{ "id": "d8dd10fc-d3e6-4d36-8c45-01e2b625b02c", "revision": 1, "last_node_id": 20, "last_link_id": 22, "nodes": [ { "id": 1, "type": "ResolutionSelector", "pos": [ -1250, -600 ], "size": [ 410, 174 ], "flags": {}, "order": 10, "mode": 0, "showAdvanced": false, "inputs": [ { "name": "megapixels", "type": "FLOAT", "widget": { "name": "megapixels" }, "link": 22 } ], "outputs": [ { "name": "width", "type": "INT", "links": [ 1, 4 ] }, { "name": "height", "type": "INT", "links": [ 2, 5 ] } ], "title": "01 | ASPECT RATIO (change this)", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "ResolutionSelector" }, "widgets_values": [ "16:9 (Widescreen)", 16, 32 ], "widgets_values_named": { "aspect_ratio": "16:9 (Widescreen)", "megapixels": 16, "multiple": 32 } }, { "id": 2, "type": "PrimitiveFloat", "pos": [ -1250, -330 ], "size": [ 410, 92 ], "flags": {}, "order": 0, "mode": 0, "inputs": [], "outputs": [ { "name": "FLOAT", "type": "FLOAT", "links": [ 3, 6 ] } ], "title": "02 | TARGET MEGAPIXELS (4–20)", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "PrimitiveFloat" }, "widgets_values": [ 20 ], "widgets_values_named": { "value": 20 } }, { "id": 3, "type": "ComfyMathExpression", "pos": [ -770, -600 ], "size": [ 440, 182 ], "flags": {}, "order": 11, "mode": 0, "inputs": [ { "name": "values.a", "type": "FLOAT,INT,BOOLEAN", "link": 1 }, { "name": "values.b", "shape": 7, "type": "FLOAT,INT,BOOLEAN", "link": 2 }, { "name": "values.c", "shape": 7, "type": "FLOAT,INT,BOOLEAN", "link": 3 }, { "name": "values.d", "shape": 7, "type": "FLOAT,INT,BOOLEAN", "link": null } ], "outputs": [ { "name": "FLOAT", "type": "FLOAT", "links": null }, { "name": "INT", "type": "INT", "links": [ 7 ] }, { "name": "BOOL", "type": "BOOLEAN", "links": null } ], "title": "Calculated width", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "ComfyMathExpression" }, "widgets_values": [ "round(sqrt(a / b * c * 1000000) / 32) * 32" ], "widgets_values_named": { "expression": "round(sqrt(a / b * c * 1000000) / 32) * 32" } }, { "id": 4, "type": "ComfyMathExpression", "pos": [ -770, -330 ], "size": [ 440, 182 ], "flags": {}, "order": 12, "mode": 0, "inputs": [ { "name": "values.a", "type": "FLOAT,INT,BOOLEAN", "link": 4 }, { "name": "values.b", "shape": 7, "type": "FLOAT,INT,BOOLEAN", "link": 5 }, { "name": "values.c", "shape": 7, "type": "FLOAT,INT,BOOLEAN", "link": 6 }, { "name": "values.d", "shape": 7, "type": "FLOAT,INT,BOOLEAN", "link": null } ], "outputs": [ { "name": "FLOAT", "type": "FLOAT", "links": null }, { "name": "INT", "type": "INT", "links": [ 8 ] }, { "name": "BOOL", "type": "BOOLEAN", "links": null } ], "title": "Calculated height", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "ComfyMathExpression" }, "widgets_values": [ "round(sqrt(b / a * c * 1000000) / 32) * 32" ], "widgets_values_named": { "expression": "round(sqrt(b / a * c * 1000000) / 32) * 32" } }, { "id": 5, "type": "UNETLoader", "pos": [ -225, -595 ], "size": [ 530, 94 ], "flags": {}, "order": 1, "mode": 0, "inputs": [], "outputs": [ { "name": "MODEL", "type": "MODEL", "links": [ 11 ] } ], "title": "ZetaLvX • MiniMax H3 • diffusion model", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "UNETLoader" }, "widgets_values": [ "minimax_h3_image_pruned_int8_convrot.safetensors", "default" ], "widgets_values_named": { "unet_name": "minimax_h3_image_pruned_int8_convrot.safetensors", "weight_dtype": "default" }, "color": "#223", "bgcolor": "#335" }, { "id": 6, "type": "CLIPLoader", "pos": [ -225, -435 ], "size": [ 530, 128 ], "flags": {}, "order": 2, "mode": 0, "inputs": [], "outputs": [ { "name": "CLIP", "type": "CLIP", "links": [ 9 ] } ], "title": "ZetaLvX • MiniMax H3 • text encoder", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "CLIPLoader" }, "widgets_values": [ "qwen3vl_32b_minimax_h3_int8_convrot.safetensors", "minimax", "default" ], "widgets_values_named": { "clip_name": "qwen3vl_32b_minimax_h3_int8_convrot.safetensors", "type": "minimax", "device": "default" } }, { "id": 7, "type": "VAELoader", "pos": [ -225, -245 ], "size": [ 530, 90 ], "flags": {}, "order": 3, "mode": 0, "inputs": [], "outputs": [ { "name": "VAE", "type": "VAE", "links": [ 10, 17 ] } ], "title": "ZetaLvX • MiniMax H3 • VAE", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "VAELoader" }, "widgets_values": [ "minimax_h3_image_vae_fp16.safetensors" ], "widgets_values_named": { "vae_name": "minimax_h3_image_vae_fp16.safetensors" }, "color": "#322", "bgcolor": "#533" }, { "id": 8, "type": "MiniMaxH3ImageConditioning", "pos": [ 381.22582806043386, -608.8751245924263 ], "size": [ 666.8817693536927, 765 ], "flags": {}, "order": 13, "mode": 0, "inputs": [ { "name": "clip", "type": "CLIP", "link": 9 }, { "name": "vae", "shape": 7, "type": "VAE", "link": 10 }, { "label": "image_0", "name": "images.image_0", "shape": 7, "type": "IMAGE", "link": 21 }, { "name": "images.image_1", "shape": 7, "type": "IMAGE", "link": null }, { "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 7 }, { "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 8 }, { "label": "image_2", "name": "images.image_2", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_3", "name": "images.image_3", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_4", "name": "images.image_4", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_5", "name": "images.image_5", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_6", "name": "images.image_6", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_7", "name": "images.image_7", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_8", "name": "images.image_8", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_9", "name": "images.image_9", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_10", "name": "images.image_10", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_11", "name": "images.image_11", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_12", "name": "images.image_12", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_13", "name": "images.image_13", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_14", "name": "images.image_14", "shape": 7, "type": "IMAGE", "link": null }, { "label": "image_15", "name": "images.image_15", "shape": 7, "type": "IMAGE", "link": null } ], "outputs": [ { "name": "positive", "type": "CONDITIONING", "links": [ 12, 13 ] }, { "name": "LATENT", "type": "LATENT", "links": [ 15 ] } ], "title": "PROMPT • MiniMax H3 Image", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "MiniMaxH3ImageConditioning" }, "widgets_values": [ "Edit the provided image_1 by ADDING TYPOGRAPHY ONLY. This is a strict image preservation task.\n\nKeep the original photograph completely unchanged. Preserve the exact same person, facial features, expression, hairstyle, sunglasses, jacket, colors, lighting, geometric background, framing, camera angle, and image proportions. Do not crop, extend, redraw, retouch, enhance, recolor, or regenerate any part of the original image.\n\nCreate an elegant, high-impact YouTube thumbnail text overlay using these EXACT words:\n\nH3-IMAGE\nCOMFYUI\nOPTIMIZED WORKFLOWS\n\nPlace the typography mainly across the lower third of the image, avoiding the woman's eyes, glasses, nose, and mouth.\n\n\"H3-IMAGE\" is the dominant headline: very large, bold, modern white sans-serif typography, with \"H3\" highlighted in bright cyan.\n\n\"COMFYUI\" is a smaller secondary heading in white.\n\n\"OPTIMIZED WORKFLOWS\" is a compact uppercase subtitle in cyan, positioned below the main heading.\n\nUse precise typography, consistent letter spacing, sharp edges, professional graphic design, and excellent readability at small thumbnail size.\n\nAdd only a subtle dark translucent gradient or soft shadow directly behind the text if necessary for contrast. Do not otherwise modify the image.\n\nKeep every letter fully visible inside the image boundaries with safe margins. Avoid overlapping the woman's face. Do not add any logos, icons, symbols, watermarks, extra words, frames, decorative graphics, or AI-themed elements.\n\nThe final image must be the original photograph with only the requested professionally designed text overlay added.", 4608, 3456 ], "widgets_values_named": { "prompt": "Edit the provided image_1 by ADDING TYPOGRAPHY ONLY. This is a strict image preservation task.\n\nKeep the original photograph completely unchanged. Preserve the exact same person, facial features, expression, hairstyle, sunglasses, jacket, colors, lighting, geometric background, framing, camera angle, and image proportions. Do not crop, extend, redraw, retouch, enhance, recolor, or regenerate any part of the original image.\n\nCreate an elegant, high-impact YouTube thumbnail text overlay using these EXACT words:\n\nH3-IMAGE\nCOMFYUI\nOPTIMIZED WORKFLOWS\n\nPlace the typography mainly across the lower third of the image, avoiding the woman's eyes, glasses, nose, and mouth.\n\n\"H3-IMAGE\" is the dominant headline: very large, bold, modern white sans-serif typography, with \"H3\" highlighted in bright cyan.\n\n\"COMFYUI\" is a smaller secondary heading in white.\n\n\"OPTIMIZED WORKFLOWS\" is a compact uppercase subtitle in cyan, positioned below the main heading.\n\nUse precise typography, consistent letter spacing, sharp edges, professional graphic design, and excellent readability at small thumbnail size.\n\nAdd only a subtle dark translucent gradient or soft shadow directly behind the text if necessary for contrast. Do not otherwise modify the image.\n\nKeep every letter fully visible inside the image boundaries with safe margins. Avoid overlapping the woman's face. Do not add any logos, icons, symbols, watermarks, extra words, frames, decorative graphics, or AI-themed elements.\n\nThe final image must be the original photograph with only the requested professionally designed text overlay added.", "width": 4608, "height": 3456 } }, { "id": 9, "type": "ConditioningZeroOut", "pos": [ 1117.6388972349741, -531.9444806833794 ], "size": [ 320, 78 ], "flags": {}, "order": 14, "mode": 0, "inputs": [ { "name": "conditioning", "type": "CONDITIONING", "link": 13 } ], "outputs": [ { "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 14 ] } ], "title": "No CFG • empty negative", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "ConditioningZeroOut" } }, { "id": 10, "type": "KSampler", "pos": [ 1129.428635689974, -365.23985297537945 ], "size": [ 510, 350 ], "flags": {}, "order": 15, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 11 }, { "name": "positive", "type": "CONDITIONING", "link": 12 }, { "name": "negative", "type": "CONDITIONING", "link": 14 }, { "name": "latent_image", "type": "LATENT", "link": 15 } ], "outputs": [ { "name": "LATENT", "type": "LATENT", "links": [ 16 ] } ], "title": "SAMPLING • 6 steps / Euler", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "KSampler" }, "widgets_values": [ 77, "fixed", 6, 1, "euler", "simple", 1 ], "widgets_values_named": { "seed": 77, "control_after_generate": "fixed", "steps": 6, "cfg": 1, "sampler_name": "euler", "scheduler": "simple", "denoise": 1 } }, { "id": 11, "type": "VAEDecode", "pos": [ 1736.1108011690271, -587.2915900157541 ], "size": [ 310, 80 ], "flags": {}, "order": 16, "mode": 0, "inputs": [ { "name": "samples", "type": "LATENT", "link": 16 }, { "name": "vae", "type": "VAE", "link": 17 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 18, 19 ] } ], "title": "DECODE • VAE FP16", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "VAEDecode" } }, { "id": 12, "type": "PreviewImage", "pos": [ 2146.1108011690267, -637.2915900157541 ], "size": [ 600, 460 ], "flags": {}, "order": 17, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 18 } ], "outputs": [ { "name": "images", "type": "IMAGE", "links": null } ], "title": "Image preview", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "PreviewImage" } }, { "id": 13, "type": "SaveImage", "pos": [ 1756.3673811690269, -99.4568378457679 ], "size": [ 500, 120 ], "flags": {}, "order": 18, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 19 } ], "outputs": [ { "name": "images", "type": "IMAGE", "links": null } ], "title": "Save PNG", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "SaveImage" }, "widgets_values": [ "ZetaLvX_MiniMax_H3_Image" ], "widgets_values_named": { "filename_prefix": "ZetaLvX_MiniMax_H3_Image" } }, { "id": 14, "type": "MarkdownNote", "pos": [ -976.0164923235902, 626.1580569320458 ], "size": [ 740, 750 ], "flags": {}, "order": 4, "mode": 0, "inputs": [], "outputs": [], "title": "GUIDE / USAGE", "properties": { "Node name for S&R": "MarkdownNote", "cnr_id": "comfy-core", "ver": "0.45.0" }, "widgets_values": [ "# ZetaLvX | MiniMax H3 Image\n### Text-to-image · Image editing · Multi-reference\n\nThe same model supports image generation and image editing. Connect reference images only when needed.\n\n**Text-to-image**\n1. Keep all `image_0`–`image_15` inputs disconnected.\n2. Enter a generation prompt in **PROMPT**.\n3. Set the aspect ratio and target megapixels, then run the workflow.\n\n**Image editing**\n1. Add a built-in **Load Image** node and connect its IMAGE output to `image_0`.\n2. Describe the requested edit and what should remain unchanged.\n3. Refer to the source image as `` in the prompt.\n\n**Multi-reference generation or editing**\n1. Connect additional Load Image nodes to `image_1`, `image_2`, etc.\n2. Refer to the connected pictures in the prompt as ``, ``, etc.\n3. Describe each image's purpose, such as subject, outfit, composition, or background.\n\n**Settings**\n- Aspect-ratio selector with adjustable 4–20 MP target resolution.\n- Sampler: **Euler**; scheduler: **Simple**; **6 steps**, **CFG 1**, **denoise 1**.\n- Prompt enhancement is not included.\n- Connect the VAE for editing so the reference images can also condition the latent representation.\n\n**Links**\n- YouTube: https://youtube.com/@zetalvx\n- Patreon: https://www.patreon.com/Zetalvx\n- GitHub: https://github.com/ZETALVX" ], "widgets_values_named": { "text": "# ZetaLvX | MiniMax H3 Image\n### Text-to-image · Image editing · Multi-reference\n\nThe same model supports image generation and image editing. Connect reference images only when needed.\n\n**Text-to-image**\n1. Keep all `image_0`–`image_15` inputs disconnected.\n2. Enter a generation prompt in **PROMPT**.\n3. Set the aspect ratio and target megapixels, then run the workflow.\n\n**Image editing**\n1. Add a built-in **Load Image** node and connect its IMAGE output to `image_0`.\n2. Describe the requested edit and what should remain unchanged.\n3. Refer to the source image as `` in the prompt.\n\n**Multi-reference generation or editing**\n1. Connect additional Load Image nodes to `image_1`, `image_2`, etc.\n2. Refer to the connected pictures in the prompt as ``, ``, etc.\n3. Describe each image's purpose, such as subject, outfit, composition, or background.\n\n**Settings**\n- Aspect-ratio selector with adjustable 4–20 MP target resolution.\n- Sampler: **Euler**; scheduler: **Simple**; **6 steps**, **CFG 1**, **denoise 1**.\n- Prompt enhancement is not included.\n- Connect the VAE for editing so the reference images can also condition the latent representation.\n\n**Links**\n- YouTube: https://youtube.com/@zetalvx\n- Patreon: https://www.patreon.com/Zetalvx\n- GitHub: https://github.com/ZETALVX" }, "color": "#432", "bgcolor": "#653" }, { "id": 15, "type": "MarkdownNote", "pos": [ -169.6878897987749, 405.6601065548359 ], "size": [ 540, 540 ], "flags": {}, "order": 5, "mode": 0, "inputs": [], "outputs": [], "title": "MODEL FILES", "properties": { "Node name for S&R": "MarkdownNote", "cnr_id": "comfy-core", "ver": "0.45.0" }, "widgets_values": [ "# Model files\n**Diffusion model**\n`minimax_h3_image_pruned_int8_convrot.safetensors`\n\n**Text encoder**\n`qwen3vl_32b_minimax_h3_int8_convrot.safetensors`\n\n**VAE**\n`minimax_h3_image_vae_fp16.safetensors`\n\nThe same model configuration is used for text-to-image and image editing. Image references are optional.\n\n### Prompt enhancement\nAn additional prompt-enhancement model is not required by this workflow. You can write a detailed prompt directly in the conditioning node." ], "widgets_values_named": { "text": "# Model files\n**Diffusion model**\n`minimax_h3_image_pruned_int8_convrot.safetensors`\n\n**Text encoder**\n`qwen3vl_32b_minimax_h3_int8_convrot.safetensors`\n\n**VAE**\n`minimax_h3_image_vae_fp16.safetensors`\n\nThe same model configuration is used for text-to-image and image editing. Image references are optional.\n\n### Prompt enhancement\nAn additional prompt-enhancement model is not required by this workflow. You can write a detailed prompt directly in the conditioning node." }, "color": "#432", "bgcolor": "#653" }, { "id": 16, "type": "MarkdownNote", "pos": [ 1091.7141704423227, 205.2204328980684 ], "size": [ 593.2988782180726, 526.944215146494 ], "flags": {}, "order": 6, "mode": 0, "inputs": [], "outputs": [], "title": "RESOLUTION / QUALITY", "properties": { "Node name for S&R": "MarkdownNote", "cnr_id": "comfy-core", "ver": "0.45.0" }, "widgets_values": [ "# Resolution and quality\nThe model renders directly at the requested resolution: **no upscaler is used**.\n\nReference ~16–17 MP sizes published by MiniMax:\n- Square: `4096 × 4096`\n- 4:3: `4736 × 3552`\n- 3:2: `5024 × 3360`\n- 16:9: `5472 × 3072`\n- 21:9: `6272 × 2688`\n\nThe dynamic control uses **exact decimal megapixels** (1 MP = 1,000,000 pixels), so it does not try to force the exact preset dimensions from the official table.\n\nFor clean comparisons: keep the same seed, prompt, steps, and sampler.\n\nSteps are **6** because the model is distilled and does not use a classic negative prompt or standard CFG workflow.\n" ], "widgets_values_named": { "text": "# Resolution and quality\nThe model renders directly at the requested resolution: **no upscaler is used**.\n\nReference ~16–17 MP sizes published by MiniMax:\n- Square: `4096 × 4096`\n- 4:3: `4736 × 3552`\n- 3:2: `5024 × 3360`\n- 16:9: `5472 × 3072`\n- 21:9: `6272 × 2688`\n\nThe dynamic control uses **exact decimal megapixels** (1 MP = 1,000,000 pixels), so it does not try to force the exact preset dimensions from the official table.\n\nFor clean comparisons: keep the same seed, prompt, steps, and sampler.\n\nSteps are **6** because the model is distilled and does not use a classic negative prompt or standard CFG workflow.\n" }, "color": "#432", "bgcolor": "#653" }, { "id": 18, "type": "MarkdownNote", "pos": [ 436.3744084295813, 278.52936169189866 ], "size": [ 600, 570 ], "flags": {}, "order": 7, "mode": 0, "inputs": [], "outputs": [], "title": "IMAGE INPUTS / PROMPT REFERENCES", "properties": { "Node name for S&R": "MarkdownNote" }, "widgets_values": [ "# Image inputs and prompt references\n\nThe inputs on the ComfyUI node are named `image_0` through `image_15`. MiniMax H3 Image identifies connected pictures in the text prompt using **``, ``, ...**.\n\n| ComfyUI input | Prompt reference when connected in order |\n|---|---|\n| `image_0` | `` |\n| `image_1` | `` |\n| `image_2` | `` |\n| ... | ... |\n| `image_15` | `` |\n\n**The numbering in the prompt follows the order of connected images.** Empty inputs are skipped. For predictable references, connect images consecutively from `image_0`.\n\n### Prompt examples\n**Editing one image:**\n`Edit by changing the jacket to red. Preserve the subject's identity, face, pose, and background.`\n\n**Combining references:**\n`Use for the subject, for the outfit, and for the background. Create a realistic cinematic photograph.`\n\n**Without image inputs:**\nWrite a normal text-to-image prompt; do not include picture references.\n\nThe 16 input slots are optional. Additional connected references may increase memory usage and processing time.\n" ], "widgets_values_named": { "text": "# Image inputs and prompt references\n\nThe inputs on the ComfyUI node are named `image_0` through `image_15`. MiniMax H3 Image identifies connected pictures in the text prompt using **``, ``, ...**.\n\n| ComfyUI input | Prompt reference when connected in order |\n|---|---|\n| `image_0` | `` |\n| `image_1` | `` |\n| `image_2` | `` |\n| ... | ... |\n| `image_15` | `` |\n\n**The numbering in the prompt follows the order of connected images.** Empty inputs are skipped. For predictable references, connect images consecutively from `image_0`.\n\n### Prompt examples\n**Editing one image:**\n`Edit by changing the jacket to red. Preserve the subject's identity, face, pose, and background.`\n\n**Combining references:**\n`Use for the subject, for the outfit, and for the background. Create a realistic cinematic photograph.`\n\n**Without image inputs:**\nWrite a normal text-to-image prompt; do not include picture references.\n\nThe 16 input slots are optional. Additional connected references may increase memory usage and processing time.\n" }, "color": "#432", "bgcolor": "#653" }, { "id": 19, "type": "LoadImage", "pos": [ -1264.0962051695783, -28.351779567149833 ], "size": [ 966.6932844716769, 569.2047913305175 ], "flags": {}, "order": 8, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 21 ] }, { "name": "MASK", "type": "MASK", "links": [] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "LoadImage" }, "widgets_values": [ "ZetaLvX_MiniMax_H3_T2I_00029_.png [output]", "image" ], "widgets_values_named": { "image": "ZetaLvX_MiniMax_H3_T2I_00029_.png [output]", "upload": "image" } }, { "id": 20, "type": "PrimitiveFloat", "pos": [ -1265.7044263916016, -690.0144467010498 ], "size": [ 250, 92 ], "flags": { "collapsed": true }, "order": 9, "mode": 0, "inputs": [], "outputs": [ { "name": "FLOAT", "type": "FLOAT", "links": [ 22 ] } ], "title": "Fixed ratio reference (internal)", "properties": { "cnr_id": "comfy-core", "ver": "0.45.0", "Node name for S&R": "PrimitiveFloat" }, "widgets_values": [ 16 ], "widgets_values_named": { "value": 16 } } ], "links": [ [ 11, 5, 0, 10, 0, "MODEL" ], [ 12, 8, 0, 10, 1, "CONDITIONING" ], [ 13, 8, 0, 9, 0, "CONDITIONING" ], [ 14, 9, 0, 10, 2, "CONDITIONING" ], [ 15, 8, 1, 10, 3, "LATENT" ], [ 16, 10, 0, 11, 0, "LATENT" ], [ 17, 7, 0, 11, 1, "VAE" ], [ 18, 11, 0, 12, 0, "IMAGE" ], [ 19, 11, 0, 13, 0, "IMAGE" ], [ 9, 6, 0, 8, 0, "CLIP" ], [ 10, 7, 0, 8, 1, "VAE" ], [ 21, 19, 0, 8, 2, "IMAGE" ], [ 7, 3, 1, 8, 4, "INT" ], [ 8, 4, 1, 8, 5, "INT" ], [ 22, 20, 0, 1, 0, "FLOAT" ], [ 1, 1, 0, 3, 0, "INT" ], [ 2, 1, 1, 3, 1, "INT" ], [ 3, 2, 0, 3, 2, "FLOAT" ], [ 4, 1, 0, 4, 0, "INT" ], [ 5, 1, 1, 4, 1, "INT" ], [ 6, 2, 0, 4, 2, "FLOAT" ] ], "groups": [ { "id": 1, "title": "1 — FORMATO e MP", "bounding": [ -1270, -675, 970.1579103452759, 582.0966430544435 ], "color": "#596f95", "flags": {} }, { "id": 2, "title": "2 — MODELLI", "bounding": [ -250, -675, 585, 748 ], "color": "#c28a54", "flags": {} }, { "id": 3, "title": "3 — PROMPT e SIZE", "bounding": [ 370, -675, 680, 768 ], "color": "#5b9d6c", "flags": {} }, { "id": 4, "title": "4 — SAMPLING", "bounding": [ 1092.6388972349741, -651.9444806833794, 565, 738 ], "color": "#8c6286", "flags": {} }, { "id": 5, "title": "5 — OUTPUT", "bounding": [ 1706.1108011690271, -692.2915900157541, 1089.7606070922848, 912.846 ], "color": "#52a2a5", "flags": {} } ], "config": {}, "extra": { "ds": { "scale": 0.513158118230707, "offset": [ 1680.5809393388286, 1060.2177060504428 ] }, "frontendVersion": "1.53.6", "VHS_latentpreview": false, "VHS_latentpreviewrate": 0, "VHS_MetadataImage": true, "VHS_KeepIntermediate": true }, "extensions": { "seed_widgets": { "10": 0 } }, "version": 0.4 }