什么是 Flux.1？
Flux.1 是由 Stable Diffusion 的开发成员创立的 Black Forest Labs 推出的图像生成模型。
不仅单纯是“高性能版”，在架构方面也是巨大转折点的模型。
- 图像生成的核心，从传统的 UNet 替换为了 Transformer（DiT）基础
- 作为文本编码器，采用了 T5 系的 LLM
通过这个组合，变得能从大规模的数据集高效地学习，
变得容易原样活用 LLM 的文章理解力，成为了通往现在主流的图像生成模型群的分歧点。
Flux.1 有 3 个变体。
- Flux.1 pro
- 仅能通过 API 利用的版本，未公开模型权重。
- Flux.1 dev
- 蒸馏了 pro 的研究・验证用模型。在本地环境最常使用的是这个。
- Flux.1 schnell
- 进一步蒸馏了 dev 的模型，以 Apache-2.0 这个比较宽松的许可证公开。
模型的下载
这里使用 dev / schnell 的 fp8 版。
-
diffusion model
-
CLIP / T5
-
VAE
-
📂ComfyUI/ └── 📂models/ ├── 📂diffusion_models/ │ ├── flux1-dev-fp8.safetensors │ └── flux1-schnell-fp8.safetensors ├── 📂clip/ │ ├── clip_l.safetensors │ └── t5xxl_fp8_e4m3fn_scaled.safetensors └── 📂vae/ └── ae.safetensors
text2image - Flux.1 [dev]
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"revision": 0,
"last_node_id": 46,
"last_link_id": 64,
"nodes": [
{
"id": 35,
"type": "FluxGuidance",
"pos": [
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"size": [
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"flags": {},
"order": 6,
"mode": 0,
"inputs": [
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],
"outputs": [
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"name": "CONDITIONING",
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"slot_index": 0,
"links": [
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]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "FluxGuidance"
},
"widgets_values": [
3.5
],
"color": "#2a363b",
"bgcolor": "#3f5159"
},
{
"id": 31,
"type": "KSampler",
"pos": [
1070,
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],
"size": [
315,
262
],
"flags": {},
"order": 7,
"mode": 0,
"inputs": [
{
"name": "model",
"type": "MODEL",
"link": 61
},
{
"name": "positive",
"type": "CONDITIONING",
"link": 57
},
{
"name": "negative",
"type": "CONDITIONING",
"link": 55
},
{
"name": "latent_image",
"type": "LATENT",
"link": 51
}
],
"outputs": [
{
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
52
]
}
],
"properties": {
"cnr_id": "comfy-core",
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"type": "DualCLIPLoader",
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],
"size": [
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],
"flags": {},
"order": 0,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "CLIP",
"type": "CLIP",
"links": [
59,
60
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "DualCLIPLoader"
},
"widgets_values": [
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"t5xxl_fp8_e4m3fn.safetensors",
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"color": "#432",
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},
{
"id": 33,
"type": "CLIPTextEncode",
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"size": [
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],
"flags": {
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},
"order": 5,
"mode": 0,
"inputs": [
{
"name": "clip",
"type": "CLIP",
"link": 60
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
55
]
}
],
"title": "CLIP Text Encode (Negative Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
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},
{
"id": 43,
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"size": [
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"flags": {},
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"outputs": [
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"type": "VAE",
"links": [
62
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "VAELoader"
},
"widgets_values": [
"ae.safetensors"
],
"color": "#322",
"bgcolor": "#533"
},
{
"id": 27,
"type": "EmptySD3LatentImage",
"pos": [
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],
"size": [
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],
"flags": {},
"order": 2,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
51
]
}
],
"properties": {
"cnr_id": "comfy-core",
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}
],
"properties": {
"cnr_id": "comfy-core",
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"id": 6,
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],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
56
]
}
],
"title": "CLIP Text Encode (Positive Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
"Futuristic architecture, flowing organic shapes, white surfaces, parametric design"
]
},
{
"id": 8,
"type": "VAEDecode",
"pos": [
1409.529396057129,
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],
"size": [
140,
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],
"flags": {},
"order": 8,
"mode": 0,
"inputs": [
{
"name": "samples",
"type": "LATENT",
"link": 52
},
{
"name": "vae",
"type": "VAE",
"link": 62
}
],
"outputs": [
{
"name": "IMAGE",
"type": "IMAGE",
"slot_index": 0,
"links": [
64
]
}
],
"properties": {
"cnr_id": "comfy-core",
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"id": 46,
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"flags": {},
"order": 9,
"mode": 0,
"inputs": [
{
"name": "images",
"type": "IMAGE",
"link": 64
}
],
"outputs": [],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.76"
},
"widgets_values": [
"ComfyUI"
]
}
],
"links": [
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8,
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33,
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31,
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"CONDITIONING"
],
[
59,
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0,
6,
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"CLIP"
],
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60,
42,
0,
33,
0,
"CLIP"
],
[
61,
41,
0,
31,
0,
"MODEL"
],
[
62,
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0,
8,
1,
"VAE"
],
[
64,
8,
0,
46,
0,
"IMAGE"
]
],
"groups": [],
"config": {},
"extra": {
"ds": {
"scale": 0.9090909090909091,
"offset": [
-85.05879211425781,
58.032955169677734
]
},
"frontendVersion": "1.35.0",
"VHS_latentpreview": false,
"VHS_latentpreviewrate": 0,
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"version": 0.4
}
Flux.1 dev / schnell 是 蒸馏了固定 CFG 为 1.0 状态的模型。
因此，不像传统的 Stable Diffusion 那样以 CFG scale 和 Negative Prompt 的调整为前提，Negative Prompt 完全不生效。
我将 Negative 侧的提示词留空了，但其他工作流中也有代替 Negative 用的 CLIP Text Encode 节点，插入 ConditioningZeroOut 节点的。
无论哪种情况，Negative 侧的条件会被乘 0，所以写什么都不会影响输出。
text2image - Flux.1 [schnell]
是进一步蒸馏了 Flux.1 [dev] 的东西，可以用 4〜6 步生成图像。
{
"id": "18404b37-92b0-4d11-a39c-ae941838eb83",
"revision": 0,
"last_node_id": 47,
"last_link_id": 64,
"nodes": [
{
"id": 35,
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"pos": [
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"size": [
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"flags": {},
"order": 6,
"mode": 0,
"inputs": [
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"link": 56
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
57
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "FluxGuidance"
},
"widgets_values": [
3.5
],
"color": "#2a363b",
"bgcolor": "#3f5159"
},
{
"id": 42,
"type": "DualCLIPLoader",
"pos": [
185.0587921142578,
235.1116485595703
],
"size": [
270,
130
],
"flags": {},
"order": 0,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "CLIP",
"type": "CLIP",
"links": [
59,
60
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "DualCLIPLoader"
},
"widgets_values": [
"clip_l.safetensors",
"t5xxl_fp8_e4m3fn.safetensors",
"flux",
"default"
],
"color": "#432",
"bgcolor": "#653"
},
{
"id": 33,
"type": "CLIPTextEncode",
"pos": [
507,
378
],
"size": [
307.77605192326325,
100.04636029960699
],
"flags": {
"collapsed": true
},
"order": 5,
"mode": 0,
"inputs": [
{
"name": "clip",
"type": "CLIP",
"link": 60
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
55
]
}
],
"title": "CLIP Text Encode (Negative Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
""
]
},
{
"id": 43,
"type": "VAELoader",
"pos": [
1144.1833021837801,
70.74821376556925
],
"size": [
240.81669781621986,
58
],
"flags": {},
"order": 1,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "VAE",
"type": "VAE",
"links": [
62
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "VAELoader"
},
"widgets_values": [
"ae.safetensors"
],
"color": "#322",
"bgcolor": "#533"
},
{
"id": 27,
"type": "EmptySD3LatentImage",
"pos": [
795.437243997102,
463.56198347107454
],
"size": [
252.16276210641365,
106
],
"flags": {},
"order": 2,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
51
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "EmptySD3LatentImage"
},
"widgets_values": [
1024,
1024,
1
]
},
{
"id": 41,
"type": "UNETLoader",
"pos": [
777.6000061035156,
41.967044830322266
],
"size": [
270,
82
],
"flags": {},
"order": 3,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "MODEL",
"type": "MODEL",
"links": [
61
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "UNETLoader"
},
"widgets_values": [
"Flux.1\\flux1-schnell-fp8.safetensors",
"fp8_e4m3fn"
],
"color": "#323",
"bgcolor": "#535"
},
{
"id": 8,
"type": "VAEDecode",
"pos": [
1409.529396057129,
190
],
"size": [
159.83471074380168,
46
],
"flags": {},
"order": 8,
"mode": 0,
"inputs": [
{
"name": "samples",
"type": "LATENT",
"link": 52
},
{
"name": "vae",
"type": "VAE",
"link": 62
}
],
"outputs": [
{
"name": "IMAGE",
"type": "IMAGE",
"slot_index": 0,
"links": [
64
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "VAEDecode"
},
"widgets_values": []
},
{
"id": 46,
"type": "SaveImage",
"pos": [
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190
],
"size": [
378.4000000000001,
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],
"flags": {},
"order": 9,
"mode": 0,
"inputs": [
{
"name": "images",
"type": "IMAGE",
"link": 64
}
],
"outputs": [],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.76"
},
"widgets_values": [
"ComfyUI"
]
},
{
"id": 6,
"type": "CLIPTextEncode",
"pos": [
507,
190
],
"size": [
301.84503173828125,
128.01304626464844
],
"flags": {},
"order": 4,
"mode": 0,
"inputs": [
{
"name": "clip",
"type": "CLIP",
"link": 59
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
56
]
}
],
"title": "CLIP Text Encode (Positive Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
"Watercolor, illustration of a bird"
]
},
{
"id": 31,
"type": "KSampler",
"pos": [
1070,
190
],
"size": [
315,
262
],
"flags": {},
"order": 7,
"mode": 0,
"inputs": [
{
"name": "model",
"type": "MODEL",
"link": 61
},
{
"name": "positive",
"type": "CONDITIONING",
"link": 57
},
{
"name": "negative",
"type": "CONDITIONING",
"link": 55
},
{
"name": "latent_image",
"type": "LATENT",
"link": 51
}
],
"outputs": [
{
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
52
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "KSampler"
},
"widgets_values": [
1234,
"fixed",
4,
1,
"euler",
"normal",
1
]
}
],
"links": [
[
51,
27,
0,
31,
3,
"LATENT"
],
[
52,
31,
0,
8,
0,
"LATENT"
],
[
55,
33,
0,
31,
2,
"CONDITIONING"
],
[
56,
6,
0,
35,
0,
"CONDITIONING"
],
[
57,
35,
0,
31,
1,
"CONDITIONING"
],
[
59,
42,
0,
6,
0,
"CLIP"
],
[
60,
42,
0,
33,
0,
"CLIP"
],
[
61,
41,
0,
31,
0,
"MODEL"
],
[
62,
43,
0,
8,
1,
"VAE"
],
[
64,
8,
0,
46,
0,
"IMAGE"
]
],
"groups": [],
"config": {},
"extra": {
"ds": {
"scale": 0.9090909090909091,
"offset": [
-85.05879211425781,
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]
},
"frontendVersion": "1.35.0",
"VHS_latentpreview": false,
"VHS_latentpreviewrate": 0,
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"version": 0.4
}
- 将
steps设为 4〜6。
LoRA - Flux.1 [dev]
试用一下提高肖像画质量的 LoRA 吧。
{
"id": "18404b37-92b0-4d11-a39c-ae941838eb83",
"revision": 0,
"last_node_id": 47,
"last_link_id": 66,
"nodes": [
{
"id": 35,
"type": "FluxGuidance",
"pos": [
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"size": [
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"flags": {},
"order": 7,
"mode": 0,
"inputs": [
{
"name": "conditioning",
"type": "CONDITIONING",
"link": 56
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
57
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "FluxGuidance"
},
"widgets_values": [
3.5
],
"color": "#2a363b",
"bgcolor": "#3f5159"
},
{
"id": 31,
"type": "KSampler",
"pos": [
1070,
190
],
"size": [
315,
262
],
"flags": {},
"order": 8,
"mode": 0,
"inputs": [
{
"name": "model",
"type": "MODEL",
"link": 65
},
{
"name": "positive",
"type": "CONDITIONING",
"link": 57
},
{
"name": "negative",
"type": "CONDITIONING",
"link": 55
},
{
"name": "latent_image",
"type": "LATENT",
"link": 51
}
],
"outputs": [
{
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
52
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "KSampler"
},
"widgets_values": [
1234,
"fixed",
20,
1,
"euler",
"normal",
1
]
},
{
"id": 42,
"type": "DualCLIPLoader",
"pos": [
185.0587921142578,
235.1116485595703
],
"size": [
270,
130
],
"flags": {},
"order": 0,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "CLIP",
"type": "CLIP",
"links": [
59,
60
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "DualCLIPLoader"
},
"widgets_values": [
"clip_l.safetensors",
"t5xxl_fp8_e4m3fn.safetensors",
"flux",
"default"
],
"color": "#432",
"bgcolor": "#653"
},
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- 🟪 在 LoRA 中也写了，Flux 以后不再学习文本编码器，所以不使用
Load LoRA节点，使用 仅适用于权重的LoraLoaderModelOnly节点。
ControlNet - Flux.1 [dev]
Flux.1 用的 ControlNet 模型也公开了几个，这里以 Union 型模型为例介绍。
模型的下载
-
FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8/diffusion_pytorch_model.safetensors
- 很难懂，所以请重命名为
FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8.safetensors等。
- 很难懂，所以请重命名为
-
📂ComfyUI/ └── 📂models/ └── 📂controlnet/ └── FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8.safetensors
工作流
ControlNet-Union 将多个代表性的 ControlNet 内置在 1 个模型中。
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87,
6,
0,
35,
0,
"CONDITIONING"
],
[
88,
35,
0,
47,
0,
"CONDITIONING"
]
],
"groups": [],
"config": {},
"extra": {
"ds": {
"scale": 0.620921323059155,
"offset": [
62.989782337250965,
24.10627508703305
]
},
"frontendVersion": "1.35.0",
"VHS_latentpreview": false,
"VHS_latentpreviewrate": 0,
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"version": 0.4
}
-
🟩 只是在使用了 Flux 的 image2image 工作流中插入了 ControlNet。
- 虽说是 image2image 但
denoise是 1.0，所以举动几乎和 text2image 一样。 - 因为可以用很少的节点制作与输入图像相同尺寸的图像，所以我常使用这个形式。
- 虽说是 image2image 但
-
🟩 在
SetUnionControlNetType中，输入想使用的 ControlNet 类型。- 基本上
auto就没问题。
- 基本上
GGUF（轻量化 Flux.1）
最后，稍微提一下 GGUF 版 Flux.1。
原本 GGUF 是为了轻量化 LLM 的格式（被量化的权重形式）， 通过将其应用到 Flux.1，可以 在减少 VRAM 使用量的同时，以相应的速度运转。
自定义节点
模型的下载
根据性能和模型尺寸的平衡，有几个变体。 请配合 PC 规格和用途选择。
-
📂ComfyUI/ └── 📂models/ └── 📂unet/ └── flux1-dev.gguf
工作流
{
"id": "18404b37-92b0-4d11-a39c-ae941838eb83",
"revision": 0,
"last_node_id": 48,
"last_link_id": 65,
"nodes": [
{
"id": 35,
"type": "FluxGuidance",
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"size": [
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"flags": {},
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"mode": 0,
"inputs": [
{
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}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
57
]
}
],
"properties": {
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},
"widgets_values": [
3.5
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"color": "#2a363b",
"bgcolor": "#3f5159"
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{
"id": 31,
"type": "KSampler",
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1070,
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],
"size": [
315,
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],
"flags": {},
"order": 7,
"mode": 0,
"inputs": [
{
"name": "model",
"type": "MODEL",
"link": 65
},
{
"name": "positive",
"type": "CONDITIONING",
"link": 57
},
{
"name": "negative",
"type": "CONDITIONING",
"link": 55
},
{
"name": "latent_image",
"type": "LATENT",
"link": 51
}
],
"outputs": [
{
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
52
]
}
],
"properties": {
"cnr_id": "comfy-core",
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},
"widgets_values": [
1234,
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20,
1,
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1
]
},
{
"id": 42,
"type": "DualCLIPLoader",
"pos": [
185.0587921142578,
235.1116485595703
],
"size": [
270,
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],
"flags": {},
"order": 0,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "CLIP",
"type": "CLIP",
"links": [
59,
60
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "DualCLIPLoader"
},
"widgets_values": [
"clip_l.safetensors",
"t5xxl_fp8_e4m3fn.safetensors",
"flux",
"default"
],
"color": "#432",
"bgcolor": "#653"
},
{
"id": 33,
"type": "CLIPTextEncode",
"pos": [
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"size": [
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],
"flags": {
"collapsed": true
},
"order": 5,
"mode": 0,
"inputs": [
{
"name": "clip",
"type": "CLIP",
"link": 60
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
55
]
}
],
"title": "CLIP Text Encode (Negative Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
""
]
},
{
"id": 43,
"type": "VAELoader",
"pos": [
1144.1833021837801,
70.74821376556925
],
"size": [
240.81669781621986,
58
],
"flags": {},
"order": 1,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "VAE",
"type": "VAE",
"links": [
62
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "VAELoader"
},
"widgets_values": [
"ae.safetensors"
],
"color": "#322",
"bgcolor": "#533"
},
{
"id": 27,
"type": "EmptySD3LatentImage",
"pos": [
795.437243997102,
463.56198347107454
],
"size": [
252.16276210641365,
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],
"flags": {},
"order": 2,
"mode": 0,
"inputs": [],
"outputs": [
{
"name": "LATENT",
"type": "LATENT",
"slot_index": 0,
"links": [
51
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "EmptySD3LatentImage"
},
"widgets_values": [
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]
},
{
"id": 8,
"type": "VAEDecode",
"pos": [
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],
"size": [
140,
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],
"flags": {},
"order": 8,
"mode": 0,
"inputs": [
{
"name": "samples",
"type": "LATENT",
"link": 52
},
{
"name": "vae",
"type": "VAE",
"link": 62
}
],
"outputs": [
{
"name": "IMAGE",
"type": "IMAGE",
"slot_index": 0,
"links": [
64
]
}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "VAEDecode"
},
"widgets_values": []
},
{
"id": 46,
"type": "SaveImage",
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],
"size": [
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],
"flags": {},
"order": 9,
"mode": 0,
"inputs": [
{
"name": "images",
"type": "IMAGE",
"link": 64
}
],
"outputs": [],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.76"
},
"widgets_values": [
"ComfyUI"
]
},
{
"id": 6,
"type": "CLIPTextEncode",
"pos": [
507,
190
],
"size": [
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],
"flags": {},
"order": 4,
"mode": 0,
"inputs": [
{
"name": "clip",
"type": "CLIP",
"link": 59
}
],
"outputs": [
{
"name": "CONDITIONING",
"type": "CONDITIONING",
"slot_index": 0,
"links": [
56
]
}
],
"title": "CLIP Text Encode (Positive Prompt)",
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.39",
"Node name for S&R": "CLIPTextEncode"
},
"widgets_values": [
"Grand hall of ancient castle, chandelier, moonlight streaming in, gothic atmosphere"
]
},
{
"id": 48,
"type": "UnetLoaderGGUF",
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],
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"mode": 0,
"inputs": [],
"outputs": [
{
"name": "MODEL",
"type": "MODEL",
"links": [
65
]
}
],
"properties": {
"cnr_id": "ComfyUI-GGUF",
"ver": "02dac863ee1b65852d39ce6b9180bf5d9bc8a636",
"Node name for S&R": "UnetLoaderGGUF"
},
"widgets_values": [
"FLUX_gguf\\flux1-dev-Q4_0.gguf"
],
"color": "#323",
"bgcolor": "#535"
}
],
"links": [
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27,
0,
31,
3,
"LATENT"
],
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31,
0,
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"LATENT"
],
[
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31,
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],
[
56,
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35,
0,
"CONDITIONING"
],
[
57,
35,
0,
31,
1,
"CONDITIONING"
],
[
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0,
6,
0,
"CLIP"
],
[
60,
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0,
33,
0,
"CLIP"
],
[
62,
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0,
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1,
"VAE"
],
[
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46,
0,
"IMAGE"
],
[
65,
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31,
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]
],
"groups": [],
"config": {},
"extra": {
"ds": {
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"offset": [
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},
"frontendVersion": "1.35.0",
"VHS_latentpreview": false,
"VHS_latentpreviewrate": 0,
"VHS_MetadataImage": true,
"VHS_KeepIntermediate": true
},
"version": 0.4
}
-
🟪 将
Load Diffusion Model节点替换为Unet Loader (GGUF)节点。 -
其他 CLIP / T5 / VAE 部分保持原样。
- 虽然也可以把 T5 换成 GGUF，但体感上没有那么大的效果。
现在的许多模型都准备了 GGUF 版。 使用 GGUF 几乎没有缺点，所以在 VRAM 不足时请积极尝试。