✨ Qwen-Image 2.1 Glamour Portrait — 4-Mode Auto-Prompt Workflow (SFW, 16GB)

ComfyUI · Qwen-Image 2.1 · one control panel · Built with Qwen

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Pick a MODE, press Queue, get a finished 4:5 portrait. The workflow writes its own prompt: a built-in list of scene ideas (200 per mode) is expanded by Qwen3-VL 8B running inside ComfyUI into a detailed photographic paragraph, a clothing guard keeps every image inside the MODE you chose, and Qwen-Image 2.1 renders it. No LoRA is included or needed. All subjects are fictional, AI-generated adults. Tested on an RTX 5080 16 GB.

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✨ Features

✅ One CONTROL PANEL, top-left — MODE, subject source, upscale switch, seed. Everything else is "Engine — no need to touch"

✅ 4 MODEs — 1 Everyday · 2 Fitted outfit · 3 Swimwear · 4 Lingerie (opaque, lined). Clothing guards are built in

✅ Random from the built-in list, or "My own idea" — type your own scene line; the expander and guards still apply

✅ Auto-prompt expander inside the graph — Qwen3-VL 8B (same file as the text encoder, no extra download)

✅ Hands-friendly prompt wording — simple hand anchors, no finger descriptions

✅ Optional Upscale — SeedVR2 2× (1792×2240 → 2560×3200), OFF by default

✅ Empty "Optional LoRA" slot — bypassed; drop in your own LoRA if you want one

✅ Civitai metadata embedded — model hash, prompt, seed, sampler in every PNG (Image Saver)

✅ No external files — all 4 subject lists are inside the workflow

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📦 Required Models (3 files, ≈17.3 GB)

• qwen_image_2.1_int8_convrot.safetensors (7.26 GB) — diffusion model → ComfyUI/models/diffusion_models/

• qwen3vl_8b_int8_convrot.safetensors (9.35 GB) — text encoder AND prompt expander → ComfyUI/models/text_encoders/

• qwen_image_2.1_vae_bf16.safetensors (0.68 GB) — VAE → ComfyUI/models/vae/

Optional upscale (only if you turn Upscale ON):

• seedvr2_ema_7b_fp16.safetensors (16.48 GB) + ema_vae_fp16.safetensors (0.50 GB) → ComfyUI/models/SEEDVR2/

• Lighter option: seedvr2_ema_3b_fp16.safetensors (6.78 GB) — in our 2-image check it matched the 7B on face and skin detail at 100% and ran at the same speed, a good choice if you have less RAM

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⬇️ Download Links (Hugging Face)

• https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/diffusion_models/qwen_image_2.1_int8_convrot.safetensors

• https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/text_encoders/qwen3vl_8b_int8_convrot.safetensors

• https://huggingface.co/Comfy-Org/Qwen-Image-2.1/resolve/main/vae/qwen_image_2.1_vae_bf16.safetensors

• SeedVR2 (optional): https://huggingface.co/numz/SeedVR2_comfyUI/tree/main

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🧩 Required Custom Nodes (all installable with ComfyUI-Manager)

1. WAS Node Suite — https://github.com/WASasquatch/was-node-suite-comfyui

2. ComfyUI-Impact-Pack — https://github.com/ltdrdata/ComfyUI-Impact-Pack

3. rgthree-comfy — https://github.com/rgthree/rgthree-comfy

4. ComfyUI_essentials — https://github.com/cubiq/ComfyUI_essentials

5. ComfyUI-Image-Saver — https://github.com/alexopus/ComfyUI-Image-Saver

6. ComfyUI-SeedVR2_VideoUpscaler (only for the optional Upscale) — https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler

Everything else is ComfyUI core. ComfyUI v0.37.0 or newer is required (Qwen-Image 2.1 nodes).

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🚀 How to Use

1. Download the 3 model files into the folders above. The loaders already use these exact file names.

2. In the CONTROL PANEL pick MODE: 1 Everyday · 2 Fitted outfit · 3 Swimwear · 4 Lingerie.

3. Press Queue. A new random image is made every run.

Optional:

• Subject source = 2 and type a scene in "My own idea" (for example: full body, red satin dress, rooftop bar at golden hour)

• Upscale: tick it in the switch on the left

• Several images: raise Batch count next to the Queue button

• Person box: the default is "Korean woman in her mid 20s" — change it to any adult you like

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⚙️ Settings & Parameters

• Size: 1792×2240 (4:5 portrait) · Sampler: euler / simple · Steps: 25 · CFG: 1.0

• Seed: randomize each run (switch to "fixed" in the Seed node to repeat an image)

• Expander: Qwen3-VL 8B, temperature 0.7, max 400 tokens, plus 3 small clean-up steps

• Output: PNG with Civitai metadata, saved to ComfyUI/output/qwen21_glamour/<mode>/

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💡 Performance Tips

• Base image 1792×2240: about 70 s on an RTX 5080 16 GB (first run is slower while models load). Upscale adds about 30 s.

• Upscale is OFF by default so first runs work on 16 GB VRAM / 32 GB RAM. The 7B upscale model needs about 48 GB RAM; if you turn it on with less, use the 3B model.

• Want it faster? Put the Viggle Turbo LoRA for Qwen-Image 2.1 into the empty Optional LoRA slot and set steps to 6 (not tested with this workflow's tuning): https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo — credit: Viggle (optional, not included)

• Pairs well with "Qwen Image 2.1 Fix v1.0" by Envy (optional, not included, not needed): https://civarchive.com/models/2957332

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🔗 Cross-links

A separate adult-content version of this workflow will be published later and will link back to this page. Follow my profile for more ComfyUI workflows.

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📝 Notes & AI Disclosure

• All images are AI-generated with Qwen-Image 2.1 and show fictional adult people — no real person is depicted.

• Clothing guards are prompt-based: check every image before you post it. Discard anything unclear or cropped.

• Content rating for the showcase images: PG-13.

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⭐ Found this useful?

• Like if it saved you time

• Comment your results — I read every one

• Follow for new ComfyUI workflows, all tested on 16 GB VRAM

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⚖️ Model Attribution & Licensing

Built with Qwen. Qwen-Image 2.1 by the Qwen team (Alibaba) — model files from Comfy-Org/Qwen-Image-2.1 on Hugging Face; please read the licence on that repository. Prompt expander: Qwen3-VL 8B (same repository).

• SeedVR2 (upscale): ByteDance-Seed, Apache-2.0; ComfyUI node by numz

• Node packs: WAS Node Suite (MIT), ComfyUI-Impact-Pack (GPL-3.0), rgthree-comfy (MIT), ComfyUI_essentials (MIT), ComfyUI-Image-Saver (MIT)

• Optional, not included: Qwen Image 2.1 Fix v1.0 by Envy (Civitai) · Viggle Turbo LoRA for Qwen-Image 2.1 by Viggle (Hugging Face)

Workflow JSON: CC0 Public Domain (free to reuse, no credit required).

🔗 Workflow by Thinni — feedback welcome!