关于INTEL 的B70 PRO。
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@terry 因为驱动程序/comfyui版本等问题，所以只能用docker来驱动comfyui。这就有挺恶心的问题：
- 不能升级comfyui版本--除非手动打补丁，而且还不一定可以搞定。
- 更新costum node 各种卡死。这个和我的系统关系比较大。
- 更新系统配套的环境，pip 起来也特别麻烦。
- 因为cuda的原因，所以好多的有cuda的流只可以转到xpa或者CPU上。这就有了更多其它的问题。
现在官方优先适配 wan/ltx 这些在comfyui 官方版本里的官方的流，但那些流都是’基础流‘没有优化的。 我试了锤哥推荐的刘悦的流、B站黑鹤的流、程序员萝卜、流光、原上咩等大佬比较新的流，基本上都没办法完善的运行。所以需要调节的还是很多的，甚至不如锤哥说的AMD的环境，这挺让人费劲。
但vllm 这个可能比较简单。我还在搞N卡的comfyui环境。搞好第一时间来发帖。
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https://github.com/intel/llm-scaler/tree/main
这是INTEL 官方公开的支持 B50/60/70 系列显卡的 comfyui 的docker 地址。他们还是做了不少适配的。下边有表：
https://github.com/intel/llm-scaler/tree/main#supported-models
Model Name FP16 Dynamic Online FP8 Dynamic Online Int4 MXFP4 Notes
openai/gpt-oss-20b
openai/gpt-oss-120b
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
deepseek-ai/DeepSeek-R1-Distill-Llama-8B
deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
deepseek-ai/DeepSeek-R1-Distill-Llama-70B
deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
deepseek-ai/DeepSeek-V2-Lite export VLLM_MLA_DISABLE=1
deepseek-ai/deepseek-coder-33b-instruct
Qwen/Qwen3-8B
Qwen/Qwen3-14B
Qwen/Qwen3-32B
Qwen/Qwen3-30B-A3B
Qwen/Qwen3-235B-A22B
Qwen/Qwen3-Coder-30B-A3B-Instruct
Qwen/Qwen3-Coder-Next
Qwen/Qwen3.5-27B
Qwen/Qwen3.5-35B-A3B
Qwen/Qwen3.5-122B-A10B
Qwen/QwQ-32B
mistralai/Ministral-8B-Instruct-2410
mistralai/Mixtral-8x7B-Instruct-v0.1
meta-llama/Llama-3.1-8B
meta-llama/Llama-3.1-70B
baichuan-inc/Baichuan2-7B-Chat with chat_template
baichuan-inc/Baichuan2-13B-Chat with chat_template
THUDM/CodeGeex4-All-9B with chat_template
zai-org/GLM-4-9B-0414 use bfloat16
zai-org/GLM-4-32B-0414 use bfloat16
zai-org/GLM-4.5-Air
zai-org/GLM-4.7-Flash
ByteDance-Seed/Seed-OSS-36B-Instruct
miromind-ai/MiroThinker-v1.5-30B
tencent/Hunyuan-0.5B-Instruct follow the guide in here
tencent/Hunyuan-7B-Instruct follow the guide in here
Qwen/Qwen2-VL-7B-Instruct
Qwen/Qwen2.5-VL-7B-Instruct
Qwen/Qwen2.5-VL-32B-Instruct
Qwen/Qwen2.5-VL-72B-Instruct
Qwen/Qwen3-VL-4B-Instruct
Qwen/Qwen3-VL-8B-Instruct
Qwen/Qwen3-VL-30B-A3B-Instruct
openbmb/MiniCPM-V-2_6
openbmb/MiniCPM-V-4
openbmb/MiniCPM-V-4_5
OpenGVLab/InternVL2-8B
OpenGVLab/InternVL3-8B
OpenGVLab/InternVL3_5-8B
OpenGVLab/InternVL3_5-30B-A3B
rednote-hilab/dots.ocr
ByteDance-Seed/UI-TARS-7B-DPO
google/gemma-3-12b-it use bfloat16
google/gemma-3-27b-it use bfloat16
THUDM/GLM-4v-9B with --hf-overrides and chat_template
zai-org/GLM-4.1V-9B-Base
zai-org/GLM-4.1V-9B-Thinking
zai-org/Glyph
opendatalab/MinerU2.5-2509-1.2B
baidu/ERNIE-4.5-VL-28B-A3B-Thinking
zai-org/GLM-4.6V-Flash pip install transformers==5.0.0rc0 first
PaddlePaddle/PaddleOCR-VL follow the guide in here
deepseek-ai/DeepSeek-OCR
deepseek-ai/DeepSeek-OCR-2 There may be accuracy issues when using --quantization fp8
moonshotai/Kimi-VL-A3B-Thinking-2506
Qwen/Qwen2.5-Omni-7B
Qwen/Qwen3-Omni-30B-A3B-Instruct
openai/whisper-medium
openai/whisper-large-v3
Qwen/Qwen3-Embedding-8B
Qwen3-VL-Embedding-2B/8B follow the guide in here
BAAI/bge-m3
BAAI/bge-large-en-v1.5
Qwen/Qwen3-Reranker-8B
Qwen3-VL-Reranker-2B/8B follow the guide in here
BAAI/bge-reranker-large
BAAI/bge-reranker-v2-m3 -
https://github.com/intel/llm-scaler/tree/main
这是INTEL 官方公开的支持 B50/60/70 系列显卡的 comfyui 的docker 地址。他们还是做了不少适配的。下边有表：
https://github.com/intel/llm-scaler/tree/main#supported-models
Model Name FP16 Dynamic Online FP8 Dynamic Online Int4 MXFP4 Notes
openai/gpt-oss-20b
openai/gpt-oss-120b
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
deepseek-ai/DeepSeek-R1-Distill-Llama-8B
deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
deepseek-ai/DeepSeek-R1-Distill-Llama-70B
deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
deepseek-ai/DeepSeek-V2-Lite export VLLM_MLA_DISABLE=1
deepseek-ai/deepseek-coder-33b-instruct
Qwen/Qwen3-8B
Qwen/Qwen3-14B
Qwen/Qwen3-32B
Qwen/Qwen3-30B-A3B
Qwen/Qwen3-235B-A22B
Qwen/Qwen3-Coder-30B-A3B-Instruct
Qwen/Qwen3-Coder-Next
Qwen/Qwen3.5-27B
Qwen/Qwen3.5-35B-A3B
Qwen/Qwen3.5-122B-A10B
Qwen/QwQ-32B
mistralai/Ministral-8B-Instruct-2410
mistralai/Mixtral-8x7B-Instruct-v0.1
meta-llama/Llama-3.1-8B
meta-llama/Llama-3.1-70B
baichuan-inc/Baichuan2-7B-Chat with chat_template
baichuan-inc/Baichuan2-13B-Chat with chat_template
THUDM/CodeGeex4-All-9B with chat_template
zai-org/GLM-4-9B-0414 use bfloat16
zai-org/GLM-4-32B-0414 use bfloat16
zai-org/GLM-4.5-Air
zai-org/GLM-4.7-Flash
ByteDance-Seed/Seed-OSS-36B-Instruct
miromind-ai/MiroThinker-v1.5-30B
tencent/Hunyuan-0.5B-Instruct follow the guide in here
tencent/Hunyuan-7B-Instruct follow the guide in here
Qwen/Qwen2-VL-7B-Instruct
Qwen/Qwen2.5-VL-7B-Instruct
Qwen/Qwen2.5-VL-32B-Instruct
Qwen/Qwen2.5-VL-72B-Instruct
Qwen/Qwen3-VL-4B-Instruct
Qwen/Qwen3-VL-8B-Instruct
Qwen/Qwen3-VL-30B-A3B-Instruct
openbmb/MiniCPM-V-2_6
openbmb/MiniCPM-V-4
openbmb/MiniCPM-V-4_5
OpenGVLab/InternVL2-8B
OpenGVLab/InternVL3-8B
OpenGVLab/InternVL3_5-8B
OpenGVLab/InternVL3_5-30B-A3B
rednote-hilab/dots.ocr
ByteDance-Seed/UI-TARS-7B-DPO
google/gemma-3-12b-it use bfloat16
google/gemma-3-27b-it use bfloat16
THUDM/GLM-4v-9B with --hf-overrides and chat_template
zai-org/GLM-4.1V-9B-Base
zai-org/GLM-4.1V-9B-Thinking
zai-org/Glyph
opendatalab/MinerU2.5-2509-1.2B
baidu/ERNIE-4.5-VL-28B-A3B-Thinking
zai-org/GLM-4.6V-Flash pip install transformers==5.0.0rc0 first
PaddlePaddle/PaddleOCR-VL follow the guide in here
deepseek-ai/DeepSeek-OCR
deepseek-ai/DeepSeek-OCR-2 There may be accuracy issues when using --quantization fp8
moonshotai/Kimi-VL-A3B-Thinking-2506
Qwen/Qwen2.5-Omni-7B
Qwen/Qwen3-Omni-30B-A3B-Instruct
openai/whisper-medium
openai/whisper-large-v3
Qwen/Qwen3-Embedding-8B
Qwen3-VL-Embedding-2B/8B follow the guide in here
BAAI/bge-m3
BAAI/bge-large-en-v1.5
Qwen/Qwen3-Reranker-8B
Qwen3-VL-Reranker-2B/8B follow the guide in here
BAAI/bge-reranker-large
BAAI/bge-reranker-v2-m3 @sirwang 等你测试反馈
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@terry 看怎么看了吧。 如果 文生图、文生视频、图生视频、 文生语音、图片反推、视频反推这几个都有相对较好的解决方案。INTEL的卡内存大，省电，最重要的还便宜的话。老大你是否觉得有够买欲望？ 比如说32G的这个内存在1W块左右。
O。这个单张卡最高290瓦的电。
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@sirwang 我1万块为什么不买AI Pro R9700，我不需要研究任何东西，直接弄回来就能跑，说实话，我宁可多花点钱上4080S 32G，其实我也折腾xtx，纯粹是因为想弄点素材，但是没想到这卡是真好用。
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系统 取消固定了该主题
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OK。回来汇报来了。 四张卡都驱起来了。机器有256G内存，一张卡分64G。 前三张运行comfyui。后一张运行qwen3.6-27B. 测试大模型压力用的4并发。 脚本和结果如下：
import urllib.request import json import concurrent.futures import time URL = "http://127.0.0.1:8091/v1/chat/completions" HEADERS = {"Content-Type": "application/json"} # 模拟长文本生成请求 DATA = { "model": "/model", "messages": [{"role": "user", "content": "请写一篇800字的科幻小说，描述人类第一次登陆木星的场景。"}], "max_tokens": 1000, "temperature": 0.8 } def send_request(req_id): req = urllib.request.Request(URL, headers=HEADERS, data=json.dumps(DATA).encode('utf-8')) start_time = time.time() try: with urllib.request.urlopen(req) as response: res = json.loads(response.read().decode('utf-8')) tokens = res['usage']['completion_tokens'] cost_time = time.time() - start_time print(f"请求 {req_id} 完成 | 耗时: {cost_time:.2f}s | 生成 Token: {tokens} | 速度: {tokens/cost_time:.2f} tokens/s") except Exception as e: print(f"请求 {req_id} 失败: {e}") # 设置并发数，从 2 开始，逐步改成 4, 8, 16 试试极限 CONCURRENCY = 4 print(f"--- 开始 vLLM 并发压测 | 并发数: {CONCURRENCY} ---") with concurrent.futures.ThreadPoolExecutor(max_workers=CONCURRENCY) as executor: # 一次性发射 20 个请求排队 executor.map(send_request, range(20))以下是运行截图：
我画红线的是第4张卡运行vllm qwen3.6-27b的卡。
下边白底的这个是docker 的日志截图。
感觉还是相当稳的。 工作室和个人用，够了。 comfyui 我去找个‘公平’的测试方法。或者大家有啥测试方法不？ -
为了方便大家测试，我把流共享出来：
{ "id": "803716fc-9d9d-4d02-817c-855cdd6b4855", "revision": 0, "last_node_id": 27, "last_link_id": 30, "nodes": [ { "id": 2, "type": "FluxKontextMultiReferenceLatentMethod", "pos": [ 797.1906256982577, 12.11786329545784 ], "size": [ 309.6734375, 70 ], "flags": {}, "order": 15, "mode": 0, "inputs": [ { "label": "条件", "name": "conditioning", "type": "CONDITIONING", "link": 2 }, { "label": "参考Latent方法", "name": "reference_latents_method", "type": "COMBO", "widget": { "name": "reference_latents_method" }, "link": null } ], "outputs": [ { "label": "条件", "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 13 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "FluxKontextMultiReferenceLatentMethod", "ue_properties": { "widget_ue_connectable": { "reference_latents_method": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65 }, "widgets_values": [ "index_timestep_zero" ], "color": "#222", "bgcolor": "#000" }, { "id": 3, "type": "FluxKontextMultiReferenceLatentMethod", "pos": [ 797.1906256982577, -117.88213670454216 ], "size": [ 309.6734375, 70 ], "flags": {}, "order": 16, "mode": 0, "inputs": [ { "label": "条件", "name": "conditioning", "type": "CONDITIONING", "link": 3 }, { "label": "参考Latent方法", "name": "reference_latents_method", "type": "COMBO", "widget": { "name": "reference_latents_method" }, "link": null } ], "outputs": [ { "label": "条件", "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 12 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "FluxKontextMultiReferenceLatentMethod", "ue_properties": { "widget_ue_connectable": { "reference_latents_method": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65 }, "widgets_values": [ "index_timestep_zero" ], "color": "#222", "bgcolor": "#000" }, { "id": 4, "type": "CFGNorm", "pos": [ 807.1906256982578, -247.88213670454212 ], "size": [ 270, 68.33333333333334 ], "flags": {}, "order": 17, "mode": 0, "inputs": [ { "label": "模型", "name": "model", "type": "MODEL", "link": 4 }, { "label": "强度", "name": "strength", "type": "FLOAT", "widget": { "name": "strength" }, "link": null } ], "outputs": [ { "label": "修正后的模型", "name": "patched_model", "type": "MODEL", "links": [ 11 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "CFGNorm", "ue_properties": { "widget_ue_connectable": { "strength": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ 1 ], "color": "#332922", "bgcolor": "#593930" }, { "id": 17, "type": "UNETLoader", "pos": [ -145.99967296522877, -365.28072730924794 ], "size": [ 412.4183876274179, 93.12632424766274 ], "flags": {}, "order": 0, "mode": 0, "inputs": [ { "label": "UNET名称", "name": "unet_name", "type": "COMBO", "widget": { "name": "unet_name" }, "link": null }, { "label": "剪枝类型", "name": "weight_dtype", "type": "COMBO", "widget": { "name": "weight_dtype" }, "link": null } ], "outputs": [ { "label": "模型", "name": "MODEL", "type": "MODEL", "slot_index": 0, "links": [ 23 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "UNETLoader", "ue_properties": { "widget_ue_connectable": { "unet_name": true, "weight_dtype": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "models": [ { "name": "qwen_image_edit_2511_bf16.safetensors", "url": "https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_edit_2511_bf16.safetensors", "directory": "diffusion_models" } ], "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ "qwen_image_edit_2511_fp8mixed.safetensors", "default" ], "color": "#332922", "bgcolor": "#593930" }, { "id": 16, "type": "LoraLoaderModelOnly", "pos": [ 339.08373304272516, -365.4385152699498 ], "size": [ 396.1328125, 96.66666666666667 ], "flags": {}, "order": 8, "mode": 0, "inputs": [ { "label": "模型", "name": "model", "type": "MODEL", "link": 23 }, { "label": "LoRA名称", "name": "lora_name", "type": "COMBO", "widget": { "name": "lora_name" }, "link": null }, { "label": "模型强度", "name": "strength_model", "type": "FLOAT", "widget": { "name": "strength_model" }, "link": null } ], "outputs": [ { "label": "模型", "name": "MODEL", "type": "MODEL", "links": [ 22 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "LoraLoaderModelOnly", "ue_properties": { "widget_ue_connectable": { "lora_name": true, "strength_model": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "models": [ { "name": "Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors", "url": "https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning/resolve/main/Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors", "directory": "loras" } ], "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65 }, "widgets_values": [ "角度切换（VNCSS）-qwen-image-edit-2511-multiple-angles-lora.safetensors", 1 ], "color": "#432", "bgcolor": "#653" }, { "id": 18, "type": "CLIPLoader", "pos": [ -142.2511206355773, -201.03371333749183 ], "size": [ 396.1328125, 125 ], "flags": {}, "order": 1, "mode": 0, "inputs": [ { "label": "CLIP名称", "name": "clip_name", "type": "COMBO", "widget": { "name": "clip_name" }, "link": null }, { "label": "类型", "name": "type", "type": "COMBO", "widget": { "name": "type" }, "link": null } ], "outputs": [ { "label": "CLIP", "name": "CLIP", "type": "CLIP", "links": [ 5, 18 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "CLIPLoader", "ue_properties": { "widget_ue_connectable": { "clip_name": true, "type": true, "device": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "models": [ { "name": "qwen_2.5_vl_7b_fp8_scaled.safetensors", "url": "https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors", "directory": "text_encoders" } ], "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ "qwen_2.5_vl_7b_fp8_scaled.safetensors", "qwen_image", "default" ], "color": "#332922", "bgcolor": "#593930" }, { "id": 14, "type": "VAELoader", "pos": [ -146.39059612263827, -17.514527994231976 ], "size": [ 396.1328125, 68.33333333333334 ], "flags": {}, "order": 2, "mode": 0, "inputs": [ { "label": "vae名称", "name": "vae_name", "type": "COMBO", "widget": { "name": "vae_name" }, "link": null } ], "outputs": [ { "name": "VAE", "type": "VAE", "slot_index": 0, "links": [ 6, 9, 16, 19 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "VAELoader", "ue_properties": { "widget_ue_connectable": { "vae_name": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "models": [ { "name": "qwen_image_vae.safetensors", "url": "https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors", "directory": "vae" } ], "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ "qwen_image_vae.safetensors" ], "color": "#332922", "bgcolor": "#593930" }, { "id": 8, "type": "FluxKontextImageScale", "pos": [ -133.49182202879047, 560.4714628108627 ], "size": [ 377.0828198681851, 37.03860129882946 ], "flags": {}, "order": 9, "mode": 0, "inputs": [ { "label": "图像", "name": "image", "type": "IMAGE", "link": 10 } ], "outputs": [ { "label": "图像", "name": "IMAGE", "type": "IMAGE", "links": [ 7, 8, 20 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "FluxKontextImageScale", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [], "color": "#332922", "bgcolor": "#593930" }, { "id": 15, "type": "LoraLoaderModelOnly", "pos": [ 347.0952420840532, -220.09228397794982 ], "size": [ 396.1328125, 96.66666666666667 ], "flags": {}, "order": 10, "mode": 0, "inputs": [ { "label": "模型", "name": "model", "type": "MODEL", "link": 22 }, { "label": "LoRA名称", "name": "lora_name", "type": "COMBO", "widget": { "name": "lora_name" }, "link": null }, { "label": "模型强度", "name": "strength_model", "type": "FLOAT", "widget": { "name": "strength_model" }, "link": null } ], "outputs": [ { "label": "模型", "name": "MODEL", "type": "MODEL", "links": [ 1 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "LoraLoaderModelOnly", "ue_properties": { "widget_ue_connectable": { "lora_name": true, "strength_model": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "models": [ { "name": "Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors", "url": "https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning/resolve/main/Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors", "directory": "loras" } ], "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ "Qwen-Image-Edit-2511-Lightning-4steps-V1.0-fp32.safetensors", 1 ], "color": "#332922", "bgcolor": "#593930" }, { "id": 5, "type": "TextEncodeQwenImageEditPlus", "pos": [ 354.4459050818072, 251.866217681473 ], "size": [ 388.2640212658655, 214.48069935058538 ], "flags": {}, "order": 11, "mode": 0, "inputs": [ { "label": "CLIP", "name": "clip", "type": "CLIP", "link": 5 }, { "label": "VAE", "name": "vae", "shape": 7, "type": "VAE", "link": 6 }, { "label": "图像1", "name": "image1", "shape": 7, "type": "IMAGE", "link": 7 }, { "label": "图像2", "name": "image2", "shape": 7, "type": "IMAGE", "link": null }, { "label": "图像3", "name": "image3", "shape": 7, "type": "IMAGE", "link": null }, { "label": "提示词", "name": "prompt", "type": "STRING", "widget": { "name": "prompt" }, "link": null } ], "outputs": [ { "label": "条件", "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 2 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "TextEncodeQwenImageEditPlus", "ue_properties": { "widget_ue_connectable": { "prompt": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65 }, "widgets_values": [ "" ], "color": "#322", "bgcolor": "#533" }, { "id": 7, "type": "VAEEncode", "pos": [ 354.7124804040489, 524.2547847261422 ], "size": [ 384.81499821657553, 60 ], "flags": {}, "order": 12, "mode": 0, "inputs": [ { "label": "图像", "name": "pixels", "type": "IMAGE", "link": 8 }, { "label": "VAE", "name": "vae", "type": "VAE", "link": 9 } ], "outputs": [ { "label": "Latent", "name": "LATENT", "type": "LATENT", "links": [ 14 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "VAEEncode", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [], "color": "#332922", "bgcolor": "#593930" }, { "id": 1, "type": "ModelSamplingAuraFlow", "pos": [ 807.1906256982578, -357.88213670454206 ], "size": [ 270, 68.33333333333334 ], "flags": {}, "order": 14, "mode": 0, "inputs": [ { "label": "模型", "name": "model", "type": "MODEL", "link": 1 }, { "label": "偏移", "name": "shift", "type": "FLOAT", "widget": { "name": "shift" }, "link": null } ], "outputs": [ { "label": "模型", "name": "MODEL", "type": "MODEL", "links": [ 4 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "ModelSamplingAuraFlow", "ue_properties": { "widget_ue_connectable": { "shift": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ 3.1 ], "color": "#332922", "bgcolor": "#593930" }, { "id": 9, "type": "KSampler", "pos": [ 1140.647653458271, -367.5409128410178 ], "size": [ 286.8991258117685, 486 ], "flags": {}, "order": 18, "mode": 0, "inputs": [ { "label": "模型", "name": "model", "type": "MODEL", "link": 11 }, { "label": "正面条件", "name": "positive", "type": "CONDITIONING", "link": 12 }, { "label": "负面条件", "name": "negative", "type": "CONDITIONING", "link": 13 }, { "label": "Latent", "name": "latent_image", "type": "LATENT", "link": 14 }, { "label": "随机种", "name": "seed", "type": "INT", "widget": { "name": "seed" }, "link": null }, { "label": "步数", "name": "steps", "type": "INT", "widget": { "name": "steps" }, "link": null }, { "label": "CFG", "name": "cfg", "type": "FLOAT", "widget": { "name": "cfg" }, "link": null }, { "label": "采样器", "name": "sampler_name", "type": "COMBO", "widget": { "name": "sampler_name" }, "link": null }, { "label": "调度器", "name": "scheduler", "type": "COMBO", "widget": { "name": "scheduler" }, "link": null }, { "label": "降噪", "name": "denoise", "type": "FLOAT", "widget": { "name": "denoise" }, "link": null } ], "outputs": [ { "label": "Latent", "name": "LATENT", "type": "LATENT", "links": [ 15 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "KSampler", "ue_properties": { "widget_ue_connectable": { "seed": true, "steps": true, "cfg": true, "sampler_name": true, "scheduler": true, "denoise": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ 173815537092855, "randomize", 4, 1, "euler", "simple", 1 ], "color": "#332922", "bgcolor": "#593930" }, { "id": 10, "type": "VAEDecode", "pos": [ 835.9280787755798, 137.81632044395135 ], "size": [ 255.0718204517343, 46 ], "flags": { "collapsed": false }, "order": 19, "mode": 0, "inputs": [ { "label": "Latent", "name": "samples", "type": "LATENT", "link": 15 }, { "label": "VAE", "name": "vae", "type": "VAE", "link": 16 } ], "outputs": [ { "label": "图像", "name": "IMAGE", "type": "IMAGE", "slot_index": 0, "links": [ 17, 29 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "VAEDecode", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [], "color": "#332922", "bgcolor": "#593930" },
貌似不行，那就再开一个贴再贴一半吧。 我没有权限上传文件，只能贴代码了。
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请把俩代码合一块。就可以了。
{ "id": 26, "type": "SaveImage", "pos": [ 1145.1501729206636, 195.07454751045992 ], "size": [ 267.9266338657344, 433.279270302052 ], "flags": {}, "order": 21, "mode": 0, "inputs": [ { "label": "图像组", "name": "images", "type": "IMAGE", "link": 29 }, { "label": "文件名前缀", "name": "filename_prefix", "type": "STRING", "widget": { "name": "filename_prefix" }, "link": null } ], "outputs": [], "properties": { "cnr_id": "comfy-core", "ver": "0.6.0", "Node name for S&R": "SaveImage", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.2" }, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ "ComfyUI" ], "color": "#332922", "bgcolor": "#593930" }, { "id": 11, "type": "PreviewImage", "pos": [ 1487.4226159090695, -382.86645688700804 ], "size": [ 861.0544444444449, 1199.7606666666666 ], "flags": {}, "order": 20, "mode": 0, "inputs": [ { "label": "图像组", "name": "images", "type": "IMAGE", "link": 17 } ], "outputs": [], "properties": { "cnr_id": "comfy-core", "ver": "0.6.0", "Node name for S&R": "PreviewImage", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.2", "input_ue_unconnectable": {} }, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [], "color": "#332922", "bgcolor": "#593930" }, { "id": 25, "type": "Note", "pos": [ 2890.282933565041, -663.9119545246833 ], "size": [ 421.42547299979583, 1472.8439775316037 ], "flags": {}, "order": 3, "mode": 0, "inputs": [], "outputs": [], "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.2", "input_ue_unconnectable": {} } }, "widgets_values": [ "正面视图低角度特写：<sks> front view low-angle shot close-up\n\n右前侧视图低角度特写：<sks> front-right quarter view low-angle shot close-up\n\n右侧视图低角度特写：<sks> right side view low-angle shot close-up\n\n右后侧视图低角度特写：<sks> back-right quarter view low-angle shot close-up\n\n背面视图低角度特写：<sks> back view low-angle shot close-up\n\n左后侧视图低角度特写：<sks> back-left quarter view low-angle shot close-up\n\n左侧视图低角度特写：<sks> left side view low-angle shot close-up\n\n左前侧视图低角度特写：<sks> front-left quarter view low-angle shot close-up\n\n正面视图平视特写：<sks> front view eye-level shot close-up\n\n右前侧视图平视特写：<sks> front-right quarter view eye-level shot close-up\n\n右侧视图平视特写：<sks> right side view eye-level shot close-up\n\n右后侧视图平视特写：<sks> back-right quarter view eye-level shot close-up\n\n背面视图平视特写：<sks> back view eye-level shot close-up\n\n左后侧视图平视特写：<sks> back-left quarter view eye-level shot close-up\n\n左侧视图平视特写：<sks> left side view eye-level shot close-up\n\n左前侧视图平视特写：<sks> front-left quarter view eye-level shot close-up\n\n正面视图高位拍摄特写：<sks> front view elevated shot close-up\n\n右前侧视图高位拍摄特写：<sks> front-right quarter view elevated shot close-up\n\n右侧视图高位拍摄特写：<sks> right side view elevated shot close-up\n\n右后侧视图高位拍摄特写：<sks> back-right quarter view elevated shot close-up\n\n背面视图高位拍摄特写：<sks> back view elevated shot close-up\n\n左后侧视图高位拍摄特写：<sks> back-left quarter view elevated shot close-up\n\n左侧视图高位拍摄特写：<sks> left side view elevated shot close-up\n\n左前侧视图高位拍摄特写：<sks> front-left quarter view elevated shot close-up\n\n正面视图高角度特写：<sks> front view high-angle shot close-up\n\n右前侧视图高角度特写：<sks> front-right quarter view high-angle shot close-up\n\n右侧视图高角度特写：<sks> right side view high-angle shot close-up\n\n右后侧视图高角度特写：<sks> back-right quarter view high-angle shot close-up\n\n背面视图高角度特写：<sks> back view high-angle shot close-up\n\n左后侧视图高角度特写：<sks> back-left quarter view high-angle shot close-up\n\n左侧视图高角度特写：<sks> left side view high-angle shot close-up\n\n左前侧视图高角度特写：<sks> front-left quarter view high-angle shot close-up\n\n正面视图低角度中景：<sks> front view low-angle shot medium shot\n\n右前侧视图低角度中景：<sks> front-right quarter view low-angle shot medium shot\n\n右侧视图低角度中景：<sks> right side view low-angle shot medium shot\n\n右后侧视图低角度中景：<sks> back-right quarter view low-angle shot medium shot\n\n背面视图低角度中景：<sks> back view low-angle shot medium shot\n\n左后侧视图低角度中景：<sks> back-left quarter view low-angle shot medium shot\n\n左侧视图低角度中景：<sks> left side view low-angle shot medium shot\n\n左前侧视图低角度中景：<sks> front-left quarter view low-angle shot medium shot\n\n正面视图平视中景：<sks> front view eye-level shot medium shot\n\n右前侧视图平视中景：<sks> front-right quarter view eye-level shot medium shot\n\n右侧视图平视中景：<sks> right side view eye-level shot medium shot\n\n右后侧视图平视中景：<sks> back-right quarter view eye-level shot medium shot\n\n背面视图平视中景：<sks> back view eye-level shot medium shot\n\n左后侧视图平视中景：<sks> back-left quarter view eye-level shot medium shot\n\n左侧视图平视中景：<sks> left side view eye-level shot medium shot\n\n左前侧视图平视中景：<sks> front-left quarter view eye-level shot medium shot\n\n正面视图高位拍摄中景：<sks> front view elevated shot medium shot\n\n右前侧视图高位拍摄中景：<sks> front-right quarter view elevated shot medium shot\n\n右侧视图高位拍摄中景：<sks> right side view elevated shot medium shot\n\n右后侧视图高位拍摄中景：<sks> back-right quarter view elevated shot medium shot\n\n背面视图高位拍摄中景：<sks> back view elevated shot medium shot\n\n左后侧视图高位拍摄中景：<sks> back-left quarter view elevated shot medium shot\n\n左侧视图高位拍摄中景：<sks> left side view elevated shot medium shot\n\n左前侧视图高位拍摄中景：<sks> front-left quarter view elevated shot medium shot\n\n正面视图高角度中景：<sks> front view high-angle shot medium shot\n\n右前侧视图高角度中景：<sks> front-right quarter view high-angle shot medium shot\n\n右侧视图高角度中景：<sks> right side view high-angle shot medium shot\n\n右后侧视图高角度中景：<sks> back-right quarter view high-angle shot medium shot\n\n背面视图高角度中景：<sks> back view high-angle shot medium shot\n\n左后侧视图高角度中景：<sks> back-left quarter view high-angle shot medium shot\n\n左侧视图高角度中景：<sks> left side view high-angle shot medium shot\n\n左前侧视图高角度中景：<sks> front-left quarter view high-angle shot medium shot\n\n正面视图低角度广角：<sks> front view low-angle shot wide shot\n\n右前侧视图低角度广角：<sks> front-right quarter view low-angle shot wide shot\n\n右侧视图低角度广角：<sks> right side view low-angle shot wide shot\n\n右后侧视图低角度广角：<sks> back-right quarter view low-angle shot wide shot\n\n背面视图低角度广角：<sks> back view low-angle shot wide shot\n\n左后侧视图低角度广角：<sks> back-left quarter view low-angle shot wide shot\n\n左侧视图低角度广角：<sks> left side view low-angle shot wide shot\n\n左前侧视图低角度广角：<sks> front-left quarter view low-angle shot wide shot" ], "color": "#223", "bgcolor": "#335" }, { "id": 27, "type": "Note", "pos": [ -1009.7430949133999, -667.218084639018 ], "size": [ 3344.867777777771, 172.79096969696934 ], "flags": {}, "order": 4, "mode": 0, "inputs": [], "outputs": [], "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "可以使用comfuyi-lumi-batcher 来跑各个角度的，一下子跑出去90条。\n在这个流里，直接换位置，也就是把位置选成节点19，之后把参数选成左边复制的提示信息就行. william" ], "color": "#232", "bgcolor": "#353" }, { "id": 20, "type": "Note", "pos": [ 2392.2425113410113, -661.9303860055464 ], "size": [ 466.503515625, 1468.5173727560402 ], "flags": {}, "order": 5, "mode": 0, "inputs": [], "outputs": [], "title": "All prompt possible for the Lora Qwen image edit multiple angles", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.2", "input_ue_unconnectable": {} } }, "widgets_values": [ "<sks> front view low-angle shot close-up\n<sks> front-right quarter view low-angle shot close-up\n<sks> right side view low-angle shot close-up\n<sks> back-right quarter view low-angle shot close-up\n<sks> back view low-angle shot close-up\n<sks> back-left quarter view low-angle shot close-up\n<sks> left side view low-angle shot close-up\n<sks> front-left quarter view low-angle shot close-up\n<sks> front view eye-level shot close-up\n<sks> front-right quarter view eye-level shot close-up\n<sks> right side view eye-level shot close-up\n<sks> back-right quarter view eye-level shot close-up\n<sks> back view eye-level shot close-up\n<sks> back-left quarter view eye-level shot close-up\n<sks> left side view eye-level shot close-up\n<sks> front-left quarter view eye-level shot close-up\n<sks> front view elevated shot close-up\n<sks> front-right quarter view elevated shot close-up\n<sks> right side view elevated shot close-up\n<sks> back-right quarter view elevated shot close-up\n<sks> back view elevated shot close-up\n<sks> back-left quarter view elevated shot close-up\n<sks> left side view elevated shot close-up\n<sks> front-left quarter view elevated shot close-up\n<sks> front view high-angle shot close-up\n<sks> front-right quarter view high-angle shot close-up\n<sks> right side view high-angle shot close-up\n<sks> back-right quarter view high-angle shot close-up\n<sks> back view high-angle shot close-up\n<sks> back-left quarter view high-angle shot close-up\n<sks> left side view high-angle shot close-up\n<sks> front-left quarter view high-angle shot close-up\n<sks> front view low-angle shot medium shot\n<sks> front-right quarter view low-angle shot medium shot\n<sks> right side view low-angle shot medium shot\n<sks> back-right quarter view low-angle shot medium shot\n<sks> back view low-angle shot medium shot\n<sks> back-left quarter view low-angle shot medium shot\n<sks> left side view low-angle shot medium shot\n<sks> front-left quarter view low-angle shot medium shot\n<sks> front view eye-level shot medium shot\n<sks> front-right quarter view eye-level shot medium shot\n<sks> right side view eye-level shot medium shot\n<sks> back-right quarter view eye-level shot medium shot\n<sks> back view eye-level shot medium shot\n<sks> back-left quarter view eye-level shot medium shot\n<sks> left side view eye-level shot medium shot\n<sks> front-left quarter view eye-level shot medium shot\n<sks> front view elevated shot medium shot\n<sks> front-right quarter view elevated shot medium shot\n<sks> right side view elevated shot medium shot\n<sks> back-right quarter view elevated shot medium shot\n<sks> back view elevated shot medium shot\n<sks> back-left quarter view elevated shot medium shot\n<sks> left side view elevated shot medium shot\n<sks> front-left quarter view elevated shot medium shot\n<sks> front view high-angle shot medium shot\n<sks> front-right quarter view high-angle shot medium shot\n<sks> right side view high-angle shot medium shot\n<sks> back-right quarter view high-angle shot medium shot\n<sks> back view high-angle shot medium shot\n<sks> back-left quarter view high-angle shot medium shot\n<sks> left side view high-angle shot medium shot\n<sks> front-left quarter view high-angle shot medium shot\n<sks> front view low-angle shot wide shot\n<sks> front-right quarter view low-angle shot wide shot\n<sks> right side view low-angle shot wide shot\n<sks> back-right quarter view low-angle shot wide shot\n<sks> back view low-angle shot wide shot\n<sks> back-left quarter view low-angle shot wide shot\n<sks> left side view low-angle shot wide shot\n<sks> front-left quarter view low-angle shot wide shot\n<sks> front view eye-level shot wide shot\n<sks> front-right quarter view eye-level shot wide shot\n<sks> right side view eye-level shot wide shot\n<sks> back-right quarter view eye-level shot wide shot\n<sks> back view eye-level shot wide shot\n<sks> back-left quarter view eye-level shot wide shot\n<sks> left side view eye-level shot wide shot\n<sks> front-left quarter view eye-level shot wide shot\n<sks> front view elevated shot wide shot\n<sks> front-right quarter view elevated shot wide shot\n<sks> right side view elevated shot wide shot\n<sks> back-right quarter view elevated shot wide shot\n<sks> back view elevated shot wide shot\n<sks> back-left quarter view elevated shot wide shot\n<sks> left side view elevated shot wide shot\n<sks> front-left quarter view elevated shot wide shot\n<sks> front view high-angle shot wide shot\n<sks> front-right quarter view high-angle shot wide shot\n<sks> right side view high-angle shot wide shot\n<sks> back-right quarter view high-angle shot wide shot\n<sks> back view high-angle shot wide shot\n<sks> back-left quarter view high-angle shot wide shot\n<sks> left side view high-angle shot wide shot\n<sks> front-left quarter view high-angle shot wide shot" ], "color": "#232", "bgcolor": "#353" }, { "id": 13, "type": "TextEncodeQwenImageEditPlus", "pos": [ 346.3903358490907, -56.08507473664949 ], "size": [ 400.4109260819468, 258.660770021565 ], "flags": {}, "order": 13, "mode": 0, "inputs": [ { "label": "CLIP", "name": "clip", "type": "CLIP", "link": 18 }, { "label": "VAE", "name": "vae", "shape": 7, "type": "VAE", "link": 19 }, { "label": "图像1", "name": "image1", "shape": 7, "type": "IMAGE", "link": 20 }, { "label": "图像2", "name": "image2", "shape": 7, "type": "IMAGE", "link": null }, { "label": "图像3", "name": "image3", "shape": 7, "type": "IMAGE", "link": null }, { "label": "提示词", "name": "prompt", "type": "STRING", "widget": { "name": "prompt" }, "link": 30 } ], "outputs": [ { "label": "条件", "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 3 ] } ], "title": "TextEncodeQwenImageEditPlus (Positive)", "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "TextEncodeQwenImageEditPlus", "ue_properties": { "widget_ue_connectable": { "prompt": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65 }, "widgets_values": [ "<sks> front view low-angle shot close-up" ], "color": "#232", "bgcolor": "#353" }, { "id": 19, "type": "VNCCS_VisualPositionControl", "pos": [ -135.64643889289317, 113.93573315518134 ], "size": [ 377.25527938354924, 400.69737743530504 ], "flags": {}, "order": 6, "mode": 0, "inputs": [], "outputs": [ { "name": "prompt", "type": "STRING", "links": [ 30 ] } ], "properties": { "cnr_id": "vnccs-utils", "ver": "e8899e8fda5e72744198efecdc6f74f7d88a3b6a", "Node name for S&R": "VNCCS_VisualPositionControl", "ue_properties": { "widget_ue_connectable": { "camera_data": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" } }, "widgets_values": [ "{\"azimuth\":225,\"elevation\":-30,\"distance\":\"close-up\",\"include_trigger\":true}", "" ], "color": "#332922", "bgcolor": "#593930" }, { "id": 12, "type": "LoadImage", "pos": [ -1045.7126666666695, -374.68955555555544 ], "size": [ 850, 1220 ], "flags": {}, "order": 7, "mode": 0, "inputs": [ { "label": "图像", "name": "image", "type": "COMBO", "widget": { "name": "image" }, "link": null }, { "label": "上传", "name": "upload", "type": "IMAGEUPLOAD", "widget": { "name": "upload" }, "link": null } ], "outputs": [ { "label": "图像", "name": "IMAGE", "type": "IMAGE", "links": [ 10 ] }, { "label": "遮罩", "name": "MASK", "type": "MASK", "links": null } ], "properties": { "cnr_id": "comfy-core", "ver": "0.5.1", "Node name for S&R": "LoadImage", "ue_properties": { "widget_ue_connectable": { "image": true, "upload": true }, "version": "7.5.2", "input_ue_unconnectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ttNbgOverride": { "color": "#332922", "bgcolor": "#593930", "groupcolor": "#b06634" }, "#sdppp_variant": "default", "#sdppp_simple_content": "canvas", "#sdppp_simple_mask": "canvas", "#sdppp_simple_boundary": "canvas", "#sdppp_label": "" }, "widgets_values": [ "微信图片_20260515114607_5418_3.png", "image" ], "color": "#332922", "bgcolor": "#593930" } ], "links": [ [ 1, 15, 0, 1, 0, "MODEL" ], [ 2, 5, 0, 2, 0, "CONDITIONING" ], [ 3, 13, 0, 3, 0, "CONDITIONING" ], [ 4, 1, 0, 4, 0, "MODEL" ], [ 5, 18, 0, 5, 0, "CLIP" ], [ 6, 14, 0, 5, 1, "VAE" ], [ 7, 8, 0, 5, 2, "IMAGE" ], [ 8, 8, 0, 7, 0, "IMAGE" ], [ 9, 14, 0, 7, 1, "VAE" ], [ 10, 12, 0, 8, 0, "IMAGE" ], [ 11, 4, 0, 9, 0, "MODEL" ], [ 12, 3, 0, 9, 1, "CONDITIONING" ], [ 13, 2, 0, 9, 2, "CONDITIONING" ], [ 14, 7, 0, 9, 3, "LATENT" ], [ 15, 9, 0, 10, 0, "LATENT" ], [ 16, 14, 0, 10, 1, "VAE" ], [ 17, 10, 0, 11, 0, "IMAGE" ], [ 18, 18, 0, 13, 0, "CLIP" ], [ 19, 14, 0, 13, 1, "VAE" ], [ 20, 8, 0, 13, 2, "IMAGE" ], [ 22, 16, 0, 15, 0, "MODEL" ], [ 23, 17, 0, 16, 0, "MODEL" ], [ 29, 10, 0, 26, 0, "IMAGE" ], [ 30, 19, 0, 13, 5, "STRING" ] ], "groups": [], "config": {}, "extra": { "workflowRendererVersion": "LG", "ue_links": [], "links_added_by_ue": [], "ds": { "scale": 0.40909090909091006, "offset": [ 1435.9227173859654, 918.2021927921285 ] }, "frontendVersion": "1.43.18", "VHS_latentpreview": false, "VHS_latentpreviewrate": 0, "VHS_MetadataImage": true, "VHS_KeepIntermediate": true }, "version": 0.4 } -
模型用的官方原版的模型，没有量化。 下载地址：https://huggingface.co/Qwen/Qwen3.6-27B/tree/main 一共 55.6G
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T terry 固定了该主题
