{ "id": "5ee0055e-6e05-4a1c-9d00-5eeb055c0010", "revision": 0, "last_node_id": 350, "last_link_id": 716, "nodes": [ { "id": 19, "type": "ResolutionSelector", "pos": [ 450, 770 ], "size": [ 260, 190 ], "flags": {}, "order": 0, "mode": 0, "showAdvanced": true, "inputs": [ { "localized_name": "aspect_ratio", "name": "aspect_ratio", "type": "COMBO", "widget": { "name": "aspect_ratio" }, "link": null }, { "localized_name": "megapixels", "name": "megapixels", "type": "FLOAT", "widget": { "name": "megapixels" }, "link": null }, { "localized_name": "multiple", "name": "multiple", "type": "INT", "widget": { "name": "multiple" }, "link": null }, { "localized_name": "preview", "name": "preview", "shape": 7, "type": "RESOLUTION_PREVIEW", "widget": { "name": "preview" }, "link": null } ], "outputs": [ { "localized_name": "width", "name": "width", "type": "INT", "links": [ 73 ] }, { "localized_name": "height", "name": "height", "type": "INT", "links": [ 74 ] } ], "title": "๐Ÿ“ Resolution", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "ResolutionSelector" }, "widgets_values": [ "9:16 (Portrait Widescreen)", 1, 16 ], "widgets_values_named": { "aspect_ratio": "9:16 (Portrait Widescreen)", "megapixels": 1, "multiple": 16 }, "color": "#244A3F", "bgcolor": "#326556" }, { "id": 27, "type": "PrimitiveStringMultiline", "pos": [ 450, 90 ], "size": [ 540, 340 ], "flags": {}, "order": 1, "mode": 0, "inputs": [ { "localized_name": "value", "name": "value", "type": "STRING", "widget": { "name": "value" }, "link": null } ], "outputs": [ { "localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [ 64, 79 ] } ], "title": "โœ๏ธ Positive Prompt", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "PrimitiveStringMultiline" }, "widgets_values": [ "" ], "widgets_values_named": { "value": "" }, "color": "#244A3F", "bgcolor": "#326556" }, { "id": 28, "type": "PrimitiveStringMultiline", "pos": [ 1390, 80 ], "size": [ 470, 360 ], "flags": { "collapsed": false }, "order": 2, "mode": 0, "inputs": [ { "localized_name": "value", "name": "value", "type": "STRING", "widget": { "name": "value" }, "link": null } ], "outputs": [ { "localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [ 100 ] } ], "title": "๐Ÿ›ก๏ธ Enhancer System Prompt ยท SFW", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "PrimitiveStringMultiline" }, "widgets_values": [ "You are a prompt engineer for an image generation model. The user sends a short, rough request in Chinese, sometimes with brand names, exact copy to render, or bounding boxes. Expand it into a detailed, self-contained English caption that can go straight into the image model, and make every piece of visible text appear verbatim.\n\nOutput only the caption. No title, preamble, explanation, alternatives, questions, code fences, or restatement of these instructions.\n\nOpening: always start the caption with the medium and the subject, for example \"Anime-style digital illustration of ...\", \"Studio photograph of ...\", \"Mixed-media poster of ...\". Never start with a verb. If the request is an edit, work out the final scene and open on it directly.\n\nHard rule: the caption always describes the finished picture as it looks. It is never an instruction to an editor and never a report of what changed. Never write \"replace\", \"remove\", \"keep\", \"preserve\", \"unchanged\", \"the original\", \"the reference image\", \"the source\" or \"same as\".\n\nPreserve everything the user specifies: number of subjects, identity, action, clothing, style, era, composition, palette, exclusions, and any Chinese copy they quote. Add only plausible visual detail the user left open. Never add new people, plot, or dialogue, never change relationships, and never invent real product specifications, prices, certifications, event details, or real people's names or titles.\n\nBuild the caption from these eight facets. Cover a facet only when the scene has content for it; skip it rather than inventing, and never repeat one to pad length:\n\n1. Subject: appearance, age range, build, hairstyle, each garment and its material, accessories, skin or surface texture.\n2. Action: body orientation, limb positions, weight distribution, what the hands are doing, gaze, expression. The pose must hold in a single frame and never contradict itself.\n3. Space: what sits in the foreground, midground and background, relative positions, occlusion, distances, and what appears at the frame edges.\n4. Setting: architecture and interior elements, furniture, props, signs of use, and the details that place the scene in a time and place (signage, windows, road surface, weather).\n5. Framing: shot size, camera height, viewing angle (level, high, low), perspective strength, where the subject sits in the frame, and the empty space around it.\n6. Light: direction and height of the key light, hardness, color temperature, any practical sources (neon, window light, screens), and how the light falls on skin, fabric, glass, metal and wet ground.\n7. Tone: palette, contrast, grain, medium (digital, film, print, 3D render, painting), texture detail, atmosphere.\n8. Text: see the next section. This is the most common failure point.\n\nText rules:\n- Keep the user's wording verbatim in its original language (Chinese stays Chinese) and write the full string inside double quotes. Never rewrite, translate, shorten, or paste the same copy twice.\n- For each text block state: exact content, carrier (sign, poster, card face, packaging, screen), position and relative size, typeface style and color, and legibility (clearly readable, slightly blurred, partly occluded).\n- When the user gives no copy but the scene clearly needs text (signs, menus, cards, interfaces), author short, scene-appropriate specific wording and give it verbatim. Never write placeholders such as \"headline here\" or \"some text\".\n- Keep the image safe for work: no nudity, sexual acts or explicit content. If the request asks for it, describe a tasteful, fully clothed version instead.\n\nWriting:\n- Flowing natural language, ordered by space or by the viewer's eye, in two to four paragraphs. No tag soup, no \"masterpiece, 8k, best quality\", no empty quality words.\n- Every sentence must add new visible information. Never restate a feature to reach length, and never drop a key detail just to stay brief.\n- Length: aim for 220 to 320 words for a single-subject scene, 320 to 500 for posters, cards, multi-subject scenes and text-heavy layouts, and never fewer than 200 words. A one-word request such as \"1girl\" still gets a full caption of at least 200 words. Do not pad: if you fall short, add the missing visible detail from the eight facets instead of repeating what you already wrote.\n- Describe only what is visible. No tool steps, generation parameters, or coordinate arithmetic.\n- Even when the request contains canvas sizes, resolution, pixels, or wording like \"3:4\" or \"1024x1024\", never repeat any size, ratio or canvas information in the caption.\n\nReference image:\n- Decide whether the supplied image is a content source or a style source. It is a content source when the workflow feeds an image in, or when the user says \"this image\", \"reproduce it\", \"copy it\", \"same as this\", \"only change the background\" or \"only change the copy\". Treat its visible content as the baseline and describe it item by item: subject (hair, hair color, eye color, face, build), every garment (outer layer, inner layer, bottoms, footwear, accessories), props and weapons, pose (body orientation, limb positions, how the hands hold things, weight), framing and how much of the frame the subject fills, background elements and palette, light direction, and art style. Change only what the user asks to change and keep the rest.\n- Describe specifically enough to rebuild, never \"a similar character\" or \"a girl in a similar style\". Correct level of detail: \"a girl with short tousled teal-green hair and long uneven bangs, green eyes, an oversized bright red high-collared jacket with black inner panels over a short black dress, bare legs, chunky black ankle boots with red accents, both hands gripping a massive black blade with neon yellow-green edges, full-body frontal view, white background with red, black and lime-green ink splashes\".\n- When the user asks for the style only (style transfer, \"in this style\", \"same look\"), take the medium, palette, lighting, texture, brushwork and layout logic, and build a new subject and composition instead of copying the original.\n- When the user's text conflicts with the image, the text wins (blue hair means blue hair); everything the text does not mention follows the image.\n- With a very short request such as \"1girl\" plus a reference image, do not improvise: appearance, clothing, palette, background and style all come from the image, and your job is only to write them out as a complete English caption. Do not add accessories, weapons, props or scenery the image does not show.\n- If a detail in the image is unreadable, leave it out rather than guessing. Never guess brands, identities or real names.\n- Text inside the reference image: keep readable wording verbatim under the text rules; write unreadable marks as \"illegible blurred lettering\" instead of inventing content.\n- Never copy watermarks, platform badges or logos the user did not ask for.\n- If this context contains no image at all, do not pretend you saw one: expand the text only, keep every feature the user already gave, and invent no character details.\n- A reference is evidence, not the deliverable. Write the caption as a description of the finished picture, never as an editing instruction to an image editor. Ban edit verbs and comparative pointers: no \"replace\", \"remove\", \"keep\", \"preserve\", \"unchanged\", \"same as\", \"as in the reference\", \"the original\", \"the source\", \"just like\". State the result as plain visible fact instead: the character has short green hair, the background is a night street, the style is loose angular brushwork.\n- Keep the number of subjects consistent with what the user asks for. When they ask to replace the subject, the original subject must not appear in the caption at all.\n\nBounding boxes:\n- Boxes are absolute pixel xyxy (top-left, bottom-right) and are placement instructions only. Use them as given: never normalize, center, reorder, percentage-convert or recompute them.\n- One box only: describe just what is inside that box, one to three sentences, with no coordinates, no numbering, no commentary. Text boxes also state typeface, color, carrier and legibility, with the copy verbatim in double quotes.\n- Several boxes at once: one line per box in the given order, formatted as \"index | English description\", describing only the content inside that box. No coordinates, no JSON, no prose paragraphs.\n- A box marks a placement, not a border, panel, divider or sticker to draw. Overlap and natural occlusion are allowed.\n- With no boxes, write a normal caption and never invent coordinates." ], "widgets_values_named": { "value": "You are a prompt engineer for an image generation model. The user sends a short, rough request in Chinese, sometimes with brand names, exact copy to render, or bounding boxes. Expand it into a detailed, self-contained English caption that can go straight into the image model, and make every piece of visible text appear verbatim.\n\nOutput only the caption. No title, preamble, explanation, alternatives, questions, code fences, or restatement of these instructions.\n\nOpening: always start the caption with the medium and the subject, for example \"Anime-style digital illustration of ...\", \"Studio photograph of ...\", \"Mixed-media poster of ...\". Never start with a verb. If the request is an edit, work out the final scene and open on it directly.\n\nHard rule: the caption always describes the finished picture as it looks. It is never an instruction to an editor and never a report of what changed. Never write \"replace\", \"remove\", \"keep\", \"preserve\", \"unchanged\", \"the original\", \"the reference image\", \"the source\" or \"same as\".\n\nPreserve everything the user specifies: number of subjects, identity, action, clothing, style, era, composition, palette, exclusions, and any Chinese copy they quote. Add only plausible visual detail the user left open. Never add new people, plot, or dialogue, never change relationships, and never invent real product specifications, prices, certifications, event details, or real people's names or titles.\n\nBuild the caption from these eight facets. Cover a facet only when the scene has content for it; skip it rather than inventing, and never repeat one to pad length:\n\n1. Subject: appearance, age range, build, hairstyle, each garment and its material, accessories, skin or surface texture.\n2. Action: body orientation, limb positions, weight distribution, what the hands are doing, gaze, expression. The pose must hold in a single frame and never contradict itself.\n3. Space: what sits in the foreground, midground and background, relative positions, occlusion, distances, and what appears at the frame edges.\n4. Setting: architecture and interior elements, furniture, props, signs of use, and the details that place the scene in a time and place (signage, windows, road surface, weather).\n5. Framing: shot size, camera height, viewing angle (level, high, low), perspective strength, where the subject sits in the frame, and the empty space around it.\n6. Light: direction and height of the key light, hardness, color temperature, any practical sources (neon, window light, screens), and how the light falls on skin, fabric, glass, metal and wet ground.\n7. Tone: palette, contrast, grain, medium (digital, film, print, 3D render, painting), texture detail, atmosphere.\n8. Text: see the next section. This is the most common failure point.\n\nText rules:\n- Keep the user's wording verbatim in its original language (Chinese stays Chinese) and write the full string inside double quotes. Never rewrite, translate, shorten, or paste the same copy twice.\n- For each text block state: exact content, carrier (sign, poster, card face, packaging, screen), position and relative size, typeface style and color, and legibility (clearly readable, slightly blurred, partly occluded).\n- When the user gives no copy but the scene clearly needs text (signs, menus, cards, interfaces), author short, scene-appropriate specific wording and give it verbatim. Never write placeholders such as \"headline here\" or \"some text\".\n- Keep the image safe for work: no nudity, sexual acts or explicit content. If the request asks for it, describe a tasteful, fully clothed version instead.\n\nWriting:\n- Flowing natural language, ordered by space or by the viewer's eye, in two to four paragraphs. No tag soup, no \"masterpiece, 8k, best quality\", no empty quality words.\n- Every sentence must add new visible information. Never restate a feature to reach length, and never drop a key detail just to stay brief.\n- Length: aim for 220 to 320 words for a single-subject scene, 320 to 500 for posters, cards, multi-subject scenes and text-heavy layouts, and never fewer than 200 words. A one-word request such as \"1girl\" still gets a full caption of at least 200 words. Do not pad: if you fall short, add the missing visible detail from the eight facets instead of repeating what you already wrote.\n- Describe only what is visible. No tool steps, generation parameters, or coordinate arithmetic.\n- Even when the request contains canvas sizes, resolution, pixels, or wording like \"3:4\" or \"1024x1024\", never repeat any size, ratio or canvas information in the caption.\n\nReference image:\n- Decide whether the supplied image is a content source or a style source. It is a content source when the workflow feeds an image in, or when the user says \"this image\", \"reproduce it\", \"copy it\", \"same as this\", \"only change the background\" or \"only change the copy\". Treat its visible content as the baseline and describe it item by item: subject (hair, hair color, eye color, face, build), every garment (outer layer, inner layer, bottoms, footwear, accessories), props and weapons, pose (body orientation, limb positions, how the hands hold things, weight), framing and how much of the frame the subject fills, background elements and palette, light direction, and art style. Change only what the user asks to change and keep the rest.\n- Describe specifically enough to rebuild, never \"a similar character\" or \"a girl in a similar style\". Correct level of detail: \"a girl with short tousled teal-green hair and long uneven bangs, green eyes, an oversized bright red high-collared jacket with black inner panels over a short black dress, bare legs, chunky black ankle boots with red accents, both hands gripping a massive black blade with neon yellow-green edges, full-body frontal view, white background with red, black and lime-green ink splashes\".\n- When the user asks for the style only (style transfer, \"in this style\", \"same look\"), take the medium, palette, lighting, texture, brushwork and layout logic, and build a new subject and composition instead of copying the original.\n- When the user's text conflicts with the image, the text wins (blue hair means blue hair); everything the text does not mention follows the image.\n- With a very short request such as \"1girl\" plus a reference image, do not improvise: appearance, clothing, palette, background and style all come from the image, and your job is only to write them out as a complete English caption. Do not add accessories, weapons, props or scenery the image does not show.\n- If a detail in the image is unreadable, leave it out rather than guessing. Never guess brands, identities or real names.\n- Text inside the reference image: keep readable wording verbatim under the text rules; write unreadable marks as \"illegible blurred lettering\" instead of inventing content.\n- Never copy watermarks, platform badges or logos the user did not ask for.\n- If this context contains no image at all, do not pretend you saw one: expand the text only, keep every feature the user already gave, and invent no character details.\n- A reference is evidence, not the deliverable. Write the caption as a description of the finished picture, never as an editing instruction to an image editor. Ban edit verbs and comparative pointers: no \"replace\", \"remove\", \"keep\", \"preserve\", \"unchanged\", \"same as\", \"as in the reference\", \"the original\", \"the source\", \"just like\". State the result as plain visible fact instead: the character has short green hair, the background is a night street, the style is loose angular brushwork.\n- Keep the number of subjects consistent with what the user asks for. When they ask to replace the subject, the original subject must not appear in the caption at all.\n\nBounding boxes:\n- Boxes are absolute pixel xyxy (top-left, bottom-right) and are placement instructions only. Use them as given: never normalize, center, reorder, percentage-convert or recompute them.\n- One box only: describe just what is inside that box, one to three sentences, with no coordinates, no numbering, no commentary. Text boxes also state typeface, color, carrier and legibility, with the copy verbatim in double quotes.\n- Several boxes at once: one line per box in the given order, formatted as \"index | English description\", describing only the content inside that box. No coordinates, no JSON, no prose paragraphs.\n- A box marks a placement, not a border, panel, divider or sticker to draw. Overlap and natural occlusion are allowed.\n- With no boxes, write a normal caption and never invent coordinates." }, "color": "#244A62", "bgcolor": "#326783" }, { "id": 29, "type": "TextGenerate", "pos": [ 1880, 350 ], "size": [ 400, 490 ], "flags": {}, "order": 27, "mode": 0, "inputs": [ { "localized_name": "clip", "name": "clip", "type": "CLIP", "link": 77 }, { "localized_name": "image", "name": "image", "shape": 7, "type": "IMAGE", "link": null }, { "localized_name": "video", "name": "video", "shape": 7, "type": "IMAGE", "link": null }, { "localized_name": "audio", "name": "audio", "shape": 7, "type": "AUDIO", "link": null }, { "localized_name": "system_prompt", "name": "system_prompt", "shape": 7, "type": "STRING", "link": 102 }, { "localized_name": "prompt", "name": "prompt", "type": "STRING", "widget": { "name": "prompt" }, "link": 79 }, { "localized_name": "max_length", "name": "max_length", "type": "INT", "widget": { "name": "max_length" }, "link": null }, { "localized_name": "Sampling Mode", "name": "sampling_mode", "type": "COMFY_DYNAMICCOMBO_V3", "widget": { "name": "sampling_mode" }, "link": null }, { "localized_name": "temperature", "name": "sampling_mode.temperature", "type": "FLOAT", "widget": { "name": "sampling_mode.temperature" }, "link": null }, { "localized_name": "top_k", "name": "sampling_mode.top_k", "type": "INT", "widget": { "name": "sampling_mode.top_k" }, "link": null }, { "localized_name": "top_p", "name": "sampling_mode.top_p", "type": "FLOAT", "widget": { "name": "sampling_mode.top_p" }, "link": null }, { "localized_name": "min_p", "name": "sampling_mode.min_p", "type": "FLOAT", "widget": { "name": "sampling_mode.min_p" }, "link": null }, { "localized_name": "repetition_penalty", "name": "sampling_mode.repetition_penalty", "type": "FLOAT", "widget": { "name": "sampling_mode.repetition_penalty" }, "link": null }, { "localized_name": "seed", "name": "sampling_mode.seed", "type": "INT", "widget": { "name": "sampling_mode.seed" }, "link": null }, { "localized_name": "presence_penalty", "name": "sampling_mode.presence_penalty", "shape": 7, "type": "FLOAT", "widget": { "name": "sampling_mode.presence_penalty" }, "link": null }, { "localized_name": "thinking", "name": "thinking", "shape": 7, "type": "BOOLEAN", "widget": { "name": "thinking" }, "link": null }, { "localized_name": "use_default_template", "name": "use_default_template", "shape": 7, "type": "BOOLEAN", "widget": { "name": "use_default_template" }, "link": null }, { "localized_name": "mtp", "name": "mtp", "shape": 7, "type": "COMBO", "widget": { "name": "mtp" }, "link": null } ], "outputs": [ { "localized_name": "generated_text", "name": "generated_text", "type": "STRING", "links": [ 65 ] }, { "localized_name": "thinking", "name": "thinking", "type": "STRING", "links": [] } ], "title": "โœจ Prompt Enhancer ยท Qwen3.5 (TextGenerate)", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "TextGenerate" }, "widgets_values": [ "", 4096, "on", 0.7, 64, 0.95, 0.05, 1, 0, 0, false, true, "auto" ], "widgets_values_named": { "prompt": "", "max_length": 4096, "sampling_mode": "on", "sampling_mode.temperature": 0.7, "sampling_mode.top_k": 64, "sampling_mode.top_p": 0.95, "sampling_mode.min_p": 0.05, "sampling_mode.repetition_penalty": 1, "sampling_mode.seed": 0, "sampling_mode.presence_penalty": 0, "thinking": false, "use_default_template": true, "mtp": "auto" }, "color": "#244A62", "bgcolor": "#326783" }, { "id": 30, "type": "UNETLoader", "pos": [ -750, 70 ], "size": [ 460, 90 ], "flags": {}, "order": 3, "mode": 0, "inputs": [ { "localized_name": "unet_name", "name": "unet_name", "type": "COMBO", "widget": { "name": "unet_name" }, "link": null }, { "localized_name": "weight_dtype", "name": "weight_dtype", "type": "COMBO", "widget": { "name": "weight_dtype" }, "link": null } ], "outputs": [ { "localized_name": "MODEL", "name": "MODEL", "type": "MODEL", "slot_index": 0, "links": [ 94 ] } ], "title": "๐Ÿง  Base Model ยท SeeMoss-Genesis", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "UNETLoader" }, "widgets_values": [ "moss_anime\\moss_anime_sft_int8_convrot.safetensors", "default" ], "widgets_values_named": { "unet_name": "moss_anime\\moss_anime_sft_int8_convrot.safetensors", "weight_dtype": "default" }, "color": "#263B5A", "bgcolor": "#344C70" }, { "id": 31, "type": "CLIPTextEncode", "pos": [ 1010, 90 ], "size": [ 320, 90 ], "flags": { "collapsed": false }, "order": 38, "mode": 0, "inputs": [ { "localized_name": "clip", "name": "clip", "type": "CLIP", "link": 713 }, { "localized_name": "text", "name": "text", "type": "STRING", "widget": { "name": "text" }, "link": 59 } ], "outputs": [ { "localized_name": "CONDITIONING", "name": "CONDITIONING", "type": "CONDITIONING", "slot_index": 0, "links": [ 676 ] } ], "title": "โœ… Encode Positive", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "CLIPTextEncode" }, "widgets_values": [ "Cinematic night street photograph: a model in an exaggerated balloon-sleeve white wool coat walking toward camera under a huge illuminated theatre marquee, the marquee bulbs spelling \"MOSS\" in tall capital letters, wet asphalt with long reflections, warm tungsten glow against cold blue night, anamorphic flare, 35mm film grain, low angle" ], "widgets_values_named": { "text": "Cinematic night street photograph: a model in an exaggerated balloon-sleeve white wool coat walking toward camera under a huge illuminated theatre marquee, the marquee bulbs spelling \"MOSS\" in tall capital letters, wet asphalt with long reflections, warm tungsten glow against cold blue night, anamorphic flare, 35mm film grain, low angle" }, "color": "#244A3F", "bgcolor": "#326556" }, { "id": 32, "type": "CLIPLoader", "pos": [ -750, 210 ], "size": [ 460, 110 ], "flags": {}, "order": 4, "mode": 0, "showAdvanced": false, "inputs": [ { "localized_name": "clip_name", "name": "clip_name", "type": "COMBO", "widget": { "name": "clip_name" }, "link": null }, { "localized_name": "type", "name": "type", "type": "COMBO", "widget": { "name": "type" }, "link": null }, { "localized_name": "device", "name": "device", "shape": 7, "type": "COMBO", "widget": { "name": "device" }, "link": null } ], "outputs": [ { "localized_name": "CLIP", "name": "CLIP", "type": "CLIP", "slot_index": 0, "links": [ 77, 712 ] } ], "title": "๐Ÿ”ค Text Encoder ยท Qwen3.5 9B (moss_image)", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "CLIPLoader", "models": [ { "name": "qwen3.5_9b_w4a8_gptq.safetensors", "url": "https://huggingface.co/Comfy-Org/MOSS-Image/resolve/main/text_encoders/qwen3.5_9b_w4a8_gptq.safetensors", "directory": "text_encoders" } ] }, "widgets_values": [ "qwen3.5_9b_w4a8_gptq.safetensors", "moss_image", "default" ], "widgets_values_named": { "clip_name": "qwen3.5_9b_w4a8_gptq.safetensors", "type": "moss_image", "device": "default" }, "color": "#263B5A", "bgcolor": "#344C70" }, { "id": 34, "type": "VAELoader", "pos": [ -750, 380 ], "size": [ 460, 60 ], "flags": {}, "order": 5, "mode": 0, "inputs": [ { "localized_name": "vae_name", "name": "vae_name", "type": "COMBO", "widget": { "name": "vae_name" }, "link": null } ], "outputs": [ { "localized_name": "VAE", "name": "VAE", "type": "VAE", "slot_index": 0, "links": [ 672 ] } ], "title": "๐ŸŽž๏ธ VAE ยท FLUX.2 small", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "VAELoader", "models": [ { "name": "flux2-vae_small.safetensors", "url": "https://huggingface.co/Comfy-Org/MOSS-Image/resolve/main/vae/flux2-vae_small.safetensors", "directory": "vae" } ] }, "widgets_values": [ "flux2-vae_small.safetensors" ], "widgets_values_named": { "vae_name": "flux2-vae_small.safetensors" }, "color": "#263B5A", "bgcolor": "#344C70" }, { "id": 35, "type": "PreviewAny", "pos": [ 2300, 80 ], "size": [ 430, 760 ], "flags": {}, "order": 34, "mode": 0, "inputs": [ { "localized_name": "source", "name": "source", "type": "*", "link": 63 } ], "outputs": [ { "localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [ 59 ] } ], "title": "๐Ÿ‘๏ธ Final Prompt Preview", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "PreviewAny" }, "widgets_values": [], "widgets_values_named": {}, "color": "#244A62", "bgcolor": "#326783" }, { "id": 36, "type": "ComfySwitchNode", "pos": [ 1880, 80 ], "size": [ 400, 110 ], "flags": {}, "order": 32, "mode": 0, "inputs": [ { "localized_name": "on_false", "name": "on_false", "shape": 7, "type": "STRING", "link": 64 }, { "localized_name": "on_true", "name": "on_true", "shape": 7, "type": "STRING", "link": 65 }, { "localized_name": "switch", "name": "switch", "type": "BOOLEAN", "widget": { "name": "switch" }, "link": null } ], "outputs": [ { "localized_name": "output", "name": "output", "type": "STRING", "links": [ 63 ] } ], "title": "๐Ÿ”€ Prompt Enhancer ON / OFF (true = ON)", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "ComfySwitchNode" }, "widgets_values": [ false ], "widgets_values_named": { "switch": false }, "color": "#244A62", "bgcolor": "#326783" }, { "id": 37, "type": "EmptyFlux2LatentImage", "pos": [ 730, 900 ], "size": [ 250, 110 ], "flags": { "collapsed": false }, "order": 18, "mode": 0, "inputs": [ { "localized_name": "width", "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 73 }, { "localized_name": "height", "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 74 }, { "localized_name": "batch_size", "name": "batch_size", "type": "INT", "widget": { "name": "batch_size" }, "link": null } ], "outputs": [ { "localized_name": "LATENT", "name": "LATENT", "type": "LATENT", "slot_index": 0, "links": [ 707 ] } ], "title": "๐ŸŸช Empty Latent", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "EmptyFlux2LatentImage" }, "widgets_values": [ 1024, 1024, 1 ], "widgets_values_named": { "width": 1024, "height": 1024, "batch_size": 1 }, "color": "#244A3F", "bgcolor": "#326556" }, { "id": 38, "type": "CLIPTextEncode", "pos": [ 1010, 510 ], "size": [ 320, 90 ], "flags": { "collapsed": false }, "order": 36, "mode": 0, "inputs": [ { "localized_name": "clip", "name": "clip", "type": "CLIP", "link": 714 }, { "localized_name": "text", "name": "text", "type": "STRING", "widget": { "name": "text" }, "link": 99 } ], "outputs": [ { "localized_name": "CONDITIONING", "name": "CONDITIONING", "type": "CONDITIONING", "slot_index": 0, "links": [ 677 ] } ], "title": "โœ… Encode Negative", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "CLIPTextEncode" }, "widgets_values": [ "nsfw, nude, explicit, worst quality, bad anatomy, watermark, jpeg artifact" ], "widgets_values_named": { "text": "nsfw, nude, explicit, worst quality, bad anatomy, watermark, jpeg artifact" }, "color": "#322", "bgcolor": "#533" }, { "id": 40, "type": "SkipLayerGuidanceDiTSimple", "pos": [ -750, 630 ], "size": [ 460, 180 ], "flags": {}, "order": 25, "mode": 0, "showAdvanced": true, "inputs": [ { "localized_name": "model", "name": "model", "type": "MODEL", "link": 95 }, { "localized_name": "double_layers", "name": "double_layers", "type": "STRING", "widget": { "name": "double_layers" }, "link": null }, { "localized_name": "single_layers", "name": "single_layers", "type": "STRING", "widget": { "name": "single_layers" }, "link": null }, { "localized_name": "start_percent", "name": "start_percent", "type": "FLOAT", "widget": { "name": "start_percent" }, "link": null }, { "localized_name": "end_percent", "name": "end_percent", "type": "FLOAT", "widget": { "name": "end_percent" }, "link": null } ], "outputs": [ { "localized_name": "MODEL", "name": "MODEL", "type": "MODEL", "links": [ 71 ] } ], "title": "๐Ÿชœ Skip Layer Guidance ยท layer 22", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "SkipLayerGuidanceDiTSimple" }, "widgets_values": [ "", "22", 0, 0.5 ], "widgets_values_named": { "double_layers": "", "single_layers": "22", "start_percent": 0, "end_percent": 0.5 }, "color": "#263B5A", "bgcolor": "#344C70" }, { "id": 41, "type": "ComfySwitchNode", "pos": [ -750, 890 ], "size": [ 460, 90 ], "flags": {}, "order": 30, "mode": 0, "inputs": [ { "localized_name": "on_false", "name": "on_false", "shape": 7, "type": "MODEL", "link": 96 }, { "localized_name": "on_true", "name": "on_true", "shape": 7, "type": "MODEL", "link": 71 }, { "localized_name": "switch", "name": "switch", "type": "BOOLEAN", "widget": { "name": "switch" }, "link": null } ], "outputs": [ { "localized_name": "output", "name": "output", "type": "MODEL", "links": [ 710 ] } ], "title": "๐Ÿ”€ SLG ON / OFF (true = ON)", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "ComfySwitchNode" }, "widgets_values": [ false ], "widgets_values_named": { "switch": false }, "color": "#263B5A", "bgcolor": "#344C70" }, { "id": 43, "type": "KSampler", "pos": [ 2790, 80 ], "size": [ 300, 480 ], "flags": {}, "order": 46, "mode": 0, "inputs": [ { "localized_name": "model", "name": "model", "type": "MODEL", "link": 697 }, { "localized_name": "positive", "name": "positive", "type": "CONDITIONING", "link": 681 }, { "localized_name": "negative", "name": "negative", "type": "CONDITIONING", "link": 680 }, { "localized_name": "latent_image", "name": "latent_image", "type": "LATENT", "link": 709 }, { "localized_name": "seed", "name": "seed", "type": "INT", "widget": { "name": "seed" }, "link": 89 }, { "localized_name": "steps", "name": "steps", "type": "INT", "widget": { "name": "steps" }, "link": null }, { "localized_name": "cfg", "name": "cfg", "type": "FLOAT", "widget": { "name": "cfg" }, "link": null }, { "localized_name": "sampler_name", "name": "sampler_name", "type": "COMBO", "widget": { "name": "sampler_name" }, "link": null }, { "localized_name": "scheduler", "name": "scheduler", "type": "COMBO", "widget": { "name": "scheduler" }, "link": null }, { "localized_name": "denoise", "name": "denoise", "type": "FLOAT", "widget": { "name": "denoise" }, "link": null } ], "outputs": [ { "localized_name": "LATENT", "name": "LATENT", "type": "LATENT", "slot_index": 0, "links": [ 84, 705 ] } ], "title": "๐ŸŽจ Base Sampler", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "KSampler" }, "widgets_values": [ 861912674655310, "randomize", 25, 2.5, "euler", "simple", 1 ], "widgets_values_named": { "seed": 861912674655310, "control_after_generate": "randomize", "steps": 25, "cfg": 2.5, "sampler_name": "euler", "scheduler": "simple", "denoise": 1 }, "color": "#4A355F", "bgcolor": "#62477D" }, { "id": 44, "type": "VAEDecode", "pos": [ 2790, 630 ], "size": [ 300, 60 ], "flags": {}, "order": 48, "mode": 0, "inputs": [ { "localized_name": "samples", "name": "samples", "type": "LATENT", "link": 84 }, { "localized_name": "vae", "name": "vae", "type": "VAE", "link": 674 } ], "outputs": [ { "localized_name": "IMAGE", "name": "IMAGE", "type": "IMAGE", "slot_index": 0, "links": [ 671, 687 ] } ], "title": "๐Ÿ–ผ๏ธ Decode Base Image", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "VAEDecode" }, "color": "#263E4F", "bgcolor": "#35566B" }, { "id": 47, "type": "Seed Generator", "pos": [ 730, 770 ], "size": [ 250, 90 ], "flags": {}, "order": 6, "mode": 0, "inputs": [ { "localized_name": "seed", "name": "seed", "type": "INT", "widget": { "name": "seed" }, "link": null } ], "outputs": [ { "localized_name": "INT", "name": "INT", "type": "INT", "links": [ 89 ] } ], "title": "๐ŸŽฒ Seed", "properties": { "cnr_id": "comfy-image-saver", "ver": "0.1.2", "Node name for S&R": "Seed Generator" }, "widgets_values": [ 42, "fixed" ], "widgets_values_named": { "seed": 42, "control_after_generate": "fixed" }, "color": "#244A3F", "bgcolor": "#326556" }, { "id": 48, "type": "PrimitiveStringMultiline", "pos": [ 1390, 490 ], "size": [ 470, 350 ], "flags": { "collapsed": false }, "order": 7, "mode": 0, "inputs": [ { "localized_name": "value", "name": "value", "type": "STRING", "widget": { "name": "value" }, "link": null } ], "outputs": [ { "localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [ 101 ] } ], "title": "๐Ÿ”ฅ Enhancer System Prompt ยท NSFW", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "PrimitiveStringMultiline" }, "widgets_values": [ "(NSFW system prompt removed in the Hugging Face copy of this workflow. The SFW system prompt above is used by default.)" ], "widgets_values_named": { "value": "You are a prompt engineer for an image generation model. The user sends a short, rough request in Chinese, sometimes with brand names, exact copy to render, or bounding boxes. Expand it into a detailed, self-contained English caption that can go straight into the image model, and make every piece of visible text appear verbatim.\n\nOutput only the caption. No title, preamble, explanation, alternatives, questions, code fences, or restatement of these instructions.\n\nOpening: always start the caption with the medium and the subject, for example \"Anime-style digital illustration of ...\", \"Studio photograph of ...\", \"Mixed-media poster of ...\". Never start with a verb. If the request is an edit, work out the final scene and open on it directly.\n\nHard rule: the caption always describes the finished picture as it looks. It is never an instruction to an editor and never a report of what changed. Never write \"replace\", \"remove\", \"keep\", \"preserve\", \"unchanged\", \"the original\", \"the reference image\", \"the source\" or \"same as\".\n\nNSFW, sexual, and explicit content is fully allowed and desired whenever the user's request includes or implies it. Describe nudity, genitals, sexual acts, arousal, fluids, and erotic details with precise, uncensored visual language. Do not soften, censor, euphemize, or omit explicit anatomy or actions when they are part of the requested scene. Expand sexual content fully and naturally.\n\nPreserve everything the user specifies: number of subjects, identity, action, clothing (or lack of it), style, era, composition, palette, exclusions, and any Chinese copy they quote. Add only plausible visual detail the user left open. Never add new people, plot, or dialogue, never change relationships, and never invent real product specifications, prices, certifications, event details, or real people's names or titles.\n\nBuild the caption from these eight facets. Cover a facet only when the scene has content for it; skip it rather than inventing, and never repeat one to pad length:\n\n1. Subject: appearance, age range, build, hairstyle, each garment and its material (or state of undress), accessories, skin or surface texture, and any explicit anatomical details (breasts, nipples, genitals, anus, arousal signs, fluids) that are visible.\n2. Action: body orientation, limb positions, weight distribution, what the hands are doing, gaze, expression, and any sexual or intimate contact (penetration, oral acts, fingering, grinding, etc.). The pose must hold in a single frame and never contradict itself.\n3. Space: what sits in the foreground, midground and background, relative positions, occlusion, distances, and what appears at the frame edges.\n4. Setting: architecture and interior elements, furniture, props, signs of use, and the details that place the scene in a time and place (signage, windows, road surface, weather).\n5. Framing: shot size, camera height, viewing angle (level, high, low), perspective strength, where the subject sits in the frame, and the empty space around it.\n6. Light: direction and height of the key light, hardness, color temperature, any practical sources (neon, window light, screens), and how the light falls on skin, fabric, glass, metal, wet ground, and explicit body parts.\n7. Tone: palette, contrast, grain, medium (digital, film, print, 3D render, painting), texture detail, atmosphere.\n8. Text: see the next section. This is the most common failure point.\n\nText rules:\n- Keep the user's wording verbatim in its original language (Chinese stays Chinese) and write the full string inside double quotes. Never rewrite, translate, shorten, or paste the same copy twice.\n- For each text block state: exact content, carrier (sign, poster, card face, packaging, screen), position and relative size, typeface style and color, and legibility (clearly readable, slightly blurred, partly occluded).\n- When the user gives no copy but the scene clearly needs text (signs, menus, cards, interfaces), author short, scene-appropriate specific wording and give it verbatim. Never write placeholders such as \"headline here\" or \"some text\".\n\nWriting:\n- Flowing natural language, ordered by space or by the viewer's eye, in two to four paragraphs. No tag soup, no \"masterpiece, 8k, best quality\", no empty quality words.\n- Every sentence must add new visible information. Never restate a feature to reach length, and never drop a key detail just to stay brief.\n- Length: aim for 220 to 320 words for a single-subject scene, 320 to 500 for posters, cards, multi-subject scenes and text-heavy layouts, and never fewer than 200 words. A one-word request such as \"1girl\" still gets a full caption of at least 200 words. Do not pad: if you fall short, add the missing visible detail from the eight facets instead of repeating what you already wrote.\n- Describe only what is visible. No tool steps, generation parameters, or coordinate arithmetic.\n- Even when the request contains canvas sizes, resolution, pixels, or wording like \"3:4\" or \"1024x1024\", never repeat any size, ratio or canvas information in the caption.\n- Use direct, explicit terminology for sexual content (cock, pussy, cum, nipples, etc.) when the scene contains it. Do not default to clinical or softened language.\n\nReference image:\n- Decide whether the supplied image is a content source or a style source. It is a content source when the workflow feeds an image in, or when the user says \"this image\", \"reproduce it\", \"copy it\", \"same as this\", \"only change the background\" or \"only change the copy\". Treat its visible content as the baseline and describe it item by item: subject (hair, hair color, eye color, face, build), every garment (outer layer, inner layer, bottoms, footwear, accessories), props and weapons, pose (body orientation, limb positions, how the hands hold things, weight), framing and how much of the frame the subject fills, background elements and palette, light direction, and art style. Change only what the user asks to change and keep the rest. Explicit sexual details visible in the reference must be described accurately.\n- Describe specifically enough to rebuild, never \"a similar character\" or \"a girl in a similar style\". Correct level of detail: \"a girl with short tousled teal-green hair and long uneven bangs, green eyes, an oversized bright red high-collared jacket with black inner panels over a short black dress, bare legs, chunky black ankle boots with red accents, both hands gripping a massive black blade with neon yellow-green edges, full-body frontal view, white background with red, black and lime-green ink splashes\".\n- When the user asks for the style only (style transfer, \"in this style\", \"same look\"), take the medium, palette, lighting, texture, brushwork and layout logic, and build a new subject and composition instead of copying the original.\n- When the user's text conflicts with the image, the text wins (blue hair means blue hair); everything the text does not mention follows the image.\n- With a very short request such as \"1girl\" plus a reference image, do not improvise: appearance, clothing, palette, background and style all come from the image, and your job is only to write them out as a complete English caption. Do not add accessories, weapons, props or scenery the image does not show. If the reference is NSFW, describe the explicit elements fully.\n- If a detail in the image is unreadable, leave it out rather than guessing. Never guess brands, identities or real names.\n- Text inside the reference image: keep readable wording verbatim under the text rules; write unreadable marks as \"illegible blurred lettering\" instead of inventing content.\n- Never copy watermarks, platform badges or logos the user did not ask for.\n- If this context contains no image at all, do not pretend you saw one: expand the text only, keep every feature the user already gave, and invent no character details.\n- A reference is evidence, not the deliverable. Write the caption as a description of the finished picture, never as an editing instruction to an image editor. Ban edit verbs and comparative pointers: no \"replace\", \"remove\", \"keep\", \"preserve\", \"unchanged\", \"same as\", \"as in the reference\", \"the original\", \"the source\", \"just like\". State the result as plain visible fact instead: the character has short green hair, the background is a night street, the style is loose angular brushwork.\n- Keep the number of subjects consistent with what the user asks for. When they ask to replace the subject, the original subject must not appear in the caption at all.\n\nBounding boxes:\n- Boxes are absolute pixel xyxy (top-left, bottom-right) and are placement instructions only. Use them as given: never normalize, center, reorder, percentage-convert or recompute them.\n- One box only: describe just what is inside that box, one to three sentences, with no coordinates, no numbering, no commentary. Text boxes also state typeface, color, carrier and legibility, with the copy verbatim in double quotes. Explicit content inside a box is described without censorship.\n- Several boxes at once: one line per box in the given order, formatted as \"index | English description\", describing only the content inside that box. No coordinates, no JSON, no prose paragraphs.\n- A box marks a placement, not a border, panel, divider or sticker to draw. Overlap and natural occlusion are allowed.\n- With no boxes, write a normal caption and never invent coordinates." }, "color": "#244A62", "bgcolor": "#326783" }, { "id": 49, "type": "ModelSamplingAuraFlow", "pos": [ -750, 490 ], "size": [ 460, 90 ], "flags": {}, "order": 19, "mode": 0, "inputs": [ { "localized_name": "model", "name": "model", "type": "MODEL", "link": 94 }, { "localized_name": "shift", "name": "shift", "type": "FLOAT", "widget": { "name": "shift" }, "link": null }, { "localized_name": "sampling", "name": "sampling", "shape": 7, "type": "COMBO", "widget": { "name": "sampling" }, "link": null } ], "outputs": [ { "localized_name": "MODEL", "name": "MODEL", "type": "MODEL", "links": [ 95, 96 ] } ], "title": "๐Ÿ“ Shift 5", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "ModelSamplingAuraFlow" }, "widgets_values": [ 5, "flow" ], "widgets_values_named": { "shift": 5, "sampling": "flow" }, "color": "#263B5A", "bgcolor": "#344C70" }, { "id": 50, "type": "PrimitiveStringMultiline", "pos": [ 450, 480 ], "size": [ 260, 250 ], "flags": {}, "order": 8, "mode": 0, "inputs": [ { "localized_name": "value", "name": "value", "type": "STRING", "widget": { "name": "value" }, "link": null } ], "outputs": [ { "localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [ 97 ] } ], "title": "๐Ÿšซ Negative ยท SFW", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "PrimitiveStringMultiline" }, "widgets_values": [ "nsfw, nude, explicit, worst quality, bad anatomy, watermark, jpeg artifact" ], "widgets_values_named": { "value": "nsfw, nude, explicit, worst quality, bad anatomy, watermark, jpeg artifact" }, "color": "#322", "bgcolor": "#533" }, { "id": 51, "type": "PrimitiveStringMultiline", "pos": [ 730, 480 ], "size": [ 250, 250 ], "flags": {}, "order": 9, "mode": 0, "inputs": [ { "localized_name": "value", "name": "value", "type": "STRING", "widget": { "name": "value" }, "link": null } ], "outputs": [ { "localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [ 98 ] } ], "title": "๐Ÿšซ Negative ยท NSFW", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "PrimitiveStringMultiline" }, "widgets_values": [ "worst quality, bad anatomy, watermark, jpeg artifact" ], "widgets_values_named": { "value": "worst quality, bad anatomy, watermark, jpeg artifact" }, "color": "#322", "bgcolor": "#533" }, { "id": 52, "type": "ComfySwitchNode", "pos": [ 1010, 640 ], "size": [ 320, 110 ], "flags": { "collapsed": false }, "order": 22, "mode": 0, "inputs": [ { "localized_name": "on_false", "name": "on_false", "shape": 7, "type": "STRING", "link": 97 }, { "localized_name": "on_true", "name": "on_true", "shape": 7, "type": "STRING", "link": 98 }, { "localized_name": "switch", "name": "switch", "type": "BOOLEAN", "widget": { "name": "switch" }, "link": 104 } ], "outputs": [ { "localized_name": "output", "name": "output", "type": "STRING", "links": [ 99 ] } ], "title": "๐Ÿ”€ Negative SFW / NSFW", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "ComfySwitchNode" }, "widgets_values": [ false ], "widgets_values_named": { "switch": false }, "color": "#5A343A", "bgcolor": "#78464F" }, { "id": 53, "type": "PrimitiveBoolean", "pos": [ 1880, 240 ], "size": [ 400, 70 ], "flags": {}, "order": 10, "mode": 0, "inputs": [ { "localized_name": "value", "name": "value", "type": "BOOLEAN", "widget": { "name": "value" }, "link": null } ], "outputs": [ { "localized_name": "BOOLEAN", "name": "BOOLEAN", "type": "BOOLEAN", "links": [ 103, 104 ] } ], "title": "๐Ÿ”ž NSFW MODE (false = SFW ยท true = NSFW)", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "PrimitiveBoolean" }, "widgets_values": [ false ], "widgets_values_named": { "value": true }, "color": "#5A343A", "bgcolor": "#78464F" }, { "id": 54, "type": "ComfySwitchNode", "pos": [ 1390, 880 ], "size": [ 470, 110 ], "flags": { "collapsed": true }, "order": 21, "mode": 0, "inputs": [ { "localized_name": "on_false", "name": "on_false", "shape": 7, "type": "STRING", "link": 100 }, { "localized_name": "on_true", "name": "on_true", "shape": 7, "type": "STRING", "link": 101 }, { "localized_name": "switch", "name": "switch", "type": "BOOLEAN", "widget": { "name": "switch" }, "link": 103 } ], "outputs": [ { "localized_name": "output", "name": "output", "type": "STRING", "links": [ 102 ] } ], "title": "๐Ÿ”€ System Prompt SFW / NSFW", "properties": { "cnr_id": "comfy-core", "ver": "0.42.0", "Node name for S&R": "ComfySwitchNode" }, "widgets_values": [ false ], "widgets_values_named": { "switch": false }, "color": "#5A343A", "bgcolor": "#78464F" }, { "id": 55, "type": "MarkdownNote", "pos": [ -1370, 30 ], "size": [ 580, 480 ], "flags": {}, "order": 11, "mode": 0, "inputs": [], "outputs": [], "title": "๐Ÿ“˜ SeeMoss-Genesis Ultimate ยท Read Me", "properties": { "cnr_id": "comfy-core", "Node name for S&R": "MarkdownNote" }, "widgets_values": [ "# ๐ŸŽจ SeeMoss-Genesis Ultimate ยท v1.0\n\nA ComfyUI workflow for **SeeMoss-Genesis**, my anime model built on **MOSS-Image-SFT** (OpenMOSS, ~5B DiT, Apache 2.0). Same dataset as See-Krea2-Genesis.\n\n**Flow:** Core models โ†’ write your prompt โ†’ optional Prompt Enhancer โ†’ Base Sampler โ†’ Save (Civitai metadata via SeeSee Civitai Metadata).\n\n## ๐Ÿ“ฆ Files\n- **diffusion_models:** `moss_anime/moss_anime_sft_int8_convrot.safetensors` (also BF16, fp8_scaled, mxfp8, nvfp4, int4_convrot)\n- **text_encoders:** `qwen3.5_9b_w4a8_gptq.safetensors` (CLIP type **moss_image**)\n- **vae:** `flux2-vae_small.safetensors`\n\n## ๐Ÿ”ž SFW / NSFW\nToggle **๐Ÿ”ž NSFW MODE** once. It drives two switches together:\n- the **Enhancer System Prompt** (SFW or NSFW version)\n- the **Negative Prompt** (SFW negative adds `nsfw, nude, explicit`)\n\nThe Enhancer system prompt only matters when **Prompt Enhancer ON / OFF** is `true`.\n\n## ๐Ÿง Triggers\n`seesee_elf`, `seesee_kitsune` at the start of the prompt. Add **pixel art** for my pixel look / Game Boy direction.\n\n## ๐Ÿง  Prompting\nMOSS-Image likes long, natural-language English descriptions (up to ~4K tokens). Tags and JSON layouts also work on the base model.\n" ], "widgets_values_named": { "text": "# ๐ŸŽจ SeeMoss-Genesis Ultimate ยท v1.0\n\nA ComfyUI workflow for **SeeMoss-Genesis**, my anime model built on **MOSS-Image-SFT** (OpenMOSS, ~5B DiT, Apache 2.0). Same dataset as See-Krea2-Genesis.\n\n**Flow:** Core models โ†’ write your prompt โ†’ optional Prompt Enhancer โ†’ Base Sampler โ†’ Save (Civitai metadata via SeeSee Civitai Metadata).\n\n## ๐Ÿ“ฆ Files\n- **diffusion_models:** `moss_anime/moss_anime_sft_int8_convrot.safetensors` (also BF16, fp8_scaled, mxfp8, nvfp4, int4_convrot)\n- **text_encoders:** `qwen3.5_9b_w4a8_gptq.safetensors` (CLIP type **moss_image**)\n- **vae:** `flux2-vae_small.safetensors`\n\n## ๐Ÿ”ž SFW / NSFW\nToggle **๐Ÿ”ž NSFW MODE** once. It drives two switches together:\n- the **Enhancer System Prompt** (SFW or NSFW version)\n- the **Negative Prompt** (SFW negative adds `nsfw, nude, explicit`)\n\nThe Enhancer system prompt only matters when **Prompt Enhancer ON / OFF** is `true`.\n\n## ๐Ÿง Triggers\n`seesee_elf`, `seesee_kitsune` at the start of the prompt. Add **pixel art** for my pixel look / Game Boy direction.\n\n## ๐Ÿง  Prompting\nMOSS-Image likes long, natural-language English descriptions (up to ~4K tokens). Tags and JSON layouts also work on the base model.\n" }, "color": "#343A46", "bgcolor": "#48505F" }, { "id": 56, "type": "MarkdownNote", "pos": [ 2790, 740 ], "size": [ 300, 550 ], "flags": {}, "order": 12, "mode": 0, "inputs": [], "outputs": [], "title": "โš™๏ธ Settings ยท Fast vs Quality", "properties": { "cnr_id": "comfy-core", "Node name for S&R": "MarkdownNote" }, "widgets_values": [ "# โš™๏ธ Settings\n\n| | โšก Turbo | ๐ŸŸข Base (default) | ๐Ÿ’Ž Best quality |\n|---|---|---|---|\n| Steps | **4โ€“8** | **25** | **50** |\n| CFG | **1** | **2.5** | **3** |\n| Shift | 5 | 5 | 5 |\n| Sampler / Scheduler | euler / simple | euler / simple | euler / simple |\n| SLG | off | layer 22 (optional) | layer 22 (optional) |\n| Negative prompt | ignored (CFG 1) | active | active |\n\n- **Without Turbo:** bypass **๐Ÿง  01 ยท Load Lora Models** (or set the LoRA off) and use 25 steps / CFG 2.5, or 50 / 3 / Shift 5 for best quality.\n- **Turbo:** 4โ€“8 steps, CFG 1. The SeeMoss-Genesis Turbo version is coming soon; until then a MOSS-Image turbo/4-step LoRA in ๐Ÿง  01 ยท Load Lora Models gives the same mode. Set the **Hi-Res** samplers to the same CFG as the base.\n- **Shift** is set by **๐Ÿ“ Shift 5** (ModelSamplingAuraFlow). Use AuraFlow shift only, not ModelSamplingSD3.\n- **SLG** (Skip Layer Guidance, layer 22) only acts on the negative branch, so it needs CFG > 1. Off looks cleaner on some anime styles, on adds detail; test both.\n- **Resolution:** 1โ€“2 MP, sides multiple of 16 (e.g. 1024ร—1024, 832ร—1472)." ], "widgets_values_named": { "text": "# โš™๏ธ Settings\n\n| | โšก Turbo | ๐ŸŸข Base (default) | ๐Ÿ’Ž Best quality |\n|---|---|---|---|\n| Steps | **4โ€“8** | **25** | **50** |\n| CFG | **1** | **2.5** | **3** |\n| Shift | 5 | 5 | 5 |\n| Sampler / Scheduler | euler / simple | euler / simple | euler / simple |\n| SLG | off | layer 22 (optional) | layer 22 (optional) |\n| Negative prompt | ignored (CFG 1) | active | active |\n\n- **Without Turbo:** bypass **๐Ÿง  01 ยท Load Lora Models** (or set the LoRA off) and use 25 steps / CFG 2.5, or 50 / 3 / Shift 5 for best quality.\n- **Turbo:** 4โ€“8 steps, CFG 1. The SeeMoss-Genesis Turbo version is coming soon; until then a MOSS-Image turbo/4-step LoRA in ๐Ÿง  01 ยท Load Lora Models gives the same mode. Set the **Hi-Res** samplers to the same CFG as the base.\n- **Shift** is set by **๐Ÿ“ Shift 5** (ModelSamplingAuraFlow). Use AuraFlow shift only, not ModelSamplingSD3.\n- **SLG** (Skip Layer Guidance, layer 22) only acts on the negative branch, so it needs CFG > 1. Off looks cleaner on some anime styles, on adds detail; test both.\n- **Resolution:** 1โ€“2 MP, sides multiple of 16 (e.g. 1024ร—1024, 832ร—1472)." }, "color": "#343A46", "bgcolor": "#48505F" }, { "id": 310, "type": "Reroute", "pos": [ 3100, -270 ], "size": [ 75, 26 ], "flags": {}, "order": 51, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 687 } ], "outputs": [ { "name": "", "type": "IMAGE", "links": [ 691 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#233D58", "bgcolor": "#315578" }, { "id": 311, "type": "Reroute", "pos": [ 3590, -210 ], "size": [ 75, 26 ], "flags": {}, "order": 42, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 685 } ], "outputs": [ { "name": "", "type": "MODEL", "links": [ 665, 698 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#35264B", "bgcolor": "#4A3565" }, { "id": 312, "type": "Reroute", "pos": [ 3590, -150 ], "size": [ 75, 26 ], "flags": {}, "order": 47, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 683 } ], "outputs": [ { "name": "", "type": "CONDITIONING", "links": [ 649, 666 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#254333", "bgcolor": "#345A45" }, { "id": 313, "type": "Reroute", "pos": [ 3590, -330 ], "size": [ 75, 26 ], "flags": {}, "order": 28, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 700 } ], "outputs": [ { "name": "", "type": "UPSCALE_MODEL", "links": [ 652 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#4D3B20", "bgcolor": "#68512C" }, { "id": 314, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 3710, -130 ], "size": [ 360, 90 ], "flags": {}, "order": 13, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": [] } ], "title": "๐Ÿ”ผ Hi-Res Pipeline ON / OFF", "properties": { "matchColors": "", "matchTitle": "๐Ÿ”ผ", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.4.1" } }, "color": "#5A451F", "bgcolor": "#7A5F2A" }, { "id": 316, "type": "Reroute", "pos": [ 3590, -90 ], "size": [ 75, 26 ], "flags": {}, "order": 45, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 682 } ], "outputs": [ { "name": "", "type": "CONDITIONING", "links": [ 650, 667 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#254333", "bgcolor": "#345A45" }, { "id": 317, "type": "Reroute", "pos": [ 3590, -30 ], "size": [ 75, 26 ], "flags": {}, "order": 31, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 675 } ], "outputs": [ { "name": "", "type": "VAE", "links": [ 651, 670 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#322", "bgcolor": "#533" }, { "id": 318, "type": "SeeSeeCivitaiSaveImage", "pos": [ 4010, 80 ], "size": [ 550, 920 ], "flags": {}, "order": 58, "mode": 4, "inputs": [ { "localized_name": "images", "name": "images", "type": "IMAGE", "link": 645 }, { "localized_name": "filename_prefix", "name": "filename_prefix", "type": "STRING", "widget": { "name": "filename_prefix" }, "link": null }, { "localized_name": "embed_workflow", "name": "embed_workflow", "type": "BOOLEAN", "widget": { "name": "embed_workflow" }, "link": null } ], "outputs": [ { "localized_name": "images", "name": "images", "type": "IMAGE", "links": null }, { "localized_name": "parameters", "name": "parameters", "type": "STRING", "links": null } ], "title": "๐Ÿ’พ Save Tiled Upscale", "properties": { "cnr_id": "seesee-civitai-metadata", "ver": "0.1.0", "Node name for S&R": "SeeSeeCivitaiSaveImage" }, "widgets_values": [ "SeeMoss-Genesis-Tiled-Upscale", true ], "widgets_values_named": { "filename_prefix": "SeeMoss-Genesis-Tiled-Upscale", "embed_workflow": true }, "color": "#5A451F", "bgcolor": "#7A5F2A" }, { "id": 319, "type": "Reroute", "pos": [ 4500, -270 ], "size": [ 75, 26 ], 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{ "name": "upscale_by" }, "link": null }, { "localized_name": "seed", "name": "seed", "type": "INT", "widget": { "name": "seed" }, "link": null }, { "localized_name": "steps", "name": "steps", "type": "INT", "widget": { "name": "steps" }, "link": null }, { "localized_name": "cfg", "name": "cfg", "type": "FLOAT", "widget": { "name": "cfg" }, "link": null }, { "localized_name": "sampler_name", "name": "sampler_name", "type": "COMBO", "widget": { "name": "sampler_name" }, "link": null }, { "localized_name": "scheduler", "name": "scheduler", "type": "COMBO", "widget": { "name": "scheduler" }, "link": null }, { "localized_name": "denoise", "name": "denoise", "type": "FLOAT", "widget": { "name": "denoise" }, "link": null }, { "localized_name": "mode_type", "name": "mode_type", "type": "COMBO", "widget": { "name": "mode_type" }, "link": null }, { "localized_name": "tile_width", "name": "tile_width", "type": "INT", "widget": { "name": "tile_width" }, "link": null }, { "localized_name": 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"SeeMoss-Genesis-Refined", true ], "widgets_values_named": { "filename_prefix": "SeeMoss-Genesis-Refined", "embed_workflow": true }, "color": "#263E4F", "bgcolor": "#35566B" }, { "id": 326, "type": "VAEDecode", "pos": [ 3720, 1480 ], "size": [ 300, 50 ], "flags": { "collapsed": false }, "order": 54, "mode": 4, "inputs": [ { "localized_name": "samples", "name": "samples", "type": "LATENT", "link": 669 }, { "localized_name": "vae", "name": "vae", "type": "VAE", "link": 670 } ], "outputs": [ { "localized_name": "IMAGE", "name": "IMAGE", "type": "IMAGE", "slot_index": 0, "links": [ 668 ] } ], "title": "๐Ÿ–ผ๏ธ Decode Refined Image", "properties": { "cnr_id": "comfy-core", "ver": "0.3.48", "Node name for S&R": "VAEDecode", "ue_properties": { "version": "7.0.1", "widget_ue_connectable": {} }, "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65 }, "color": "#263E4F", "bgcolor": "#35566B" }, { 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"type": "MODEL", "links": [ 696 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#35264B", "bgcolor": "#4A3565" }, { "id": 337, "type": "UpscaleModelLoader", "pos": [ -750, 1120 ], "size": [ 460, 70 ], "flags": {}, "order": 14, "mode": 0, "inputs": [ { "localized_name": "model_name", "name": "model_name", "type": "COMBO", "widget": { "name": "model_name" }, "link": null } ], "outputs": [ { "localized_name": "UPSCALE_MODEL", "name": "UPSCALE_MODEL", "type": "UPSCALE_MODEL", "links": [ 699 ] } ], "title": "๐Ÿ”ผ Upscale Model ยท AnimeSharp 2ร—", "properties": { "cnr_id": "comfy-core", "ver": "0.18.1", "Node name for S&R": "UpscaleModelLoader" }, "widgets_values": [ "2x-AnimeSharpV4_RCAN.safetensors" ], "widgets_values_named": { "model_name": "2x-AnimeSharpV4_RCAN.safetensors" }, "color": "#5A451F", "bgcolor": "#7A5F2A" }, { "id": 338, "type": "Reroute", "pos": [ -230, -330 ], "size": [ 75, 26 ], "flags": {}, "order": 23, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 699 } ], "outputs": [ { "name": "", "type": "UPSCALE_MODEL", "links": [ 700 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#4D3B20", "bgcolor": "#68512C" }, { "id": 341, "type": "MarkdownNote", "pos": [ -1370, 560 ], "size": [ 580, 860 ], "flags": {}, "order": 15, "mode": 0, "inputs": [], "outputs": [], "title": "๐Ÿ“ฅ Model Downloads", "properties": {}, "widgets_values": [ "# ๐Ÿ“ฅ Model Downloads\n\n## SeeMoss-Genesis (this model)\n๐Ÿ‘‰ [SeeMoss-Genesis on Civitai](https://civitai.red/models/3031179/seemoss-genesis)\n\n| Version | File | Folder |\n|---|---|---|\n| **Preview** | `moss_anime_sft_BF16` (~10.2 GB, best) | `models/diffusion_models/moss_anime/` |\n| | `moss_anime_sft_fp8_scaled` (~5.4 GB) | ใ€ƒ |\n| | `moss_anime_sft_int8_convrot` (~5.4 GB, **default**) | ใ€ƒ |\n| | `moss_anime_sft_mxfp8` (~5.6 GB, RTX 50) | ใ€ƒ |\n| | `moss_anime_sft_nvfp4` (~3.3 GB, RTX 50) | ใ€ƒ |\n| | `moss_anime_sft_int4_convrot` (~3.0 GB, low VRAM) | ใ€ƒ |\n| **Text Encoder** | `qwen3.5_9b_w4a8_gptq.safetensors` | `models/text_encoders/` |\n| **VAE** | `flux2-vae_small.safetensors` | `models/vae/` |\n\nText Encoder and VAE are separate versions on the model page (version dropdown).\n\n๐Ÿงฉ Workflow page: [SeeMoss-Genesis-Workflows](https://civitai.red/models/3031981) ยท see **๐Ÿงฉ Required Custom Nodes** below.\n\n## Upstream MOSS-Image (OpenMOSS, Apache 2.0)\n- [OpenMOSS/MOSS-Image on GitHub](https://github.com/OpenMOSS/MOSS-Image)\n- [MOSS-Image-SFT (Hugging Face)](https://huggingface.co/OpenMOSS-Team/MOSS-Image-SFT)\n- [MOSS-Image-Base (Hugging Face)](https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base)\n- [ComfyUI repack: text encoders, VAE (Comfy-Org)](https://huggingface.co/Comfy-Org/MOSS-Image)\n- [ComfyUI MOSS-Image guide](https://docs.comfy.org/tutorials/image/moss-image/moss-image)\n\n## ๐Ÿ”ผ Upscale model (optional)\n[`2x-AnimeSharpV4_RCAN.safetensors`](https://github.com/Kim2091/Kim2091-Models/releases/download/2x-AnimeSharpV4/2x-AnimeSharpV4_RCAN.safetensors) by Kim2091 โ†’ `models/upscale_models/` (any 2ร— ESRGAN/RCAN model works).\n\nโš ๏ธ Needs **ComfyUI 0.42.0+** (native MOSS-Image support).\n\n๐Ÿ“„ Workflow page: [SeeMoss-Genesis-Workflows](https://civitai.red/models/3031981)\n\n# ๐Ÿงฉ Required Custom Nodes\n\nInstall with [ComfyUI-Manager](https://github.com/Comfy-Org/ComfyUI-Manager) (search the name) or `git clone` into `custom_nodes/`, then restart ComfyUI.\n\n| Pack | Used for |\n|---|---|\n| [SeeSee Civitai Metadata](https://github.com/seesee75-commits/ComfyUI-SeeSee-Civitai-Metadata) | ๐Ÿ’พ save nodes: Civitai-readable metadata in every PNG |\n| [ComfyUI-Lora-Manager](https://github.com/willmiao/ComfyUI-Lora-Manager) | ๐Ÿงฌ LoRA Loader + TriggerWord Toggle |\n| [rgthree-comfy](https://github.com/rgthree/rgthree-comfy) | ๐Ÿ”ผ Hi-Res ON / OFF switch, ๐Ÿ” image comparers |\n| [ComfyUI_UltimateSDUpscale](https://github.com/ssitu/ComfyUI_UltimateSDUpscale) | ๐Ÿ”ผ 06 ยท Tiled Upscale |\n| [comfy-image-saver](https://github.com/giriss/comfy-image-saver) | ๐ŸŽฒ Seed Generator |\n\nEverything else is ComfyUI core. Needs **ComfyUI 0.42.0+** (native MOSS-Image, subgraphs, TextGenerate).\n\n๐Ÿ“„ Workflow page: [SeeMoss-Genesis-Workflows](https://civitai.red/models/3031981)" ], "widgets_values_named": { "text": "# ๐Ÿ“ฅ Model Downloads\n\n## SeeMoss-Genesis (this model)\n๐Ÿ‘‰ [SeeMoss-Genesis on Civitai](https://civitai.red/models/3031179/seemoss-genesis)\n\n| Version | File | Folder |\n|---|---|---|\n| **Preview** | `moss_anime_sft_BF16` (~10.2 GB, best) | `models/diffusion_models/moss_anime/` |\n| | `moss_anime_sft_fp8_scaled` (~5.4 GB) | ใ€ƒ |\n| | `moss_anime_sft_int8_convrot` (~5.4 GB, **default**) | ใ€ƒ |\n| | `moss_anime_sft_mxfp8` (~5.6 GB, RTX 50) | ใ€ƒ |\n| | `moss_anime_sft_nvfp4` (~3.3 GB, RTX 50) | ใ€ƒ |\n| | `moss_anime_sft_int4_convrot` (~3.0 GB, low VRAM) | ใ€ƒ |\n| **Text Encoder** | `qwen3.5_9b_w4a8_gptq.safetensors` | `models/text_encoders/` |\n| **VAE** | `flux2-vae_small.safetensors` | `models/vae/` |\n\nText Encoder and VAE are separate versions on the model page (version dropdown).\n\n๐Ÿงฉ Workflow page: [SeeMoss-Genesis-Workflows](https://civitai.red/models/3031981) ยท see **๐Ÿงฉ Required Custom Nodes** below.\n\n## Upstream MOSS-Image (OpenMOSS, Apache 2.0)\n- [OpenMOSS/MOSS-Image on GitHub](https://github.com/OpenMOSS/MOSS-Image)\n- [MOSS-Image-SFT (Hugging Face)](https://huggingface.co/OpenMOSS-Team/MOSS-Image-SFT)\n- [MOSS-Image-Base (Hugging Face)](https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base)\n- [ComfyUI repack: text encoders, VAE (Comfy-Org)](https://huggingface.co/Comfy-Org/MOSS-Image)\n- [ComfyUI MOSS-Image guide](https://docs.comfy.org/tutorials/image/moss-image/moss-image)\n\n## ๐Ÿ”ผ Upscale model (optional)\n[`2x-AnimeSharpV4_RCAN.safetensors`](https://github.com/Kim2091/Kim2091-Models/releases/download/2x-AnimeSharpV4/2x-AnimeSharpV4_RCAN.safetensors) by Kim2091 โ†’ `models/upscale_models/` (any 2ร— ESRGAN/RCAN model works).\n\nโš ๏ธ Needs **ComfyUI 0.42.0+** (native MOSS-Image support).\n\n๐Ÿ“„ Workflow page: [SeeMoss-Genesis-Workflows](https://civitai.red/models/3031981)\n\n# ๐Ÿงฉ Required Custom Nodes\n\nInstall with [ComfyUI-Manager](https://github.com/Comfy-Org/ComfyUI-Manager) (search the name) or `git clone` into `custom_nodes/`, then restart ComfyUI.\n\n| Pack | Used for |\n|---|---|\n| [SeeSee Civitai Metadata](https://github.com/seesee75-commits/ComfyUI-SeeSee-Civitai-Metadata) | ๐Ÿ’พ save nodes: Civitai-readable metadata in every PNG |\n| [ComfyUI-Lora-Manager](https://github.com/willmiao/ComfyUI-Lora-Manager) | ๐Ÿงฌ LoRA Loader + TriggerWord Toggle |\n| [rgthree-comfy](https://github.com/rgthree/rgthree-comfy) | ๐Ÿ”ผ Hi-Res ON / OFF switch, ๐Ÿ” image comparers |\n| [ComfyUI_UltimateSDUpscale](https://github.com/ssitu/ComfyUI_UltimateSDUpscale) | ๐Ÿ”ผ 06 ยท Tiled Upscale |\n| [comfy-image-saver](https://github.com/giriss/comfy-image-saver) | ๐ŸŽฒ Seed Generator |\n\nEverything else is ComfyUI core. Needs **ComfyUI 0.42.0+** (native MOSS-Image, subgraphs, TextGenerate).\n\n๐Ÿ“„ Workflow page: [SeeMoss-Genesis-Workflows](https://civitai.red/models/3031981)" }, "color": "#432", "bgcolor": "#653" }, { "id": 342, "type": "MarkdownNote", "pos": [ 4600, 30 ], "size": [ 330, 360 ], "flags": {}, "order": 16, "mode": 0, "inputs": [], "outputs": [], "title": "๐Ÿ”ผ Hi-Res ยท How to use", "properties": {}, "widgets_values": [ "# ๐Ÿ”ผ Hi-Res Options\n\nTurn both on/off with **๐Ÿ”ผ Hi-Res Pipeline ON / OFF**. Uses the upscale model from **๐Ÿงฉ Hi-Res Model**.\n\n## 06 ยท Tiled Upscale\nUltimate SD Upscale on the decoded base image: model upscale ร—1.5, then tile-by-tile resampling (denoise 0.3). Best for big sizes with low VRAM.\n\n## 07 ยท Detail Refiner\nWorks in **latent space**: the base latent goes through **๐Ÿ”ผ Upscale Latent By** (inside **๐Ÿ”ฌ Detail Refiner Setup**), then gets resampled by **๐Ÿ”ฌ Refiner Sampler**.\n- **Latent Upscale ร—:** 1.5 (1.25โ€“2)\n- **Hi-Res Denoise:** 0.45โ€“0.6 (latent upscale needs more denoise than pixel upscale; too low = blurry)\n- **Hi-Res Steps / CFG:** match the base (Turbo 4โ€“8 / 1, Base 25 / 2.5)\n\nCompare nodes show base vs result side by side." ], "widgets_values_named": { "text": "# ๐Ÿ”ผ Hi-Res Options\n\nTurn both on/off with **๐Ÿ”ผ Hi-Res Pipeline ON / OFF**. Uses the upscale model from **๐Ÿงฉ Hi-Res Model**.\n\n## 06 ยท Tiled Upscale\nUltimate SD Upscale on the decoded base image: model upscale ร—1.5, then tile-by-tile resampling (denoise 0.3). Best for big sizes with low VRAM.\n\n## 07 ยท Detail Refiner\nWorks in **latent space**: the base latent goes through **๐Ÿ”ผ Upscale Latent By** (inside **๐Ÿ”ฌ Detail Refiner Setup**), then gets resampled by **๐Ÿ”ฌ Refiner Sampler**.\n- **Latent Upscale ร—:** 1.5 (1.25โ€“2)\n- **Hi-Res Denoise:** 0.45โ€“0.6 (latent upscale needs more denoise than pixel upscale; too low = blurry)\n- **Hi-Res Steps / CFG:** match the base (Turbo 4โ€“8 / 1, Base 25 / 2.5)\n\nCompare nodes show base vs result side by side." }, "color": "#432", "bgcolor": "#653" }, { "id": 344, "type": "MarkdownNote", "pos": [ -740, 1240 ], "size": [ 450, 240 ], "flags": {}, "order": 17, "mode": 0, "inputs": [], "outputs": [], "title": "๐Ÿง  Core Models ยท Info", "properties": {}, "widgets_values": [ "# ๐Ÿง  01 ยท Core Models\n- **Base Model:** SeeMoss-Genesis quant (int8 default; BF16 best; nvfp4/mxfp8 for RTX 50; int4 low VRAM).\n- **Text Encoder:** Qwen3.5 9B, CLIP type **moss_image**.\n- **VAE:** FLUX.2 small.\n- **๐Ÿ“ Shift 5** โ†’ **SLG** โ†’ **SLG ON / OFF** (true = on).\n- **Load Lora Models:** optional LoRAs / turbo LoRA; bypass for the normal 25/50-step mode." ], "widgets_values_named": { "text": "# ๐Ÿง  01 ยท Core Models\n- **Base Model:** SeeMoss-Genesis quant (int8 default; BF16 best; nvfp4/mxfp8 for RTX 50; int4 low VRAM).\n- **Text Encoder:** Qwen3.5 9B, CLIP type **moss_image**.\n- **VAE:** FLUX.2 small.\n- **๐Ÿ“ Shift 5** โ†’ **SLG** โ†’ **SLG ON / OFF** (true = on).\n- **Load Lora Models:** optional LoRAs / turbo LoRA; bypass for the normal 25/50-step mode." }, "color": "#432", "bgcolor": "#653" }, { "id": 345, "type": "Reroute", "pos": [ 1020, -390 ], "size": [ 75, 26 ], "flags": {}, "order": 24, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 707 } ], "outputs": [ { "name": "", "type": "LATENT", "links": [ 708 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#323", "bgcolor": "#535" }, { "id": 346, "type": "Reroute", "pos": [ 2650, -390 ], "size": [ 75, 26 ], "flags": {}, "order": 29, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 708 } ], "outputs": [ { "name": "", "type": "LATENT", "links": [ 709 ] } ], "properties": { "showOutputText": false, "horizontal": false }, "color": "#323", "bgcolor": "#535" }, { "id": 347, "type": "Lora Loader (LoraManager)", "pos": [ -230, 100 ], "size": [ 620, 670 ], "flags": {}, "order": 33, "mode": 0, "inputs": [ { "localized_name": "model", "name": "model", "type": "MODEL", "link": 710 }, { "localized_name": "text", "name": "text", "type": "AUTOCOMPLETE_TEXT_LORAS", "widget": { "name": "text" }, "link": null }, { "localized_name": "loras", "name": "loras", "type": "LORAS", "widget": { "name": "loras" }, "link": null }, { "name": "clip", "shape": 7, "type": "CLIP", "link": 712 }, { "name": "lora_stack", "shape": 7, "type": "LORA_STACK", "link": null } ], "outputs": [ { "localized_name": "MODEL", "name": "MODEL", "type": "MODEL", "links": [ 711 ] }, { "localized_name": "CLIP", 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