How to Choose a Text-to-Image Model? Which Text-to-Image Model Is Best? A Full Breakdown of 12 NadouPro Image Models

With the exact same prompt, different models can produce dramatically different images: some excel at photorealistic portraits, some specialize in graphic layout, and some win on generation speed. Choosing a text-to-image model is never about "which one is the strongest," but "which one best fits your scenario."

NadouPro includes 12 mainstream image models, covering cinematic visuals, commercial design, photorealistic photography, ultra-fast generation, and more. This article first explains how text-to-image models work and how to compare them, then lays out the positioning and selection method for each model in NadouPro.

How Text-to-Image Models Work

Text-to-image models turn natural language into images by learning correspondences from massive paired datasets of "images + descriptions": patterns among words and objects, colors, materials, and spatial relationships.

The generation process roughly has three steps:

1. Understanding the prompt. The system first encodes the text into a form the model can read, identifying the subject, attributes, and context.

2. Generating the image step by step. The mainstream approach is diffusion: starting from visual noise, the model denoises step by step according to the prompt, gradually forming outlines, details, and style. Some models use an autoregressive approach, building visual elements one by one in sequence. For an overview of diffusion models, see Text-to-image Diffusion Models in Generative AI: A Survey.

3. Refining the output. After the image takes shape, details are adjusted, or the image enters an editing workflow for further changes.

The same prompt performs differently across models partly because of differences in generation architecture, and partly because of the input types each model can understand. A text-only model and a multimodal model that can also read images and reference materials have completely different ceilings.

Compare Text-to-Image Models Across These Six Dimensions

Comparison Dimension	What to Look For	Why It Matters
Prompt understanding	How well it restores the subject, attributes, object relationships, composition, and required details	No matter how polished an image is, it fails if it misses the prompt
Reference capability	Number of reference images, subject preservation, style transfer, composition guidance	Determines whether characters and products can remain consistent across images
Image editing	Local edits, natural-language editing, whether untouched areas remain intact	Precise edits save you from regenerating the entire image
Visual consistency	Whether characters, clothing, products, and style stay stable across a series of images	The lifeline of series assets, storyboards, and image sets
Style control	Lighting, color palette, texture, photographic feel, illustration style	The prerequisite for visual unity across a group of assets
Workflow continuity	Editing, exporting, and image-to-video handoff	What happens after generation is often just as important as the first image

If you only need one concept image, prompt understanding and image quality are enough. For product image sets, fixed characters, and series assets, reference capability, editing, and consistency are the real hard requirements.

How to Choose Among the 12 Image Models in NadouPro

The following positioning comes from the model quick-reference table in the official NadouPro documentation center. Match each model to your use case:

For cinematic and commercial blockbuster visuals

• Seedream 5.0 Pro: cinematic visuals and high-density graphic design, suitable for posters, infographics, and design assets;

• Seedream 5.0 Lite: cost-effective with strong understanding, a main choice for everyday creation;

• Seedream 4.5: multi-image editing and stable text generation, suitable for composite edits based on reference images;

• Seedream 4.0: integrated generation and editing.

For photorealism and text layout

• GPT Image 2.5 Sunburst: a next-generation flagship image model with lossless image quality during continuous editing, suitable for projects that require repeated refinement;

• GPT Image 2.5 Flare: a next-generation efficient model for fast, high-quality image generation;

• GPT Image 2: photorealistic photos with accurate text and layout restoration, the first choice for packaging and signage images;

• Nano Banana 2: ultra-fast generation, good text rendering, and stronger consistency, suitable for batch image runs;

• Nano Banana Pro: multi-image fusion with better results

For aesthetic quality

• MJ 8: high-end aesthetics, native HD;

• MJ 7: high-end aesthetics, delicate texture.

For full-process editing

• Kling O1: full-process image editing from basic to advanced.

A one-sentence shortcut: choose Seedream 5.0 Pro for a cinematic feel, GPT Image 2.5 Flare or Nano Banana 2 for speed, GPT Image 2 for precise text, GPT Image 2.5 Sunburst for repeated refinement, Nano Banana Pro for multi-image fusion, and Kling O1 for deep editing.

Quick Reference: Choose a Model by Scenario

Your Need	What to Prioritize	NadouPro Recommendation
Quick concept image	Generation speed, prompt understanding	GPT Image 2.5 Flare, Seedream 5.0 Lite
Fixed character / product image set	Reference capability, detail preservation	GPT Image 2.5 Sunburst continuous editing, Nano Banana multi-image fusion
Frequent revisions and rework	Local editing, lossless refinement	GPT Image 2.5 Sunburst, Kling O1
Marketing assets, posters	Graphic layout, unified style	Seedream 5.0 Pro, GPT Image 2
Batch image runs	Speed, consistency	Nano Banana 2
Turn generated images into video afterward	Reference materials, subject stability	After image generation, go directly into a video node for image-to-video; the reference image serves as the starting frame

Beyond Generation: Three Features That Make Models Easier to Use

Use fusion mode for multi-reference creation. The fusion mode in the NadouPro image node supports generating new images based on reference images: feed multiple reference images to the model, with the subject, clothing, scene, and style each defined by different references, while the prompt explains how these elements should be combined. Keeping a character consistent across images and transferring the style of one image to another both follow this path.

Use image editing for local changes. When you are generally satisfied with an image and only want to change a local area, use image editing capabilities: erase, cutout, redraw, depth map, crop, and grid splitting are all included. To change an object’s color, material, or background, you do not need to start the entire image over. The cutout with a transparent background can be used directly for product images and design layouts.

Use HD upscaling for output size. When large-size delivery is required, use image HD upscaling to bring the image to a high resolution. In the generation stage, first use a fast model to lock in the composition; after finalizing, refine it and add HD upscaling for the best efficiency.

Frequently Asked Questions

Q: What is the biggest difference between text-to-image models?
First, the precision of prompt understanding; second, the types of input they can understand. Models that only take text have a limited ceiling, while models that can take reference images and support multimodal input can handle long-term projects such as character consistency and style continuity.

Q: Which model in NadouPro is the most realistic?
For photorealism, GPT Image 2 is the first choice, specializing in photorealistic photos and precise text layout. For overall image quality and room for refinement, use GPT Image 2.5 Sunburst.

Q: Can text-to-image models use reference images?
Yes. NadouPro’s fusion mode supports generation with reference images and text prompts together. Reference images define the subject, composition, and style, while the prompt explains what to change. If the same character or product needs to remain recognizable across multiple images, fusion mode is the most stable path.

Q: How do I remove the background from an image?
Use the cutout capability in image editing to isolate the subject. Transparent backgrounds are suitable for product images, presentations, and social media assets. After cutting out, remember to check the edges of hair, clothing, and small objects before deciding whether to use a transparent background, a solid-color background, or place the subject into a new scene.

Q: Can I still edit an image after it has been generated?
Yes. Image editing supports local changes such as erase, redraw, and crop. Parts that need to be completely redone can be regenerated through fusion mode. After editing, upscale the resolution once with HD upscaling to ensure delivery quality.

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Contains AI-generated information that may be incorrect. Please verify independently.