nodes/Zehong-Ma-ComfyUI-MagCache
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update_workflow

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zehongma
2025-11-27 19:52:43 +08:00
parent f450802862
commit 47bdd2aca9
3 changed files with 157 additions and 1264 deletions
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README.md
+2 -2
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@@ -50,7 +50,7 @@ To use MagCache node, simply add `MagCache` node to your workflow after `Load Di
| Chroma | 0.10 | 0.25 | 2 |
| Qwen-Image | 0.10 | 0.20 | 2 |
| HunyuanVideo-T2V | 0.24 | 0.2 | 6 |
| HunyuanVideo1.5-T2V | 0.03 | 0.25 | 2 |
| HunyuanVideo1.5-T2V(20 steps)| 0.03 | 0.25 | 2 |
| Wan2.1-T2V-1.3B | 0.12 | 0.2 | 4 |
| Wan2.1-T2V-14B | 0.24 | 0.2 | 6 |
| Wan2.1-I2V-480P-14B | 0.24 | 0.2 | 6 |
@@ -62,7 +62,7 @@ To use MagCache node, simply add `MagCache` node to your workflow after `Load Di
**If the image/video after applying MagCache is of low quality, please decrease `magcache_thresh` and `magcache_K`**. The default parameters are configured for extremely fast inference(2x-3x), which may lead to failures in some cases.
The demo workflows ([flux](./examples/flux.json), [flux-kontext](./examples/flux_1_kontext_dev.json), [qwen-image](./examples/qwen_image_basic_example.json), [chroma](./examples/chroma.json), [hunyuanvideo](./examples/hunyuanvideo.json), [hunyuanvideo1.5](./examples/video_hunyuan_video_1.5_720p_t2v_magcache_fast.json), [wan2.1_t2v](./examples/wan2.1_t2v.json), [wan2.1_i2v](./examples/wan2.1_i2v.json), and [wan2.1_vace](./examples/wan2.1_vace.json)) are placed in examples folder. The workflow [chroma_calibration](./examples/chroma_calibration.json) is used to calibrate the `mag_ratios` for `Chroma` when the number of inference steps differs from the pre-defined value.
The demo workflows ([flux](./examples/flux.json), [flux-kontext](./examples/flux_1_kontext_dev.json), [qwen-image](./examples/qwen_image_basic_example.json), [chroma](./examples/chroma.json), [hunyuanvideo](./examples/hunyuanvideo.json), [hunyuanvideo1.5](./examples/video_hunyuan_video_1.5_720p_t2v_magcache.json), [wan2.1_t2v](./examples/wan2.1_t2v.json), [wan2.1_i2v](./examples/wan2.1_i2v.json), and [wan2.1_vace](./examples/wan2.1_vace.json)) are placed in examples folder. The workflow [chroma_calibration](./examples/chroma_calibration.json) is used to calibrate the `mag_ratios` for `Chroma` when the number of inference steps differs from the pre-defined value.
**In our experiments, the videos generated by Wan2.1 are not as high-quality as those produced by the [original unquantized version](https://github.com/Wan-Video/Wan2.1).**
examples/video_hunyuan_video_1.5_720p_t2v_magcache.json
+155 -96
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@@ -1,8 +1,8 @@
{
"id": "ecc20583-98c5-4707-83f4-631b49a2bf0b",
"revision": 0,
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"last_link_id": 287,
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"nodes": [
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"id": 8,
@@ -16,7 +16,7 @@
46
],
"flags": {},
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"order": 11,
"mode": 0,
"inputs": [
{
@@ -138,49 +138,6 @@
"hunyuanvideo15_vae_fp16.safetensors"
]
},
{
"id": 44,
"type": "CLIPTextEncode",
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],
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],
"flags": {},
"order": 5,
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"inputs": [
{
"name": "clip",
"type": "CLIP",
"link": 205
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
272
]
}
],
"title": "CLIP Text Encode (Positive Prompt)",
"properties": {
"Node name for S&R": "CLIPTextEncode",
"cnr_id": "comfy-core",
"ver": "0.3.68"
},
"widgets_values": [
"A paper airplane released from the top of a skyscraper, gliding through urban canyons, crossing traffic, flying over streets, spiraling upward between buildings. The camera follows the paper airplane's perspective, shooting cityscape in first-person POV, finally flying toward the sunset, disappearing in golden light. Creative camera movement, free perspective, dreamlike colors."
],
"color": "#232",
"bgcolor": "#353"
},
{
"id": 107,
"type": "EmptyHunyuanVideo15Latent",
@@ -229,7 +186,7 @@
78
],
"flags": {},
"order": 10,
"order": 12,
"mode": 0,
"inputs": [
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@@ -274,7 +231,7 @@
200
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"inputs": [
{
@@ -351,7 +308,7 @@
"type": "MODEL",
"slot_index": 0,
"links": [
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]
}
],
@@ -372,6 +329,141 @@
"default"
]
},
{
"id": 102,
"type": "SaveVideo",
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],
"size": [
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],
"flags": {},
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"inputs": [
{
"name": "video",
"type": "VIDEO",
"link": 269
}
],
"outputs": [],
"properties": {
"Node name for S&R": "SaveVideo",
"cnr_id": "comfy-core",
"ver": "0.3.68"
},
"widgets_values": [
"video/hunyuan_video_1.5",
"auto",
"h264"
]
},
{
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"type": "CLIPTextEncode",
"pos": [
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"size": [
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],
"flags": {},
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"inputs": [
{
"name": "clip",
"type": "CLIP",
"link": 205
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
272
]
}
],
"title": "CLIP Text Encode (Positive Prompt)",
"properties": {
"Node name for S&R": "CLIPTextEncode",
"cnr_id": "comfy-core",
"ver": "0.3.68"
},
"widgets_values": [
"俯视角度，一位有着深色，略带凌乱的长卷发的年轻中国女性，佩戴着闪耀的珍珠项链和圆形金色耳环，她凌乱的头发被风吹散，她微微抬头，望向天空，神情十分哀伤，眼中含着泪水。嘴唇涂着红色口红。背景是带有华丽红色花纹的图案。画面呈现复古电影风格，色调低饱和，带着轻微柔焦，烘托情绪氛围，质感仿佛20世纪90年代的经典胶片风格，营造出怀旧且富有戏剧性的感觉。"
],
"color": "#232",
"bgcolor": "#353"
},
{
"id": 114,
"type": "MagCacheCalibration",
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],
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"inputs": [
{
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"type": "MODEL",
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}
],
"outputs": [
{
"name": "model",
"type": "MODEL",
"links": []
}
],
"properties": {
"Node name for S&R": "MagCacheCalibration"
},
"widgets_values": [
"hunyuanvideo1.5"
]
},
{
"id": 113,
"type": "Note",
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],
"size": [
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"flags": {},
"order": 6,
"mode": 0,
"inputs": [],
"outputs": [],
"title": "Note for MagCache",
"properties": {},
"widgets_values": [
"We calibrate the MagCache using the MagCache Calibration node with 20 euler sampling steps. The calibrated mag_ratios can also be utilized with a different inference steps. \n\nThe following config achieves 1.5x speedup without degrading visual quality.\nmagcache_thresh: 0.03\nmagcache_K: 1\nretention_ratio: 0.25\n\nFor a faster generateing, please utilize the following hyper-parameters, achieving a 1.7x speedup with a balance between quality and speed. \nmagcache_thresh: 0.03\nmagcache_K: 2\nretention_ratio: 0.25\n\nWith more inference steps (30-50), please increase the magcache_thresh to 0.06 and decrease the retension ratio to 0.2\n\nThe following config achieves 1.7x speedup without degrading visual quality.\nmagcache_thresh: 0.06\nmagcache_K: 2\nretention_ratio: 0.2\n\nThe following config achieves 2.1x speedup without degrading visual quality.\nmagcache_thresh: 0.06\nmagcache_K: 3\nretention_ratio: 0.2\n\n"
],
"color": "#432",
"bgcolor": "#653"
},
{
"id": 100,
"type": "23f96f01-8d55-4804-b218-e42e2bafa41b",
@@ -384,7 +476,7 @@
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],
"flags": {},
"order": 8,
"order": 10,
"mode": 0,
"inputs": [
{
@@ -395,7 +487,7 @@
{
"name": "model",
"type": "MODEL",
"link": 287
"link": 291
},
{
"name": "positive",
@@ -457,39 +549,6 @@
},
"widgets_values": []
},
{
"id": 102,
"type": "SaveVideo",
"pos": [
650,
20
],
"size": [
730,
828
],
"flags": {},
"order": 11,
"mode": 0,
"inputs": [
{
"name": "video",
"type": "VIDEO",
"link": 269
}
],
"outputs": [],
"properties": {
"Node name for S&R": "SaveVideo",
"cnr_id": "comfy-core",
"ver": "0.3.68"
},
"widgets_values": [
"video/hunyuan_video_1.5",
"auto",
"h264"
]
},
{
"id": 112,
"type": "MagCache",
@@ -502,13 +561,13 @@
178
],
"flags": {},
"order": 7,
"order": 9,
"mode": 0,
"inputs": [
{
"name": "model",
"type": "MODEL",
"link": 286
"link": 290
}
],
"outputs": [
@@ -516,7 +575,7 @@
"name": "model",
"type": "MODEL",
"links": [
287
291
]
}
],
@@ -525,9 +584,9 @@
},
"widgets_values": [
"hunyuan_video1.5",
0.03,
0.25,
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0.06,
0.2,
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-2
]
@@ -607,7 +666,7 @@
"LATENT"
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@@ -615,7 +674,7 @@
"MODEL"
],
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@@ -877,7 +936,7 @@
},
"widgets_values": [
"simple",
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]
},
@@ -1148,10 +1207,10 @@
"config": {},
"extra": {
"ds": {
"scale": 0.5200099198249751,
"scale": 0.6292120029882204,
"offset": [
1340.6097763776763,
190.8478393197784
709.8860997402827,
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]
},
"frontendVersion": "1.28.9",
examples/video_hunyuan_video_1.5_720p_t2v_magcache_fast.json
-1166
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