{ "id": "e3f2b845-8f2c-4b5a-9caf-eac1029d3e7e", "revision": 0, "last_node_id": 158, "last_link_id": 360, "nodes": [ { "id": 120, "type": "GetImageSize", "pos": [ -1099.018553963862, 5000.292830066376 ], "size": [ 230, 80 ], "flags": {}, "order": 8, "mode": 2, "inputs": [ { "name": "image", "type": "IMAGE", "link": 228 } ], "outputs": [ { "name": "width", "type": "INT", "links": null }, { "name": "height", "type": "INT", "links": null }, { "name": "batch_size", "type": "INT", "links": null } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "GetImageSize", "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } } }, { "id": 119, "type": "ImageScaleToTotalPixels", "pos": [ -1129.018553963862, 4800.292830066376 ], "size": [ 280, 150 ], "flags": {}, "order": 0, "mode": 2, "showAdvanced": true, "inputs": [ { "name": "image", "type": "IMAGE", "link": null } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 228 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "ImageScaleToTotalPixels", "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "nearest-exact", 1, 32 ], "widgets_values_named": { "upscale_method": "nearest-exact", "megapixels": 1, "resolution_steps": 32 } }, { "id": 116, "type": "MarkdownNote", "pos": [ -1937.753202556722, 4826.947863702127 ], "size": [ 450, 630 ], "flags": {}, "order": 1, "mode": 0, "inputs": [], "outputs": [], "title": "Note: MiniMax H3", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "## MiniMax H3 - Video DeltaNet (VDN) Hybrid Attention\n\nThis workflow runs **Video DeltaNet (VDN)** hybrid attention on MiniMax H3 via the ApplyVDNH3 node. VDN replaces most of H3's heavy softmax attention with a hybrid design \u2014 a sliding-window softmax branch for local detail plus a linear-attention branch for long-range context \u2014 that scales **linearly with clip length instead of quadratically**. The upshot: the longer and higher-res your clip, the more VDN helps.\n\n**Honest expectations:** this is an experimental PyTorch port of VDN for ComfyUI (by Saganaki22). The headline \"75-90x / faster-than-playback\" figures are from the official release on 8x B200 datacenter GPUs, not consumer hardware. On a normal GPU this runs an extra linear branch on every block, so it needs solid VRAM \u2014 it shines on long/high-res clips, not short ones. If you're VRAM-limited, the fused turbo or standard turbo workflows are the lighter choice.\n\nVDN node by **Saganaki22**: https://github.com/Saganaki22/ComfyUI-VDN-H3\nVDN model/research by **OpenVDN**: https://huggingface.co/OpenVDN/vdn-minimax-h3\n\n### Key inputs\n- **first_frame / last_frame**: optional keyframes\n- **vdn_checkpoint**: the VDN adapter (see download below)\n- **prompt**: shot, motion, and audio in one block\n- **width/height**: Resolution Selector (768px short edge, multiple of 32)" ], "widgets_values_named": { "text": "## MiniMax H3 - Video DeltaNet (VDN) Hybrid Attention\n\nThis workflow runs **Video DeltaNet (VDN)** hybrid attention on MiniMax H3 via the ApplyVDNH3 node. VDN replaces most of H3's heavy softmax attention with a hybrid design \u2014 a sliding-window softmax branch for local detail plus a linear-attention branch for long-range context \u2014 that scales **linearly with clip length instead of quadratically**. The upshot: the longer and higher-res your clip, the more VDN helps.\n\n**Honest expectations:** this is an experimental PyTorch port of VDN for ComfyUI (by Saganaki22). The headline \"75-90x / faster-than-playback\" figures are from the official release on 8x B200 datacenter GPUs, not consumer hardware. On a normal GPU this runs an extra linear branch on every block, so it needs solid VRAM \u2014 it shines on long/high-res clips, not short ones. If you're VRAM-limited, the fused turbo or standard turbo workflows are the lighter choice.\n\nVDN node by **Saganaki22**: https://github.com/Saganaki22/ComfyUI-VDN-H3\nVDN model/research by **OpenVDN**: https://huggingface.co/OpenVDN/vdn-minimax-h3\n\n### Key inputs\n- **first_frame / last_frame**: optional keyframes\n- **vdn_checkpoint**: the VDN adapter (see download below)\n- **prompt**: shot, motion, and audio in one block\n- **width/height**: Resolution Selector (768px short edge, multiple of 32)" }, "color": "#222", "bgcolor": "#000" }, { "id": 118, "type": "MarkdownNote", "pos": [ -1469.8176099999998, 4841.275115972465 ], "size": [ 300, 520 ], "flags": {}, "order": 2, "mode": 0, "inputs": [], "outputs": [], "title": "Note: Size Settings Reference", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "## MiniMax H3 - Video DeltaNet (VDN) Hybrid Attention\n\nThis workflow runs **Video DeltaNet (VDN)** hybrid attention on MiniMax H3 via the ApplyVDNH3 node. VDN replaces most of H3's heavy softmax attention with a hybrid design \u2014 a sliding-window softmax branch for local detail plus a linear-attention branch for long-range context \u2014 that scales **linearly with clip length instead of quadratically**. The upshot: the longer and higher-res your clip, the more VDN helps.\n\n**Honest expectations:** this is an experimental PyTorch port of VDN for ComfyUI (by Saganaki22). The headline \"75-90x / faster-than-playback\" figures are from the official release on 8x B200 datacenter GPUs, not consumer hardware. On a normal GPU this runs an extra linear branch on every block, so it needs solid VRAM \u2014 it shines on long/high-res clips, not short ones. If you're VRAM-limited, the fused turbo or standard turbo workflows are the lighter choice.\n\nVDN node by **Saganaki22**: https://github.com/Saganaki22/ComfyUI-VDN-H3\nVDN model/research by **OpenVDN**: https://huggingface.co/OpenVDN/vdn-minimax-h3\n\n### Key inputs\n- **first_frame / last_frame**: optional keyframes\n- **vdn_checkpoint**: the VDN adapter (see download below)\n- **prompt**: shot, motion, and audio in one block\n- **width/height**: Resolution Selector (768px short edge, multiple of 32)" ], "widgets_values_named": { "text": "## MiniMax H3 - Video DeltaNet (VDN) Hybrid Attention\n\nThis workflow runs **Video DeltaNet (VDN)** hybrid attention on MiniMax H3 via the ApplyVDNH3 node. VDN replaces most of H3's heavy softmax attention with a hybrid design \u2014 a sliding-window softmax branch for local detail plus a linear-attention branch for long-range context \u2014 that scales **linearly with clip length instead of quadratically**. The upshot: the longer and higher-res your clip, the more VDN helps.\n\n**Honest expectations:** this is an experimental PyTorch port of VDN for ComfyUI (by Saganaki22). The headline \"75-90x / faster-than-playback\" figures are from the official release on 8x B200 datacenter GPUs, not consumer hardware. On a normal GPU this runs an extra linear branch on every block, so it needs solid VRAM \u2014 it shines on long/high-res clips, not short ones. If you're VRAM-limited, the fused turbo or standard turbo workflows are the lighter choice.\n\nVDN node by **Saganaki22**: https://github.com/Saganaki22/ComfyUI-VDN-H3\nVDN model/research by **OpenVDN**: https://huggingface.co/OpenVDN/vdn-minimax-h3\n\n### Key inputs\n- **first_frame / last_frame**: optional keyframes\n- **vdn_checkpoint**: the VDN adapter (see download below)\n- **prompt**: shot, motion, and audio in one block\n- **width/height**: Resolution Selector (768px short edge, multiple of 32)" }, "color": "#222", "bgcolor": "#000" }, { "id": 117, "type": "MarkdownNote", "pos": [ -2400.6044920767217, 4827.101773378694 ], "size": [ 440, 680 ], "flags": {}, "order": 3, "mode": 0, "inputs": [], "outputs": [], "title": "Note: Model Links", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "## Model Links\n\n**Base H3 models** (from Comfy-Org/MiniMax-H3):\n- diffusion_models/ -> minimax_h3_ref2va_pruned_int8_convrot.safetensors -> ComfyUI/models/unet/\n- text_encoders/ -> qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors -> ComfyUI/models/clip/\n- vae/ -> minimax_h3_video_vae_fp16.safetensors + minimax_h3_audio_vae_fp32.safetensors -> ComfyUI/models/vae/\n\n**VDN checkpoint** (by OpenVDN) -> ComfyUI/models/vdn/\nDownload with the Hugging Face CLI (grabs the specific split checkpoint):\n`hf download OpenVDN/vdn-minimax-h3 --include \"stage-dmd-step-250/*\" --local-dir models/vdn`\n\nSet the CLIPLoader type to krea2. VDN node: Saganaki22/ComfyUI-VDN-H3." ], "widgets_values_named": { "text": "## Model Links\n\n**Base H3 models** (from Comfy-Org/MiniMax-H3):\n- diffusion_models/ -> minimax_h3_ref2va_pruned_int8_convrot.safetensors -> ComfyUI/models/unet/\n- text_encoders/ -> qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors -> ComfyUI/models/clip/\n- vae/ -> minimax_h3_video_vae_fp16.safetensors + minimax_h3_audio_vae_fp32.safetensors -> ComfyUI/models/vae/\n\n**VDN checkpoint** (by OpenVDN) -> ComfyUI/models/vdn/\nDownload with the Hugging Face CLI (grabs the specific split checkpoint):\n`hf download OpenVDN/vdn-minimax-h3 --include \"stage-dmd-step-250/*\" --local-dir models/vdn`\n\nSet the CLIPLoader type to krea2. VDN node: Saganaki22/ComfyUI-VDN-H3." }, "color": "#222", "bgcolor": "#000" }, { "id": 147, "type": "LoadImage", "pos": [ -1687.6417120505473, 5549.891954719866 ], "size": [ 504.2327968929999, 384.7734401360003 ], "flags": {}, "order": 4, "mode": 2, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 324 ] }, { "name": "MASK", "type": "MASK", "links": null } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "LoadImage", "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "1024834.jpg", "image" ], "widgets_values_named": { "image": "1024834.jpg", "upload": "image" } }, { "id": 148, "type": "ImageResizeKJv2", "pos": [ -1155.840188910504, 5558.496268691281 ], "size": [ 270, 336.00000000000045 ], "flags": {}, "order": 10, "mode": 2, "inputs": [ { "label": "image", "name": "image", "type": "IMAGE", "link": 324 }, { "label": "mask", "name": "mask", "shape": 7, "type": "MASK", "link": null }, { "label": "width", "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 325 }, { "label": "height", "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 326 }, { "label": "upscale_method", "name": "upscale_method", "type": "COMBO", "widget": { "name": "upscale_method" }, "link": null }, { "label": "keep_proportion", "name": "keep_proportion", "type": "COMBO", "widget": { "name": "keep_proportion" }, "link": null }, { "label": "pad_color", "name": "pad_color", "type": "STRING", "widget": { "name": "pad_color" }, "link": null }, { "label": "crop_position", "name": "crop_position", "type": "COMBO", "widget": { "name": "crop_position" }, "link": null }, { "label": "divisible_by", "name": "divisible_by", "type": "INT", "widget": { "name": "divisible_by" }, "link": null }, { "label": "device", "name": "device", "shape": 7, "type": "COMBO", "widget": { "name": "device" }, "link": null } ], "outputs": [ { "label": "IMAGE", "name": "IMAGE", "type": "IMAGE", "links": [ 327 ] }, { "label": "width", "name": "width", "type": "INT", "links": null }, { "label": "height", "name": "height", "type": "INT", "links": null }, { "label": "mask", "name": "mask", "type": "MASK", "links": null } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "79f529a84a8c20fe5dcdfa984c6be7a94102c014", "Node name for S&R": "ImageResizeKJv2", "ue_properties": { "widget_ue_connectable": { "width": true, "height": true, "upscale_method": true, "keep_proportion": true, "pad_color": true, "crop_position": true, "divisible_by": true, "device": true }, "version": "7.5.2", "input_ue_unconnectable": {} } }, "widgets_values": [ 480, 640, "lanczos", "crop", "0, 0, 0", "center", 32, "cpu" ], "widgets_values_named": { "width": 480, "height": 640, "upscale_method": "lanczos", "keep_proportion": "crop", "pad_color": "0, 0, 0", "crop_position": "center", "divisible_by": 32, "device": "cpu" } }, { "id": 142, "type": "ImageResizeKJv2", "pos": [ -1142.2429809462835, 5977.983385796561 ], "size": [ 270, 336.0000000000001 ], "flags": {}, "order": 9, "mode": 2, "inputs": [ { "label": "image", "name": "image", "type": "IMAGE", "link": 323 }, { "label": "mask", "name": "mask", "shape": 7, "type": "MASK", "link": null }, { "label": "width", "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 321 }, { "label": "height", "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 322 }, { "label": "upscale_method", "name": "upscale_method", "type": "COMBO", "widget": { "name": "upscale_method" }, "link": null }, { "label": "keep_proportion", "name": "keep_proportion", "type": "COMBO", "widget": { "name": "keep_proportion" }, "link": null }, { "label": "pad_color", "name": "pad_color", "type": "STRING", "widget": { "name": "pad_color" }, "link": null }, { "label": "crop_position", "name": "crop_position", "type": "COMBO", "widget": { "name": "crop_position" }, "link": null }, { "label": "divisible_by", "name": "divisible_by", "type": "INT", "widget": { "name": "divisible_by" }, "link": null }, { "label": "device", "name": "device", "shape": 7, "type": "COMBO", "widget": { "name": "device" }, "link": null } ], "outputs": [ { "label": "IMAGE", "name": "IMAGE", "type": "IMAGE", "links": [ 320 ] }, { "label": "width", "name": "width", "type": "INT", "links": null }, { "label": "height", "name": "height", "type": "INT", "links": null }, { "label": "mask", "name": "mask", "type": "MASK", "links": null } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "79f529a84a8c20fe5dcdfa984c6be7a94102c014", "Node name for S&R": "ImageResizeKJv2", "ue_properties": { "widget_ue_connectable": { "width": true, "height": true, "upscale_method": true, "keep_proportion": true, "pad_color": true, "crop_position": true, "divisible_by": true, "device": true }, "version": "7.5.2", "input_ue_unconnectable": {} } }, "widgets_values": [ 480, 640, "lanczos", "crop", "0, 0, 0", "center", 32, "cpu" ], "widgets_values_named": { "width": 480, "height": 640, "upscale_method": "lanczos", "keep_proportion": "crop", "pad_color": "0, 0, 0", "crop_position": "center", "divisible_by": 32, "device": "cpu" } }, { "id": 114, "type": "LoadImage", "pos": [ -1683.2296875771474, 5977.968582798644 ], "size": [ 497.15895381999985, 384.7734401360003 ], "flags": {}, "order": 5, "mode": 2, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 323 ] }, { "name": "MASK", "type": "MASK", "links": null } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "LoadImage", "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "1024834.jpg", "image" ], "widgets_values_named": { "image": "1024834.jpg", "upload": "image" } }, { "id": 143, "type": "PreviewImage", "pos": [ -842.0068874523383, 5774.126149170824 ], "size": [ 345.2114935707133, 435.03718865873634 ], "flags": {}, "order": 11, "mode": 2, "inputs": [ { "name": "images", "type": "IMAGE", "link": 320 } ], "outputs": [ { "name": "images", "type": "IMAGE", "links": [ 319 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "PreviewImage", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.8" } } }, { "id": 152, "type": "Fast Groups Muter (rgthree)", "pos": [ -1135.7764785690729, 5145.260710958273 ], "size": [ 287.1815421874999, 97.03250000000025 ], "flags": {}, "order": 6, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "properties": { "matchColors": "black", "matchTitle": "", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#222", "bgcolor": "#000" }, { "id": 138, "type": "RTXVideoSuperResolution", "pos": [ -119.93406101755284, 4623.495904351338 ], "size": [ 285.81015625, 106 ], "flags": {}, "order": 13, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 302 } ], "outputs": [ { "name": "upscaled_images", "type": "IMAGE", "links": [ 303 ] } ], "properties": { "cnr_id": "comfyui_nvidia_rtx_nodes", "ver": "0.1.3", "Node name for S&R": "RTXVideoSuperResolution", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.8" } }, "widgets_values": [ "scale by multiplier", 2, "ULTRA" ], "widgets_values_named": { "resize_type": "scale by multiplier", "resize_type.scale": 2, "quality": "ULTRA" } }, { "id": 136, "type": "VHS_VideoCombine", "pos": [ -197.51965272054596, 4811.535374640719 ], "size": [ 752.6556301296483, 1335.4923710443086 ], "flags": {}, "order": 14, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 300 }, { "name": "audio", "shape": 7, "type": "AUDIO", "link": 301 }, { "name": "meta_batch", "shape": 7, "type": "VHS_BatchManager", "link": null }, { "name": "vae", "shape": 7, "type": "VAE", "link": null } ], "outputs": [ { "name": "Filenames", "type": "VHS_FILENAMES", "links": null } ], "properties": { "cnr_id": "comfyui_fearnworksnodes", "ver": "0.1.2", "Node name for S&R": "VHS_VideoCombine", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.8" } }, "widgets_values": { "frame_rate": 24, "loop_count": 0, "filename_prefix": "Mini", "format": "video/h264-mp4", "pix_fmt": "yuv420p", "crf": 19, "save_metadata": true, "trim_to_audio": false, "pingpong": false, "save_output": false, "videopreview": { "hidden": false, "paused": false, "params": { "filename": "Mini_00005-audio.mp4", "subfolder": "", "type": "temp", "format": "video/h264-mp4", "frame_rate": 24, "workflow": "Mini_00005.png", "fullpath": "/app/ComfyUI/temp/Mini_00005-audio.mp4" } } }, "widgets_values_named": { "frame_rate": 24, "loop_count": 0, "filename_prefix": "Mini", "format": "video/h264-mp4", "pix_fmt": "yuv420p", "crf": 19, "save_metadata": true, "trim_to_audio": false, "pingpong": false, 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"input_ue_unconnectable": {}, "version": "7.8" } }, "widgets_values": { "frame_rate": 24, "loop_count": 0, "filename_prefix": "MiniUP", "format": "video/h264-mp4", "pix_fmt": "yuv420p", "crf": 19, "save_metadata": true, "trim_to_audio": false, "pingpong": false, "save_output": false, "videopreview": { "hidden": false, "paused": false, "params": { "filename": "MiniUP_00005-audio.mp4", "subfolder": "", "type": "temp", "format": "video/h264-mp4", "frame_rate": 24, "workflow": "MiniUP_00005.png", "fullpath": "/app/ComfyUI/temp/MiniUP_00005-audio.mp4" } } }, "widgets_values_named": { "frame_rate": 24, "loop_count": 0, "filename_prefix": "MiniUP", "format": "video/h264-mp4", "pix_fmt": "yuv420p", "crf": 19, "save_metadata": true, "trim_to_audio": false, "pingpong": false, "save_output": false, "videopreview": { "hidden": false, "paused": false, "params": { "filename": "MiniUP_00005-audio.mp4", "subfolder": "", "type": "temp", "format": "video/h264-mp4", "frame_rate": 24, "workflow": "MiniUP_00005.png", "fullpath": "/app/ComfyUI/temp/MiniUP_00005-audio.mp4" } } } }, { "id": 115, "type": "ResolutionSelector", "pos": [ -1126.361157314262, 5283.387140906113 ], "size": [ 270, 170 ], "flags": {}, "order": 7, "mode": 0, "showAdvanced": false, "inputs": [ { "name": "preview", "shape": 7, "type": "RESOLUTION_PREVIEW", "link": null } ], "outputs": [ { "name": "width", "type": "INT", "links": [ 219, 321, 325 ] }, { "name": "height", "type": "INT", "links": [ 220, 322, 326 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "ResolutionSelector", "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "3:4 (Portrait Standard)", 0.7, 32 ], "widgets_values_named": { "aspect_ratio": "3:4 (Portrait Standard)", "megapixels": 0.7, "multiple": 32 } }, { "id": 105, "type": "4c314f31-ecda-4b08-ae98-faaba1bf613f", "pos": [ -741.2117687301633, 4778.406988594188 ], "size": [ 480, 630 ], "flags": {}, "order": 12, "mode": 0, "inputs": [ { "name": "first_frame", "shape": 7, "type": "IMAGE", "link": 319 }, { "name": "last_frame", "shape": 7, "type": "IMAGE", "link": 327 }, { "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 219 }, { "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 220 }, { "label": "duration", "name": "value_1", "type": "FLOAT", "widget": { "name": "value_1" }, "link": null }, { "label": "audio_vae", "name": "vae_name_1", "type": "COMBO", "widget": { "name": "vae_name_1" }, "link": null } ], "outputs": [ { "name": "VIDEO", "type": "VIDEO", "links": [] }, { "name": "IMAGE", "type": "IMAGE", "links": [ 300, 302 ] }, { "name": "AUDIO", "type": "AUDIO", "links": [ 301, 304 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "previewExposures": [], "ue_properties": { "widget_ue_connectable": { "width": true, "height": true, "value_1": true, "vae_name_1": true }, "version": "7.8", 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