[Qwen Image 2.1] Character Design Sheet Maker (Workflow)

Changelog

V2.0

In version 2.0, based on community feedback, I redesigned the workflow to be much more task-focused: minimal unnecessary typography, maximum focus on key character elements, body structure, and facial details. This layout makes it drastically easier for video generation models to read character details and maintain consistency.

How It Works

The PE (Prompt Enhancer) generates 2 to 3 main panels:

1. Facial Expressions

2. Poses

3. Equipment & Accessories (optional)

This amount of information is ideal for video models to produce coherent, high-quality results.

Layout Rules & Features:

1. Faceless Entities: If the object or character does not have a human face (e.g., mask, robot, inanimate object), only a single neutral close-up panel is generated.

2. Expression Variety: The set of emotional expressions adapts to the character's backstory and description, but a neutral expression always comes first.

3. Gear & Accessories: If accessories or gear are present, a separate 3rd panel displays them in detail, isolated from the main character.

4. character_description Parameter: Helps the PE better understand character traits and posture. For instance, providing a description like "Ayaka is a slender, fragile girl. She is mostly shy, but occasionally gives a subtle smile" allows the PE to choose matching expressions and poses. This parameter is optional (the PE can infer details strictly from the image), but manually specifying details yields much higher accuracy.

Important Considerations:

1. Input Image: The workflow performs best when the reference image shows a full-body character facing forward. The PE is intentionally constrained from hallucinating missing body parts unless explicitly specified in the character_description. This prevents unwanted inconsistencies like altered height, age, or outfit details.

2. Two Workflow Variants: They differ only in how the PE prompt is generated:

   • For GPUs with <12GB VRAM: Use the standard version (without the _native_pe suffix).

   • The official Generate Text node is currently unoptimized for Qwen 3.5 9B, which can cause prompt generation on lower-end hardware to exceed 30 minutes. The developers are aware of this issue and working on performance fixes.

Summary of Changes (v2.0):

• Complete Redesign: Shifted focus from purely stylistic/artistic design sheets to a functional, production-ready Character Design Sheet optimized for video models.

• Updated Text Field: Replaced entity_name (name only) with character_description (full personality & detail specifications).

• Native PE Support: Added a secondary workflow utilizing the official PE execution method.

• Usability: Added clear explanatory comments inside the ComfyUI node graphs.

About this Workflow

This workflow allows you to generate detailed Character Design Sheets from a single reference image. These sheets can later be used as reference frameworks for video generation models like Seedance 2.5 or MiniMax H3.

In my experience, Qwen Image 2.1 is the first open-source image editing model capable of natively generating clean, highly detailed character design sheets right out of the box.

Recommended Settings

• CLIP Encoder: Use FP32 / FP16 / BF16 precision for maximum image quality and prompt adherence. Tests show that INT8 and other lower-bit quantizations introduce noticeable artifacts and reduce image clarity. Don't skimp on SSD space — install qwen3vl_8b_bf16.safetensors.

• Sampler & Scheduler: Use res_2m + beta to reduce artifacts and improve detail. While I haven't run extensive benchmarks on every combination, this pairing yielded the best results.

• Resolution (Megapixels):

  • 3.4 MP — Sweet spot for speed and clarity.

  • 6.0 MP — Superior quality and detail, though generation time increases significantly.

How to Use

1. Install custom nodes via ComfyUI Manager:

   • ComfyUI-KJNodes

   • ComfyUI-DeGrid

   • ComfyUI-ThinkingLLM (you can replace this with the standard Generate Text node if you want to use official Qwen Image 2.1 PE weights). Don't forget to install llama-cpp-python as specified here.

2. Download GGUF PE I2I weights and place them into ComfyUI/models/LLM/GGUF/.

   Important: Both the main PE model and the mmproj file must be present in this folder, otherwise ComfyUI-ThinkingLLM will not detect it.

3. Run generation: Load your reference image, select the path to the PE model, and start generating.

Useful Resources

• Official Qwen Image 2.1 Weight for ComfyUI: HuggingFace

• GGUF PE T2I: HuggingFace | GGUF PE I2I: HuggingFace