How to Choose an AI Image Generator: Hard Criteria, NadouPro Selection Methods, and Workflow Fit

A good first image does not mean the generator is right for you. The real differences appear in what happens next: whether it still follows your prompt as the prompt gets more detailed, whether it can work from a reference image, whether it still recognizes the character after generating ten images in a row, and whether you need to start over when making the fifth revision. This article provides a practical selection framework and explains how to match each criterion with NadouPro's actual capabilities.

Start with four hard criteria when choosing a tool

Criterion 1: Prompt adherence

Writing a detailed prompt is the fastest test method. Ask the model to handle specific requirements at the same time, such as the subject, spatial relationships, quantity, text, and light direction, then see how many it misses. Weaker models may perform acceptably with broad descriptions, but once the requirements become specific, they start improvising.

To test this criterion in NadouPro, it is recommended to use Nano Banana 2 or Seedream 5.0 lite directly: the former understands instructions precisely and renders text well, while the latter has solid semantic understanding and low image-generation cost, making it suitable for repeated trial and error. The Photo Parameters feature provides more structured control: Focal Length, Depth of Field, Color Science, and Lens Set offer more than 300 preset combinations across four dimensions. It applies to the Text to Image and Image Fusion modes of GPT Image 2, Nano Banana Pro, and Nano Banana 2, effectively extending "adherence" from language into visual lens language.

Criterion 2: Ability to carry over reference images

Text can describe an idea, but existing characters, products, packaging, and styles can only be conveyed through reference images. During evaluation, focus on two things: whether key details from the reference image are carried into the new image, and whether the model can take what it needs from multiple reference images instead of mixing everything together.

NadouPro's Image Fusion mode is designed for this: upload reference images so that image details, subject silhouettes, color tone, and style can continue from existing materials into a new image. In multi-image scenarios, Nano Banana Pro's advantage is more precise instruction following, making it possible to clearly distinguish what task each reference image should serve. When continuous editing is needed without quality loss, GPT Image 2.5 Sunburst can maintain lossless image quality through continuous edits.

Criterion 3: Cross-image consistency

A single image has a large margin for error; a series of images has a very small one. Shot sequences, serialized content, poster series, and characters appearing across multiple scenes all require the face, clothing, key props, and overall visual direction to remain stable across images. The evaluation method is straightforward: use the same character description to generate five images in different scenes, then count how often the facial features and clothing drift.

NadouPro handles consistency in three layers. First, Multi-Grid capabilities can generate multiple angles of the same character in one go, such as Character Body 3-View, Character Face 3-View, Character Expression 9-Grid, and character profile images, which serve as reference anchors for later generation. Second, Image Fusion can continue the process by feeding finalized character-design images as reference images into subsequent shots. Third, canvas arrangement lets you organize character references, scene references, and generation nodes on one canvas, so all materials for the series can be managed and reused in the same workspace.

Criterion 4: Iteration cost

The first version is rarely the final version. To evaluate iteration cost, look at three questions: do you need to regenerate the entire image to change one area, can you keep editing after one change, and does the image quality hold up when upscaling for delivery?

NadouPro's image editing covers common revision scenarios: removing clutter, cutting out and replacing backgrounds, repainting local areas, cropping and reframing, and adjusting depth maps, along with Portrait Enhancement, facial retouching, and Relight for people-focused refinements. Once the direction is right, use upscaling capabilities to raise the resolution for delivery. The entire chain can be completed within the same platform, without moving assets between multiple tools.

Workflow differences: match the tool to three typical scenarios

Beyond the criteria, different workflows place very different emphasis on capabilities. Matching the scenario is more effective than reading a feature list.

Exploratory creation from scratch: The idea is still at the language stage, and you need to quickly open up multiple visual directions. This type of work depends on Text to Image speed and style coverage. NadouPro's twelve image models each have their own character, such as Midjourney 8 for advanced aesthetics, GPT Image 2 for ultra-realism, and Nano Banana 2 for extremely fast image output. Run the same prompt through different models once, and the differences in direction become clear at a glance.

Continuation-based creation from existing materials: A product already has packaging images, a character already has design sheets, or a brand already has an established visual identity. The core of this type of work is the carryover quality of Image Fusion; whether the reference image can be understood accurately determines the amount of rework. Product images changing scenes, characters changing poses, and existing styles extending into new images all start here.

Series-based creation for complete sets of output: Multiple assets for a marketing campaign, multiple frames for a storyboard, or a fixed visual identity for a content column. This type of work values both consistency and efficiency: use Multi-Grid to lock the character first, use Image Fusion to maintain continuity, and use the canvas for centralized management. For example, if a brand campaign needs one key visual plus six extension images, after the key visual is approved, use it as a reference image and generate the extension images in batches on the canvas, keeping the visual direction unified and controllable.

Compliance self-checklist before commercial delivery

Meeting image-quality standards is only half of delivery. Before entering ad placement, product pages, or client projects, these six items are worth checking one by one:

Check the platform terms of use: Confirm the authorization scope for the commercial scenario on the platform you use, including advertising, merchandise production, client projects, and more. NadouPro's Beans system provides commercial licensing options; the specific details are subject to what is displayed on the platform page.

Confirm the rights to reference materials: For uploaded product images, portraits, illustrations, and logos, make sure you own the rights or have obtained authorization. AI processing does not remove the rights restrictions attached to the original materials.

Check for unintended brand elements: After high-resolution upscaling, carefully inspect whether the image contains logos, packaging designs, or iconic visual elements that resemble existing brands, especially in photorealistic generation results.

Handle recognizable real people with caution: If a commercial image includes a likeness highly similar to a real person, it may involve portrait and endorsement issues. This should be avoided especially in ad placement scenarios.

Avoid misleading expression: Product renderings, before-and-after comparisons, and effect-demonstration images can be misleading if they show functions or effects that the product does not have.

Keep records of the creation process: The degree of human creative input can affect rights determinations. Keeping prompts, reference images, and revision records can help with possible future ownership explanations.

FAQ

Q: If I do not have a clear requirement, which model should I try first?
Start with lower-cost models to explore directions, such as Seedream 5.0 lite or GPT Image 2.5 Flare. After confirming the style, switch to a model that is stronger in the relevant area for refined output. NadouPro's twelve image models each have their own positioning, and the documentation center has a complete capability quick-reference table for comparison.

Q: How should Text to Image and Image Fusion work together?
Text to Image is responsible for exploring directions from scratch, while Image Fusion is responsible for extending from existing materials. A typical process is: use Text to Image to create concepts, choose a direction, then use the finished image or design sheet as a reference image and use Image Fusion to extend new scenes in batches. The two can be connected into a complete workflow on the canvas.

Q: How can I tell whether a generated result can be used commercially right away?
Three conditions must be met at the same time: the platform terms allow the corresponding commercial scenario, the rights to the reference materials are clean, and the image has no infringement or misleading-risk issues. If any one of these is uncertain, resolve it before delivery.

Q: My series images are always inconsistent. Is there a systematic solution?
Yes. First use Multi-Grid to produce finalized design materials for the character or scene, use those finalized images as reference images throughout every subsequent generation, and manage all images on the same canvas. Consistency depends on anchors, not luck.

Q: What is going on when platforms detect AI-generated images?
Some platforms identify AI content based on source information embedded in the image or voluntary declarations from creators. Detection methods and labeling requirements vary. The safer approach is to proactively understand the AI-content labeling rules of the placement platform and disclose according to those rules.

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