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工作流 / 图像 / H3I Fixed! Extremely Simple 16MP workflow T2I (I2I Ready)
H3I Fixed! Extremely Simple 16MP workflow T2I (I2I Ready)

H3I Fixed! Extremely Simple 16MP workflow T2I (I2I Ready)

H3I Fixed! Extremely Simple 16MP workflow T2I (I2I Ready)

Simple MiniMax H3-Image workflow (text to image)A few people asked about blurry or weird eyes with the official ComfyUI template. The template has two problems: it renders at only 4 MP, and it uses euler. H3-Image works …

图像 18 个节点 42 次使用 VinPara 20 KB

下载工作流 JSON 查看官方来源

下载后把文件拖进 ComfyUI 窗口即可打开。

需要的权重

这个工作流引用了 1 个权重文件,其中 0 个能在本站模型库里找到。

MiniMax_H3-Image_simple_T2I.json 模型库暂未收录

节点构成

MarkdownNote × 2
SaveImage × 2
PrimitiveStringMultiline × 1
ResolutionSelector × 1
RandomNoise × 1
UNETLoader × 1
LoraLoaderModelOnly × 1
CLIPLoader × 1
VAELoader × 1
MiniMaxH3ImageConditioning × 1
BasicGuider × 1
SamplerLCM × 1
BasicScheduler × 1
SamplerCustomAdvanced × 1
VAEDecode × 1
ImageScaleBy × 1

官方标注的模型

minimax_h3_image_pruned_int8_convrot.safetensorsp-h3-image_vae_int8_convrot.safetensorsqwen3vl_32b_minimax_h3_nvfp4_awq.safetensorsyour_lora.safetensors

工作流 JSON

和上面「下载工作流 JSON」是同一份文件。

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3 "revision": 0,
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5 "last_link_id": 19,
6 "nodes": [
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18 "flags": [],
19 "order": 0,
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21 "inputs": [],
22 "outputs": [],
23 "title": "Read me",
24 "properties": {
25 "Node name for S&R": "MarkdownNote"
26 },
27 "widgets_values": [
28 "## MiniMax H3-Image · simple text to image\n\n**Models** (free, pick them in *Models*):\n\n| Folder | File | From |\n|---|---|---|\n| diffusion_models | `minimax_h3_image_pruned_int8_convrot` | Comfy-Org/MiniMax-H3-Image |\n| text_encoders | `qwen3vl_32b_minimax_h3_nvfp4_awq` (RTX 50) or the template's `..._int8_convrot` | Comfy-Org/MiniMax-H3-Image |\n| vae | `p-h3-image_vae_int8_convrot` (or the standard `minimax_h3_image_vae_fp16`) | PrunaAI/P-H3-Image-Comfy |\n\nComfyUI 0.45.0 or newer, core nodes only.\n\n**Prompt:** describe the picture in full sentences. No negative prompt, no prompt enhancer.\n\n**Keep:** 16 MP (lower = blurry eyes) and the gray *Sampling* group (SamplerLCM, 6 steps).\n\n**LoRA (optional):** the LoRA node is bypassed. Pick a LoRA, select the node and press **Ctrl+B**.\n\n**Output:** the half-size image is saved. The full 16 MP save is bypassed, **Ctrl+B** turns it on too.\n\n**Images:** see the blue note below."
29 ],
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48 "outputs": [],
49 "title": "Using images",
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52 },
53 "widgets_values": [
54 "## Using images (edit or reference)\n\nAdd a **Load Image** node and connect it to `image_0` on the *H3-Image conditioning* node in the gray group. A new slot appears for the next image. Up to 4 images work well.\n\n- In the prompt the images are `<Picture 1>`, `<Picture 2>` ... in slot order.\n- **Edit:** Picture 1 is the image to change. Say what changes and what stays, e.g. *\"Change her jacket to a red leather jacket. Her face, hair, pose and the background stay exactly as in <Picture 1>.\"* Set the aspect ratio in *Size & seed* to match Picture 1.\n- **Reference:** describe a new scene, e.g. *\"The woman from <Picture 1> sits in a street cafe ...\"*. The size comes from *Size & seed*.\n\nThe VAE is already connected, so nothing else needs to change."
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99 "Full body shot at a slightly low angle of a woman boxer standing in the corner of a boxing ring, front three-quarter to the camera, wrapping white tape around her right hand with her teeth holding the end of the tape. She has deep brown skin shining with sweat, dark brown eyes and long black hair in tight cornrow braids pulled into a high ponytail, and an athletic, muscular build. She wears a black sports bra, red satin boxing shorts with a gold waistband and black high-top boxing boots. She looks at the camera with a fierce, focused stare. Behind her are red ring ropes, a dark arena with blurred crowd silhouettes and a pair of red gloves hanging on the corner post. A bright spotlight from above makes the sweat on her shoulders glisten, with deep shadows below."
100 ]
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102 {
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104 "type": "ResolutionSelector",
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120 "type": "COMBO",
121 "link": null,
122 "widget": {
123 "name": "aspect_ratio"
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126 {
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128 "name": "megapixels",
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164 {
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176 },
177 "widgets_values": [
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180 32
181 ]
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183 {
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193 ],
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195 "order": 4,
196 "mode": 0,
197 "inputs": [
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199 "localized_name": "noise_seed",
200 "name": "noise_seed",
201 "type": "INT",
202 "link": null,
203 "widget": {
204 "name": "noise_seed"
205 }
206 }
207 ],
208 "outputs": [
209 {
210 "localized_name": "NOISE",
211 "name": "NOISE",
212 "type": "NOISE",
213 "links": [
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215 ]
216 }
217 ],
218 "title": "Seed",
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221 },
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224 "randomize"
225 ]
226 },
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264 "name": "MODEL",
265 "type": "MODEL",
266 "links": [
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268 ]
269 }
270 ],
271 "title": "H3-Image DiT",
272 "properties": {
273 "Node name for S&R": "UNETLoader"
274 },
275 "widgets_values": [
276 "minimax_h3_image_pruned_int8_convrot.safetensors",
277 "default"
278 ]
279 },
280 {
281 "id": 2,
282 "type": "LoraLoaderModelOnly",
283 "pos": [
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285 140
286 ],
287 "size": [
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290 ],
291 "flags": [],
292 "order": 6,
293 "mode": 4,
294 "inputs": [
295 {
296 "localized_name": "model",
297 "name": "model",
298 "type": "MODEL",
299 "link": 1
300 },
301 {
302 "localized_name": "lora_name",
303 "name": "lora_name",
304 "type": "COMBO",
305 "link": null,
306 "widget": {
307 "name": "lora_name"
308 }
309 },
310 {
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312 "name": "strength_model",
313 "type": "FLOAT",
314 "link": null,
315 "widget": {
316 "name": "strength_model"
317 }
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319 ],
320 "outputs": [
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323 "name": "MODEL",
324 "type": "MODEL",
325 "links": [
326 2,
327 3
328 ]
329 }
330 ],
331 "title": "LoRA (optional) · bypassed, Ctrl+B to enable",
332 "properties": {
333 "Node name for S&R": "LoraLoaderModelOnly"
334 },
335 "widgets_values": [
336 "your_lora.safetensors",
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338 ]
339 },
340 {
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342 "type": "CLIPLoader",
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351 "flags": [],
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388 "type": "CLIP",
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394 "title": "Text encoder (Qwen3-VL 32B)",
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416 "order": 8,
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432 "name": "VAE",
433 "type": "VAE",
434 "links": [
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437 ]
438 }
439 ],
440 "title": "VAE (P-H3 VAE, decodes + encodes images)",
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443 },
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514 "name": "positive",
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519 },
520 {
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528 ],
529 "title": "H3-Image conditioning",
530 "properties": {
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753 {
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873 }
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884 {
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