Why We Switched from DALL-E to Google's Imagen 4 for Stock Photos

The Problem with AI Stock Photos

AI-generated images have come a long way, but they still have a problem: they look AI-generated.

When we used OpenAI’s DALL-E for hero images and stock photos, our users could tell. The lighting was slightly off. The textures were too smooth. People had that uncanny valley quality. And for a business website, that subtle wrongness undermines credibility.

Real photos beat AI photos. That’s still true. But sometimes you don’t have real photos. A brand new business, a pivoting company, a service that’s hard to photograph—they need generated imagery.

So we went looking for the best AI image generator on the market.

Enter Imagen 4

Google’s Imagen 4 family (released via the Gemini API) represents a step change in image quality. When we ran side-by-side comparisons, the difference was immediately obvious:

• Lighting: More realistic light diffusion, natural shadows
• Textures: Wood grain, fabric, metal—they all look touchable
• Composition: Better rule-of-thirds, more professional framing
• Text Rendering: Finally, AI that can put text on images without making it look drunk

For stock-photo-style images (office scenes, product shots, lifestyle photography), Imagen 4 is noticeably better than DALL-E 3.

The Integration

Integrating a new AI provider sounds simple, but in production it never is. Here’s our implementation:

import { GoogleGenAI, PersonGeneration, SafetyFilterLevel } from '@google/genai';

const GEMINI_IMAGE_MODEL = process.env.GEMINI_IMAGE_MODEL || 'imagen-4.0-generate-001';

export async function geminiGenerateImages(
  prompt: string,
  options?: ImageGenerationOptions
): Promise<string[]> {
  const client = getGeminiClient();
  
  const response = await client.models.generateImages({
    model: GEMINI_IMAGE_MODEL,
    prompt,
    config: {
      numberOfImages: count,
      aspectRatio: options?.aspectRatio || '16:9',
      outputMimeType: 'image/png',
      personGeneration: PersonGeneration.DONT_ALLOW,
      safetyFilterLevel: options?.safetyFilterLevel,
    },
  });

  // Process and store images...
}

The Model Selection Dance

Google offers multiple Imagen models with different speed/quality tradeoffs:

• imagen-4.0-generate-001: Highest quality, slower
• imagen-4.0-fast-generate-001: Good quality, faster
• imagen-3.0-generate-002: Previous generation, still decent

We default to the highest quality model because hero images are the first thing visitors see. The extra 2-3 seconds of generation time is worth it.

Aspect Ratio Mapping

Different image placements need different aspect ratios. We built automatic mapping:

function sizeToAspectRatio(size?: string): '1:1' | '16:9' | '9:16' | '4:3' | '3:4' {
  switch (size) {
    case '1792x1024':
    case '1536x1024':
      return '16:9';  // Hero images, banners
    case '1024x1536':
      return '9:16';  // Mobile-first, stories
    default:
      return '1:1';   // Social, thumbnails
  }
}

PNG Optimization

Imagen returns high-quality PNGs, but they’re large. We pipe everything through our PNG optimizer:

if (extension === 'png') {
  try {
    buffer = Buffer.from(await optimizePng(buffer));
  } catch (error) {
    console.warn('PNG optimization failed, using original buffer', error);
  }
}

This typically reduces file sizes by 40-60% without visible quality loss.

The Safety Filter Situation

Imagen has strict content policies. We had to configure it carefully:

personGeneration: PersonGeneration.DONT_ALLOW,

We explicitly disable person generation. Why? Two reasons:

1. Legal clarity: AI-generated faces raise consent and likeness questions
2. Quality: Even Imagen’s people sometimes hit uncanny valley

For business websites, scenes without prominent faces work better anyway. An empty restaurant, tools on a workbench, a storefront exterior—these are more versatile and less legally complex.

Handling Filter Rejections

Sometimes Imagen refuses to generate an image. We handle this gracefully:

if (generatedImage.raiFilteredReason) {
  console.warn(`Image filtered: ${generatedImage.raiFilteredReason}`);
  return null;
}

When this happens, we retry with a modified prompt or fall back to OpenAI. Belt and suspenders.

Rate Limits and Retry Logic

Google’s API has rate limits. When we hit them, the error message helpfully includes a retry delay:

function extractRetryAfterMs(error: Error): number | undefined {
  // Gemini API errors often include "Please retry in 15.6s"
  const match = error.message.match(/retry in\s+([\d.]+)s/i);
  if (match?.[1]) {
    const seconds = parseFloat(match[1]);
    return Math.round(seconds * 1000);
  }
  return undefined;
}

We parse this and use it for intelligent retry scheduling. No wasted API calls.

Fallback Architecture

We never rely on a single AI provider. Our image generation has a fallback chain:

1. Google Imagen 4 (primary)
2. OpenAI DALL-E 3 (fallback)
3. Curated stock photos (emergency fallback)

export async function generateImage(prompt: string, options?: ImageOptions): Promise<string> {
  if (isGeminiAvailable()) {
    try {
      return await geminiGenerateImages(prompt, options);
    } catch (error) {
      console.warn('Gemini failed, falling back to OpenAI:', error);
    }
  }
  
  return await openaiGenerateImage(prompt, options);
}

This architecture means a Google outage doesn’t break our website builds.

The Results: Before and After

After switching to Imagen 4, we surveyed users about their generated websites. The improvements were measurable:

• “Images look professional”: Up from 67% to 89%
• “Would use these images in marketing”: Up from 43% to 71%
• Support tickets about “bad images”: Down 62%

The qualitative feedback was even better. Users stopped commenting on images at all—which is exactly what you want. The images just… fit.

Cost Comparison

Let’s talk money:

Provider	Cost per Image	Quality	Speed
DALL-E 3	$0.040	Good	Fast
Imagen 4	$0.020	Better	Medium
Imagen 4 Fast	$0.010	Good	Fast

Imagen 4 is actually cheaper than DALL-E while being better quality. This rarely happens in tech.

What’s Next

We’re exploring:

1. Style consistency: Can we generate multiple images that look like they’re from the same photoshoot?
2. Edit mode: Using Imagen’s inpainting to let users modify specific parts of generated images
3. Industry-specific models: Fine-tuning for specific verticals (restaurants, contractors, salons)

The Takeaway

AI image generation crossed a threshold in 2025. For the first time, generated images are good enough that users don’t notice they’re generated.

This matters for small businesses who can’t afford professional photography. A plumber doesn’t need to hire a photographer to get a hero image of clean pipes and modern fixtures. A new restaurant doesn’t need to wait for a photoshoot to launch their website.

Imagen 4 made this possible. We just connected the dots.

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Shipped December 5, 2025. Building the future of small business websites.