How to Create Better AI Images
A useful AI image workflow is less about finding one perfect prompt and more about making clear choices: define the subject, choose a model, compare the first result, and refine the details that matter.
WaveSpeedAI lets you run models such as Nano Banana, Seedream, GPT Image, Qwen Image, FLUX, and WAN from one generator. Because each model interprets prompts and references differently, testing the same idea across two models can save time.
The steps below work for text-to-image generation and for edits that begin with one or more reference images.
Step 1: Write a Specific Prompt
Begin with the subject and action. Then add only the details that affect the result: environment, composition, viewpoint, lighting, color, medium, mood, and any text that must be rendered.
Examples:
- A waist-up editorial portrait on a neon-lit Tokyo street, photographed at night with shallow depth of field
- A white ceramic skincare bottle on pale stone, soft window light from the left, clean ecommerce composition
- An anime courier crossing a desert city, wide establishing shot, warm sunset palette
When the image needs a logo, label, or headline, include the exact wording and describe its placement. Avoid stacking unrelated styles or conflicting camera instructions in the same prompt.
Step 2: Choose a Model for the Task
Choose based on the capability you need rather than a single overall ranking. Check whether the model supports text-to-image, editing, multiple references, the required aspect ratio, and the output resolution you plan to use.
For an important image, run the same prompt and reference set through two suitable models. Comparing real outputs is more reliable than choosing from a generic model ranking.
Step 3: Generate and Evaluate
Generate the first result, then evaluate the parts separately: subject accuracy, composition, hands and faces, typography, product details, background, and overall style.
Generation time varies by model, resolution, reference count, and current demand. The estimated price is shown before submission so you can compare options before generating.
Use starter credits for small tests. When comparing models, keep the prompt, aspect ratio, and references the same so the results are easier to judge.
Step 4: Refine or Export
If the composition is already close, use a supported editing model instead of restarting. Give a narrow instruction and state what should remain unchanged.
Common refinement tasks include:
- Changing or cleaning up a background
- Adjusting color, lighting, or material
- Creating campaign or layout variations
- Preserving a product or character across new scenes
Before publishing, review small details at full size and confirm that you have the necessary rights to any references, brands, people, or protected material in the image.
AI Image Model Comparison
Start with the capability your project requires, then compare real outputs.
Image models differ in prompt interpretation, reference-image support, typography, editing controls, speed, output size, and price. There is no single best choice for every prompt.
Use this table as a starting point. Check the controls shown for the selected model and test the same prompt across two candidates when consistency or fine detail matters.
| AI model | Best for | Key strengths |
|---|---|---|
| GPT Image2 | Natural-language generation and editing | Quality tiers, reference-based edits, layout and text instructions |
| Nano Banana Pro & 2 | Generation, editing, and reference-heavy workflows | Reference images, resolution and format controls, plus optional search on Nano Banana 2 |
| Seedream | Detailed images, design work, and editing | Prompt following, typography, composition, and multi-reference editing |
| FLUX | General image generation and editing | 9B text-to-image and editing with size and seed controls |
| Qwen Image | Multilingual prompts and structured edits | Chinese and English support, text rendering, multi-image editing |
| WAN | Image generation and editing in a video-model family | Text-to-image and image-edit variants alongside video workflows |
Practical AI Image Use Cases
AI-generated images are most useful when they support a clear task. These examples show where text-to-image, reference-based generation, and editing can shorten an early creative workflow while still leaving room for human review.
AI Images for Social Media Content
Create draft visuals in the dimensions and visual language of a campaign, then review text, faces, products, and brand details before publishing.
Popular social media use cases include:
- Social post and story concepts
- Video covers and YouTube thumbnails
- Campaign variations for different aspect ratios
- Editorial illustrations and reaction graphics
AI Product Photography for Ecommerce
Use a product reference to explore backgrounds, lighting, placement, and campaign directions. Preserve important packaging and shape details, and verify them against the original product before use.
With WaveSpeedAI, ecommerce businesses can generate:
- Product background and lighting concepts
- Lifestyle scene mockups
- Marketplace composition drafts
- Seasonal campaign variations
AI Marketing and Advertising Creatives
Generate multiple creative directions before committing production time. Keep brand constraints in the prompt and treat generated typography, claims, and product details as items that require review.
Common marketing use cases include:
- Ad and landing-page concepts
- Banner and email imagery
- Product launch moodboards
- Localized or audience-specific variations
AI Art, Anime, and Creative Design
Artists and designers can use generated images to explore composition, character, environment, and visual style before moving into a finished workflow.
Useful starting points include:
- Character and costume explorations
- Environment and prop concepts
- Storyboards and keyframes
- Illustration and style studies