Image Generation
Tool comparison for AI image generation
Image Generation
What This Section Covers
AI image generation has moved from novelty to practical tool. You can describe what you want in plain English and get usable visuals for presentations, marketing materials, social media, concept work, and more. This section covers which tools do what, how to prompt them effectively, and where they actually fit into real workflows.
Honest assessment up front: AI-generated images are not replacements for professional design work or custom illustration. They are excellent for concepts, drafts, social content, presentations, and anything where “good enough fast” beats “perfect later.” For final marketing assets, brand materials, or anything customer-facing where quality matters, treat AI images as a starting point, not the finish line.
The Major Tools
DALL-E (ChatGPT)
DALL-E 3 lives inside ChatGPT, which is its biggest practical advantage. You’re already in the same conversation where you drafted the copy, outlined the presentation, or brainstormed the concept, so generating the image is seamless. The integration also means you can iterate naturally: “make it more blue,” “add a person in the foreground,” “change the style to watercolor.”
DALL-E’s strength is prompt adherence. If you describe something specific - “a golden retriever wearing a red bandana sitting on a front porch at sunset, watercolor style” - it will actually include all those elements. Some rival tools produce prettier images but miss details in your prompt. DALL-E is less likely to do that.
Where it fits best: People who already use ChatGPT. Situations where text and images need to match precisely - social posts, presentation slides, marketing concepts. Anyone who wants to iterate conversationally.
Pricing:
- Free: 3 images/day through ChatGPT
- Plus ($20/month): Unlimited image generation (note: OpenAI’s pricing and limits change frequently; verify current terms before subscribing)
What it’s good at: Following specific instructions, text-in-image generation (logos, signs with words), consistent style across variations.
What it struggles with: Extreme photorealism compared to some rivals, very complex compositions with many elements.
Midjourney
Midjourney lives in Discord and produces consistently beautiful images. It’s widely considered the best option for artistic quality, visual appeal, and “wow factor.” If you want something that looks stunning and you care less about precise control, Midjourney is the choice.
The Discord interface is a blessing and a curse. On one hand, it’s unintuitive if you don’t already use Discord. On the other, the community aspect is real - you can see what others are generating, learn from their prompts, and get inspired. Midjourney also has strong style transfer: upload a reference image and generate new images in that style.
Where it fits best: Creative professionals, social media content, concept art, anything where visual impact matters more than precise prompt adherence.
Pricing:
- Basic: ~$10/month (roughly 200 generations)
- Standard: ~$30/month (unlimited generations in “relax” mode)
- Pro and Mega: Higher tiers for heavy users
- Note: Pricing and exact features change frequently. Midjourney also sometimes offers annual discounts. Verify current plans and pricing before subscribing.
What it’s good at: Aesthetics, artistic styles, photorealism, landscapes, portraits. The community gallery is a constant source of inspiration and prompt ideas.
What it struggles with: Precise control, text in images (gets words wrong), specific positioning of elements. If you need “exactly this, exactly there,” you’ll need to iterate or edit afterward.
Stable Diffusion
Stable Diffusion is open source, which means two things: there are hundreds of variants and interfaces, and you can run it yourself on your own hardware for free. For technical users comfortable installing software and possibly troubleshooting, this is the most flexible and ultimately cheapest option.
For non-technical users, Stable Diffusion is most accessible through third-party services that host it for you - Stablecog, NightCafe, and dozens of others. These services add a layer of convenience and pricing on top of the base model.
The main advantage of Stable Diffusion is control and customization. If you’re willing to learn, you can use techniques like LoRA (training the model on specific styles or subjects), ControlNet (precise control over poses, compositions, and edges), and img2img (transforming one image into another). This is why it’s the default choice for people doing serious AI art, game assets, or highly specific visual work.
Where it fits best: Technical users who want maximum control. People who need to generate many images cheaply at scale. Anyone who wants to run AI locally for privacy or cost reasons.
Pricing:
- Free if you run it yourself (requires decent GPU, technical setup)
- Third-party hosting services: typically $5-20/month depending on usage
- Note: The ecosystem is fragmented and pricing varies widely by host
What it’s good at: Customization, control, cost at scale, privacy (local hosting), specialized use cases.
What it struggles with: Ease of use. You will need to read documentation and experiment. The learning curve is real.
Adobe Firefly
Adobe Firefly is integrated into Adobe’s ecosystem - Photoshop, Illustrator, Express, and the standalone Firefly web app. Its main selling point is that it was trained on Adobe Stock, public domain content, and licensed work, making it arguably the safest option for commercial use from a copyright perspective.
Firefly is particularly strong at practical design tasks: generating variations of an image, extending images beyond their borders (generative fill), recoloring vector art, and applying consistent styles. If you already use Adobe tools, Firefly is built in rather than being a separate workflow.
Where it fits best: Adobe users. Designers who need AI-assisted ideation within existing workflows. Teams concerned about copyright and commercial usage rights.
Pricing:
- Free tier: Limited monthly credits (around 25 generations/month)
- Included in many Adobe Creative Cloud plans
- Standalone Firefly subscription: ~$5-10/month for additional credits
- Note: Adobe’s pricing structure is complex and bundled. Verify based on your specific Adobe plan.
What it’s good at: Integration with Adobe workflows, generative fill in Photoshop, text effects, style transfer, commercial-safe training data.
What it struggles with: Standing alone as a general-purpose image generator. Firefly’s strength is in the design workflow, not as a one-to-one replacement for DALL-E or Midjourney.
Canva AI (Magic Media)
Canva’s AI image generation is built into a design tool that many people already use. The workflow is: generate an image, then immediately drop it into a presentation, social media post, flyer, or whatever else you’re building in Canva. This friction reduction matters more than it sounds like it would.
Canva integrates multiple AI models (including Stable Diffusion and DALL-E through partnerships), and the quality is good enough for most business use cases. The real advantage is the Canva ecosystem - templates, editing tools, brand kits, and a straightforward interface.
Where it fits best: Non-designers who need simple visuals. Small business owners, marketers, educators, anyone who already uses Canva.
Pricing:
- Free: Limited AI generations (roughly 50 uses/month across all Canva AI features)
- Pro ($12.99/month or ~$120/year): ~500 AI uses/month
- Note: Canva’s “uses” are shared across all AI features (Magic Write, Magic Edit, etc.), not just image generation. See full pricing details
What it’s good at: Integration with design templates, brand consistency, quick social media visuals, ease of use.
What it struggles with: High-end artistic quality compared to Midjourney or Stable Diffusion. Fine-tuned control.
Google (ImageFX and Imagen 3)
Google’s image generation (ImageFX is the consumer interface; Imagen 3 is the underlying model) is available through Google Labs and integrated into Gemini. Quality is competitive with the other major models, and the interface is straightforward.
The main reason to use Google’s tools is ecosystem integration. If you’re already in Google Workspace - generating images in Gemini and dropping them into Slides or using them in Google Docs - the workflow is seamless. For teams fully committed to Google’s ecosystem, this is worth considering.
Where it fits best: Google Workspace users. People who want a simple, no-frills image generator.
Pricing:
- ImageFX: Currently free through Google Labs (with usage limits)
- Included with Gemini AI Pro subscription ($19.99/month)
- Note: Google’s AI pricing and packaging changes frequently. Verify current terms.
What it’s good at: Simplicity, integration with Google tools, solid quality.
What it struggles with: Advanced features, fine-tuned control, community and ecosystem compared to Midjourney or Stable Diffusion.
Quick Comparison {#tool-comparison}
| Tool | Best For | Monthly Cost | Access |
|---|---|---|---|
| DALL-E | ChatGPT users, prompt adherence | $20 (ChatGPT Plus) or free tier | chatgpt.com |
| Midjourney | Artistic quality, visuals | $10-30+ | Discord |
| Stable Diffusion | Control, customization, scale | Free (self-hosted) or $5-20 | Multiple hosts |
| Adobe Firefly | Adobe workflows, commercial safety | Varies (Adobe plans) | firefly.adobe.com |
| Canva AI | Non-designers, quick visuals | $12.99 Pro tier | canva.com |
| Google Workspace users | Free tier or $19.99 (Gemini Pro) | labs.google, Gemini |
Note: Pricing is approximate and changes frequently. Verify all pricing and terms directly with providers before subscribing.
Prompting for Images: Practical Guidance {#prompting-for-images}
Image prompting is different from text prompting. The core principle is the same - be specific - but the details that matter are different. For foundational prompting principles that also apply to images, see Prompt Engineering: The Deep Dive.
Start with the subject: What is the image actually of? “A coffee shop on a rainy day” rather than “something cozy.”
Add style details: “Watercolor painting,” “photorealistic,” “1950s vintage poster style,” “minimalist flat design.” The style you specify dramatically changes the output.
Describe the composition: “Close-up shot,” “bird’s-eye view,” “rule of thirds,” “depth of field.” These terms tell the AI how to frame the image.
Set the mood: “Warm lighting,” “dramatic shadows,” “bright and cheerful,” “moody and atmospheric.”
Include quality keywords: “High resolution,” “detailed,” “sharp focus,” “professional photograph” - these consistently improve output quality.
A Good Prompt Template
[Subject] + [Action/Context] + [Style/Medium] + [Lighting/Mood] + [Composition] + [Quality keywords]
Example: “A golden retriever puppy sitting on a front porch, looking at the camera with head tilted, watercolor painting style, warm golden hour lighting, close-up portrait shot, detailed and professional”
Iteration Process
Start simple, then refine. First pass: “A coffee shop.” Second pass: “A cozy coffee shop on a rainy day, warm lighting through windows, people working at tables, photorealistic, high detail.” Third pass: “A cozy coffee shop on a rainy day, warm golden light spilling onto wet pavement, reflection in window, steam rising from coffee cup, cinematic lighting, photorealistic 8k.”
Each refinement adds detail and direction. Most images need 2-4 iterations to get what you’re actually envisioning.
What Most Beginners Get Wrong
Vague prompts: “Something professional” or “make it look good” produce generic results. Be specific about subject, style, and mood.
Overcrowding prompts: Too many unrelated concepts confuse the model. “A dog in space drinking coffee while playing guitar” produces visual chaos. Pick one clear concept.
Not specifying style: If you don’t specify a style, you get the model’s default, which may not match your vision. Always state whether you want photorealistic, illustration, painting, minimalist, etc.
Not iterating: First attempts rarely nail it. Treat image generation as a conversation, not a one-shot prompt. Refine based on what you see.
Realistic Use Cases {#realistic-use-cases}
Marketing and Creative Work
Concept mockups: “Show me a lifestyle product shot for a reusable water bottle, outdoor setting, hiker in background, natural lighting, clean minimalist aesthetic.”
Social media content: Generate variations for A/B testing. “Create an Instagram story background for a summer sale, tropical theme, bright colors, space for text overlay.”
Ad creative: Quick drafts to test concepts before investing in photography. “A fitness app promotional image, diverse group of people exercising outdoors, energetic and motivational style.”
Brand exploration: “Show me ten different logo concepts for a sustainable coffee brand, minimalist style, earth tones.” Use AI to explore directions before working with a designer.
Presentations and Documents
Slide visuals: “Generate a simple illustration of supply chain logistics, flat design style, blue and gray color scheme.” Drop directly into slides.
Diagrams and concepts: “A stylized illustration of cloud computing, isometric view, tech aesthetic, space for text labels.”
Contextual imagery: “A professional workspace scene, diverse team collaborating, modern office, bright and clean” for internal communications or HR materials.
Social Media
Post backgrounds: Textured backgrounds, gradients, simple scenes that leave room for captions.
Profile pictures: Concept art or stylized portraits for personal branding (note: be cautious with photorealistic faces of real people).
Themed content: Holiday posts, seasonal content, event announcements - quick visuals without custom design work.
Ideation and Concept Work
Mood boards: Generate images in a specific style to explore visual direction.
Character or product concepts: “Show me concept art for a futuristic sneaker, minimalist white design, side view.”
Scene visualization: Writers, filmmakers, game designers can visualize scenes, settings, or characters before committing to production.
Photo Editing and Enhancement
Most image tools can also modify existing images:
Generative fill: Add elements, remove backgrounds, extend images beyond their borders.
Style transfer: Apply a specific aesthetic to an existing photo.
Variations: Generate alternative versions of an image you like.
Copyright and Usage Considerations {#copyright-usage}
This is an evolving area with genuine uncertainty. Here’s the honest state of things as of early 2026:
Can You Copyright AI-Generated Images?
In the United States: The U.S. Copyright Office has taken the position that purely AI-generated images (without meaningful human creative input) cannot be copyrighted. If you type a prompt and the AI generates the image, you cannot claim copyright on that image.
However: If you use AI as one tool in a larger creative process - generating elements that you then significantly edit, composite, or transform - your final work may be copyrightable as a human-created work that incorporates AI elements. The boundary is fuzzy and case-by-case.
Internationally: Laws vary. Some countries are more restrictive, others more permissive. This is actively changing.
Commercial Use Rights
The tools’ terms: DALL-E, Midjourney, Adobe Firefly, and others generally grant commercial usage rights to images you generate on paid tiers. You can use them in marketing, client work, products, etc. Check each tool’s specific terms - free tiers sometimes restrict commercial use.
The training data question: There are ongoing legal disputes about whether training AI models on copyrighted images without permission constitutes infringement. This doesn’t directly affect your right to use generated images in most cases, but it’s worth being aware of as a live controversy.
Adobe Firefly’s position: Adobe explicitly trains Firefly on licensed work, Adobe Stock, and public domain content, and markets it as “commercially safe.” This doesn’t guarantee protection from future legal challenges, but Adobe is positioning Firefly as the lower-risk option for businesses.
Practical Guidance
For internal use: Drafts, concepts, internal presentations - copyright concerns are minimal.
For customer-facing work: Treat AI images as a starting point. Edit, composite, or transform them enough that your creative contribution is clear. This both improves quality and strengthens your copyright position.
For client work: Be transparent that AI was used. Many clients are fine with AI-assisted work if they know about it upfront and can consent.
For stock or resale: Be cautious. Using AI-generated images in stock portfolios or products you resell is legally murkier. Understand the platform’s policies and current law in your jurisdiction.
Deepfakes and Likeness
Don’t generate images of real people without their consent, especially for commercial or misleading purposes. This is ethically wrong and in some jurisdictions explicitly illegal. Most tools have policies against generating likenesses of public figures or real people, and these policies are enforced.
When in Doubt
If a use case is important and legally sensitive - a major campaign, a product launch, anything with significant financial or legal exposure - consult an actual lawyer. This section is practical guidance, not legal advice, and the law in this area is actively evolving.
Where to Start {#where-to-start}
If you’re new to AI image generation:
Start where you already are: If you use ChatGPT, try DALL-E first. If you’re in Adobe Creative Cloud, try Firefly. If you use Canva, try Magic Media. The friction of learning a new tool is real.
For pure visual quality: Midjourney produces the most consistently beautiful images, and the community gallery is endlessly inspiring. The Discord interface takes getting used to, but it’s worth it.
For maximum control and lowest long-term cost: Stable Diffusion, if you’re willing to invest in learning it.
For business and commercial use: Adobe Firefly or DALL-E are positioned as more commercially safe. Read the terms and make your own judgment.
For quick social media or presentation visuals: Canva AI is the fastest path from “I need an image” to “I have an image in my document.”
Most importantly: treat AI image generation as a tool in your workflow, not the entire workflow. Generate concepts, iterate fast, then refine with human judgment and editing. That’s where the real value is.