AI Image Generator API: Build Image Generation Into Your App

You're building an app that needs image generation. Maybe it's a design tool. Maybe it's a marketing platform that creates social posts. Maybe it's a game that generates assets on the fly. Whatever it is, you need an API that's reliable, affordable, and doesn't take 30 seconds per image.

Here's the current state of AI image generation APIs, with real pricing and honest tradeoffs.

The Major APIs

OpenAI (DALL-E 3 / GPT-Image)

The most well-known option. DALL-E 3 through the OpenAI API costs $0.04 per standard image (1024×1024) and $0.08 for HD. GPT-Image-1 is newer and higher quality but runs $0.02-0.19 depending on size and quality.

Pros: Excellent prompt following, built-in safety filters, reliable uptime, strong text rendering in images.

Cons: Limited model selection (you get what OpenAI offers), slower than some alternatives (3-8 seconds typical), safety filters sometimes block legitimate creative prompts. No NSFW content at all, which matters for some use cases like medical illustration or artistic nudity.

Latency: 3-8 seconds for DALL-E 3. GPT-Image varies.

Stability AI

The API behind Stable Diffusion. They offer SD3.5, SDXL, and various specialized models. Pricing runs about $0.01-0.05 per image depending on model and resolution.

Pros: Cheapest option for bulk generation, multiple model choices, more permissive content policies, good community and documentation.

Cons: Quality is a step below DALL-E 3 and Flux for photorealism, API stability has been inconsistent (they've had rough patches), company's financial situation has raised concerns about long-term reliability.

Latency: 2-6 seconds depending on model.

FAL.ai

A newer player that's gained serious developer traction. They host multiple models — Flux, Stable Diffusion, and others — behind a unified API. Pricing varies by model: Flux Pro runs about $0.05/image, Flux Dev around $0.025.

Pros: Multi-model access through one API, fast inference (they optimize heavily for speed), good developer experience, queue-based with webhooks for async workflows.

Cons: Smaller company (reliability concerns for enterprise), pricing can fluctuate, less built-in content moderation (you handle it).

Latency: 1-4 seconds for Flux on their optimized infrastructure.

Replicate

A platform model — they host community models that you call via API. Pricing is per-second of compute, which makes cost estimation tricky. Roughly $0.02-0.10 per image depending on model and hardware.

Pros: Massive model selection (anything the community has uploaded), easy to experiment, cold starts aside the developer experience is solid.

Cons: Cold start latency (first request to a model can take 10-30 seconds while it loads), unpredictable costs, quality varies wildly by model.

Latency: 10-30 seconds cold start, 2-8 seconds warm.

Myjourney API

Myjourney offers API access to multiple models including Flux Pro and Ultra. Pricing starts at $0.03 per standard image. The API follows a simple REST pattern.

Pros: Pay-per-image pricing (no minimums, no subscriptions), multiple model access, built-in quality modes for upscaling, straightforward authentication.

Cons: Newer API (smaller community, fewer integration examples), no on-premise option, throughput limits on free tier.

Latency: 2-5 seconds typical.

Pricing Comparison (Per Standard Image)

At scale, these differences matter. If you're generating 100,000 images/month, the difference between $0.01 and $0.05 per image is $4,000/month.

What to Optimize For

If you need speed: FAL.ai or Stability AI

Sub-2-second generation is possible with Flux Schnell on FAL or SDXL Turbo on Stability. These are good for real-time applications where users are waiting.

If you need quality: OpenAI or FAL (Flux Pro)

DALL-E 3 and Flux Pro produce the most consistently impressive images. For customer-facing applications where image quality represents your brand, don't cheap out here.

If you need volume: Stability AI

At $0.01/image with SDXL, bulk generation is cheapest through Stability. Quality is "good enough" for thumbnails, backgrounds, and variations.

If you want simplicity: Myjourney or OpenAI

Both offer clean APIs without the complexity of managing model versions, GPU selection, or queue infrastructure. Myjourney's pricing is flat per image — no compute-time surprises.

Integration Pattern

Most image generation APIs follow the same basic pattern:

// Generic pattern — adjust for your provider
const response = await fetch('https://api.example.com/generate', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    prompt: 'a mountain lake at sunrise, photorealistic',
    model: 'flux-pro',
    width: 1024,
    height: 1024
  })
});
 
const result = await response.json();
const imageUrl = result.image_url;

The differences are in the details: authentication methods, response formats, webhook support, and error handling. But the core flow is always: send prompt → get image URL.

Async vs Sync

For any production application, use async generation with webhooks. Here's why:

Sync requests tie up a connection for 2-8 seconds. Under load, that means hundreds of open connections. Your server runs out of connection pools. Users see timeouts.

Async flow:

1. Submit generation request → get a job ID immediately
2. Server calls your webhook when the image is ready
3. Your app fetches the result

FAL and Replicate have good webhook support. OpenAI is sync-only (which is honestly annoying at scale). Myjourney supports both patterns.

Error Handling You'll Actually Need

Every image API will occasionally:

• Return a content policy violation (even for benign prompts)
• Time out under heavy load
• Return a degraded image (wrong aspect ratio, truncated)
• Rate limit you without warning

Build retry logic with exponential backoff. Log every failed generation so you can adjust prompts that consistently trigger filters. And always have a fallback — either a different model or a graceful "generation failed, please try again" UX.

The Build vs Buy Decision

You could self-host Stable Diffusion on your own GPUs. A single A100 runs about $1.50-3.00/hour on cloud providers and can generate roughly 500-1,000 images per hour depending on model and resolution.

That's $0.003-0.006 per image. Way cheaper than any API.

But you're now managing GPU infrastructure, model updates, scaling, monitoring, and the inevitable 3 AM incident where the inference server crashes. For most startups and mid-size teams, the API premium is worth not dealing with that.

Self-host when you're generating 500K+ images/month and have DevOps capacity. Use an API for everything else.

Getting Started

Pick one API. Build a proof of concept. Generate 100 images and evaluate quality, speed, and cost. Then decide if you need to optimize.

If you want to start quickly without a subscription or minimum commitment, Myjourney's API lets you pay per image with no monthly fees. Generate 10 images, see if the quality and latency work for your use case, and scale from there.

The best API is the one that fits your constraints. Not the one with the most impressive benchmark. Check out the gallery to see real output from our API.