -259
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example_workflows/sdxl checkpoint loader advanced.jpg
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example_workflows/sdxl checkpoint loader advanced.json
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example_workflows/wan2_2 distorch2 double_unet no_cpu.jpg
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example_workflows/distorch2/wan2_2_DisTorch2.json → example_workflows/wan2_2 distorch2 double_unet no_cpu.json
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"A DisTorch2 Wan 2.2 workflow where we ignore CPU offloading completely and load both UNets placing blocks on the CPU and CLIP DisTorch2. In this case we are using the DisTorch2 node to statically allocate approximately 70% of the UNet model (13.3G) to the cpu. With `eject_models` being `True`, all other models on the `compute` card (`cuda:0`) will be unloaded, regardless of size, ensuring a clean compute card prior to inference.\n\n## Custom Node\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors)\n- [wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors)\n\n**CLIP**\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)\n\n**VAE**\n- [wan_2.1_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 unet/\n│ │ ├── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ ├── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├── 📂 vae/\n│ │ └── qwen_image_vae.safetensors \n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n├── 🟣 cuda:1\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ └── wan_2.1_vae.safetensors\n├── ⚙️ cpu\n```"
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example_workflows/wan2_2 t2v lightx2v lora distorch2.json
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"A DisTorch2 Wan 2.2 workflow where we eschew our other `gpu`, offloading both UNets by placing blocks on the `cpu`. In this case we are using the DisTorch2 node to statically allocate approximately 70% of the UNet model (13.3G) to the `cpu`, along with a proportional amount of the LoRAs patched to the model. With `eject_models` being `True`, all other models on the `compute` card (`cuda:0`) will be unloaded, regardless of size, ensuring a clean compute card prior to inference.\n\n## Custom Node\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors)\n- [wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors)\n\n**CLIP**\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)\n\n**VAE**\n- [wan_2.1_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors)\n\n**LoRA**\n- [high_noise_model.safetensors](https://huggingface.co/lightx2v/Wan2.2-Lightning/resolve/main/Wan2.2-T2V-A14B-4steps-lora-rank64-Seko-V1.1/high_noise_model.safetensors)\n- [low_noise_model.safetensors](https://huggingface.co/lightx2v/Wan2.2-Lightning/resolve/main/Wan2.2-T2V-A14B-4steps-lora-rank64-Seko-V1.1/low_noise_model.safetensors)\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 unet/\n│ │ ├── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ ├── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├───📂 loras/\n│ ├─────📂 Wan2.2-T2V-A14B-4steps-lora-rank64-Seko-V1.1/\n│ │ ├────── high_noise_model.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ └────── low_noise_model.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├── 📂 vae/\n│ │ └── qwen_image_vae.safetensors \n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── high_noise_model.safetensors [🟩🟩🟩]\n│ └── low_noise_model.safetensors [🟩🟩🟩]\n│ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ └── wan_2.1_vae.safetensors\n├── 🟣 cuda:1\n│ └── EMPTY\n├── ⚙️ cpu\n └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n └── high_noise_model.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n └── low_noise_model.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n```"
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"A DisTorch2 Wan 2.2 workflow where we ignore CPU offloading completely and load both UNets placing blocks on the CPU and CLIP DisTorch2. In this case we are using the DisTorch2 node to statically allocate approximately 70% of the UNet model (13.3G) to the cpu. With `eject_models` being `True`, all other models on the `compute` card (`cuda:0`) will be unloaded, regardless of size, ensuring a clean compute card prior to inference.\n\n## Custom Node\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors)\n- [wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors)\n\n**CLIP**\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)\n\n**VAE**\n- [wan_2.1_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 unet/\n│ │ ├── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ ├── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├── 📂 vae/\n│ │ └── qwen_image_vae.safetensors \n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n├── 🟣 cuda:1\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ └── wan_2.1_vae.safetensors\n├── ⚙️ cpu\n```"
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