What AI Can Generate Images?

Too Many AI Image Tools, Too Little Guidance

Every AI image generator on the market claims to be "the best" — and here's the uncomfortable truth: most of them aren't lying. Hands-on testing from Zapier's reviewers puts it bluntly: "We've reached the stage where the top 50 or so models are all excellent, so other features and usability matter more than they used to." Raw image quality, the thing every marketing page leads with, is no longer what separates winners from losers.

The field has consolidated around a recognizable set of leaders — ChatGPT's GPT Image 2, Midjourney, Google's Nano Banana, Adobe Firefly, Stable Diffusion/FLUX, Ideogram, Reve, and Recraft — each genuinely excellent at producing images. Midjourney alone generates revenue "significantly above $200M" with roughly 40–45 employees and no venture capital, according to verified reporting. Adobe Firefly's ARR is approaching $300M. These are mature, proven products, not experiments.

So if quality is table stakes, what should you actually compare? The criteria that matter today fall into six buckets:

• Ease of use — ChatGPT wins here; testers call it "ridiculously easy to use," while Midjourney demands more work in exchange for more control.
• Text rendering — GPT Image 2 hits ~99% accuracy with the standard Latin alphabet; Ideogram leads among dedicated tools; Midjourney still can't reliably render text.
• Customization — Midjourney's style references, character references, and aspect-ratio control remain best-in-class.
• Editing — Google's Nano Banana excels at modifying existing images, though it adds a visible watermark.
• Workflow integration and legal safety — Firefly embeds in Creative Cloud and offers enterprise indemnification; Midjourney does not indemnify users and is being sued by Disney and Universal.

That last point deserves emphasis for business readers. As one practitioner notes, client indemnification is becoming the standard — Adobe, Getty, Shutterstock, Bria, and Google all offer it, while Midjourney notably does not. The U.S. Copyright Office also holds that purely AI-generated images can't be copyrighted. A beautiful image you can't legally deploy is worthless.

The same "everything looks good on the surface" problem exists across the AI tooling ecosystem, which is why independent verification has become its own discipline. SkillzBench is building exactly that for agent skills — security-scanning, license-checking, and benchmarking skills with and without them — because a demo that looks great tells you nothing about safety or real-world performance. The same skepticism serves you well when choosing an image generator.

The sections that follow apply these criteria model by model, so you can match a tool to your actual workflow rather than to its homepage claims.

The Leading AI Image Generators and Their Strengths

Ask ten AI image generators to draw "a coffee shop sign that says OPEN in clean sans-serif," and you'll get ten very different answers — which is exactly why picking the right tool matters more than ever. The good news, according to hands-on testing by Zapier, is that "the top 50 or so models are all excellent," so usability and fit now matter more than raw image quality.

Here's how the leaders stack up:

• ChatGPT (GPT Image 2) — Best overall and easiest to use, with roughly 99% text accuracy using the standard Latin alphabet, conversational editing, inpainting, and the ability to upload an image as a base. Testers called it "ridiculously easy to use."
• Midjourney — The artistic powerhouse: photorealism, textures, and best-in-class customization through style and character references, outpainting, aspect-ratio control, and 5-second image animation. The trade-off? As Zapier put it, "with Midjourney, you have to do more work, but you have a lot more control." It also can't reliably render text and offers no copyright indemnification.
• Google Nano Banana — Excels at editing existing images across the Gemini image model family, though prompt adherence is weaker and outputs carry a visible watermark.
• Adobe Firefly — Built for professional creative-suite workflows, trained on Adobe's own stock portfolio, and one of the few generators offering enterprise indemnification — a growing standard for business use.
• FLUX / Stable Diffusion — Open-source and deeply customizable, runnable locally or via APIs for teams that need full control.
• Ideogram, Reve, and Recraft — Specialists: Ideogram for accurate text rendering, Reve for prompt adherence with a solid free plan, and Recraft for graphic design.

For business readers comparing options, here's the pricing landscape:

The scale behind these tools is real: Google's Nano Banana models have generated over 50 billion cumulative images, Adobe Firefly is approaching $300M in annual recurring revenue, and Midjourney's revenue sits "significantly above $200M" — all vendor-disclosed figures worth trusting over the stale statistics that circulate widely.

One practical note for teams building AI workflows: once you've chosen a generator, testing shows the real productivity gains come from chaining these tools into repeatable processes. Agent skills can automate the rest of that workflow — and SkillzBench's free directory and MCP connector (currently in development, with a live waitlist) are being built to help you find, verify, and benchmark the skills that actually work.

The Legal Risk Factor Most Comparisons Skip

Most AI image tool comparisons rank aesthetics and ignore the question that actually keeps legal teams awake: who pays if the output gets you sued? That single question separates the enterprise-ready vendors from the rest of the field.

Indemnification is the new dividing line. Adobe, Getty, Shutterstock, Bria, and Google all offer copyright indemnification to customers, while Midjourney notably does not — and it's often at the center of image copyright disputes, including an active lawsuit from Disney and Universal alleging copyright infringement (practitioner analysis; hands-on testing). As analyst Geoff Livingston puts it, client indemnification "is becoming the standard for all image and video generators" — Midjourney simply hasn't subscribed to that standard.

There's a second exposure most businesses miss: your prompts and outputs may not be private. Midjourney publishes user images to a public gallery by default, and the only way to keep generations hidden is the $60/month Pro plan with Stealth Mode (per Zapier's testing). If your team is mocking up unreleased products or campaign concepts, that default matters.

And a third: the U.S. Copyright Office has held since February 2023, and reaffirmed since, that purely AI-generated images cannot be copyrighted. For brands, that means AI-only assets carry no ownership protection — a real issue for packaging, logos, and campaign imagery.

The commercial stakes explain why vendors are racing to prove trust at scale:

• Adobe Firefly's ARR is approaching $300M, growing roughly 50% quarter-over-quarter, with 22B+ cumulative assets generated (verified vendor figures)
• Google's Nano Banana models have produced 50B+ cumulative images, up from 5B in mid-October 2025
• Midjourney reports revenue significantly above $200M — profitable, self-funded, with no indemnification on offer

One caution when evaluating any vendor's traction claims: several widely-cited market statistics are stale or unverifiable. The famous "15.5 billion AI images" figure from Everypixel dates to August 2023, and some "2026 updates" citing it appear to be fabricated attributions, per one verification-based analysis. Only Adobe and Google publish dated generation-volume figures — treat everything else skeptically.

The practical takeaway: match the tool to the risk profile. Firefly for anything customer-facing, Midjourney for internal concepting where legal exposure is acceptable. And once you've picked your generator, agent skills can automate the surrounding workflow — resizing, publishing, asset tagging. SkillzBench (skillzbench.com) is building a free directory and MCP connector for exactly that, with security scanning and benchmarking of every skill before it reaches your agents.

Choosing Your Tool and Automating the Rest of the Workflow

The right image generator depends far less on image quality than it did a few years ago. As Zapier's hands-on testers put it, "the top 50 or so models are all excellent" — so the real question is which tool fits the job, the workflow, and the legal risk you can carry.

A practical decision framework looks like this:

• Marketing copy and social images: ChatGPT (GPT Image 2) is the easiest to use and hits roughly 99% text accuracy with the standard Latin alphabet, making it ideal when words need to appear correctly on the image. Ideogram is also strong for accurate text rendering.
• Brand campaigns and artistic work: Midjourney leads on photorealism, textures, and customization — style and character references, outpainting, aspect ratio control — though it still can't reliably render text. Note that it publishes user images publicly unless you pay for the $60/month Pro plan's Stealth Mode.
• Enterprise and commercial work: Adobe Firefly is trained on Adobe's own stock portfolio and offers enterprise indemnification, which matters as client indemnification becomes the industry standard — one that Midjourney notably does not offer.
• Developer pipelines: FLUX from Black Forest Labs runs via APIs, NightCafe, Civitai, or local servers, giving teams open-source control and customizability that closed tools can't match.

Budget matters too. Entry pricing ranges from Google AI Plus at $4.99/month and Firefly at $9.99 for 2,000 credits to Midjourney from $10/month, ChatGPT Plus at $20/month, and Ideogram from $20/month. For teams evaluating vendors, analysts at Grand View Research expect competitive advantage to come from multimodal capabilities, governance, copyright protection, and integration — not raw output quality.

Once the images are generated, though, the work is rarely done: resizing, captioning, uploading to CMSs, A/B testing variants, logging assets. This is where agent skills can automate the rest of the workflow. Skills are instruction packages (SKILL.md files) that plug into Claude Code, Codex, Cursor, Gemini CLI, and chat-app agents — but quality varies wildly, and published research found roughly 26% of skills carry at least one vulnerability.

That's the problem SkillzBench is building for. Its free, independent directory continuously crawls and dedupes skills from GitHub, pins every version to a commit SHA, runs security scans and license checks, and benchmarks each skill in a sandbox — with and without the skill — to publish a Lift score in percentage points. A trust score from 0 to 100 combines security, quality, license, maintenance, and community signals, and money never touches scores.

SkillzBench is currently in pre-launch, but you can join the waitlist now and be first in line when the free directory and MCP connector go live. Your image pipeline shouldn't stop at the prompt — let agents handle the rest, with skills you can actually trust.