Google Imagen 4 & Nano Banana Pricing 2026: Midjourney API Killers?

Google Imagen 4 & Nano Banana Pricing 2026: Midjourney API Killers?

(Updated: ) 📖 4 min read

Google’s image generation ecosystem in 2026 is more powerful — and more confusing — than ever. Between the Nano Banana models (Gemini’s native image generation), Imagen 4 (the standalone image model), and legacy options, choosing the right model for your budget requires a clear pricing map.

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What is “Nano Banana”?

If you’ve seen the banana emoji next to some Gemini models in Google AI Studio, you’ve found the Nano Banana family. These are Gemini’s native image generation models — they can understand text, reason about it, AND generate images natively in one model.

There are two main variants:

Model Powered By Model ID Best For
Nano Banana 2 Gemini 3.1 Flash Image gemini-3.1-flash-image-preview Fast, affordable native image generation
Nano Banana Pro Gemini 3 Pro Image gemini-3-pro-image-preview High-fidelity, professional-grade output

Nano Banana 2 (Gemini 3.1 Flash Image) Pricing

Image output is priced at $60.00 per million output tokens. Since different resolutions use different token counts, the per-image price varies:

Resolution Pixels Tokens Used Price per Image Batch API (50% Off)
0.5K 512×512 747 $0.045 $0.022
1K 1024×1024 1,120 $0.067 $0.034
2K 2048×2048 1,680 $0.101 $0.050
4K 4096×4096 2,520 $0.151 $0.076

Cost comparison: At $0.067 per 1K image, Nano Banana 2 is 3x cheaper than Nano Banana Pro. Use it for social media content, thumbnail mockups, and rapid prototyping.

Free Tier in AI Studio

Nano Banana 2 is available in the free tier of Google AI Studio with standard rate limits — perfect for testing before committing to paid usage.


Nano Banana Pro (Gemini 3 Pro Image) Pricing

Image output is priced at $120.00 per million output tokens — 2× the cost of Nano Banana 2, but with significantly higher quality and adherence to complex text prompts.

Resolution Pixels Tokens Used Price per Image Batch API (50% Off)
1K 1024×1024 1,120 $0.134 $0.067
2K 2048×2048 1,120 $0.134 $0.067
4K 4096×4096 2,000 $0.240 $0.120

When to use Pro: Marketing campaigns, hero images, product photography, or any case where visual quality directly impacts conversions.


Imagen 4 Pricing — The Standalone Powerhouse

Imagen 4 is Google’s dedicated image generation model — separate from Gemini. It’s optimized for the highest quality output, excellent text rendering, and photorealism.

Model Tier Model ID Price per Image Best For
Imagen 4 Fast imagen-4.0-fast-generate-001 $0.02 High-volume generation, drafts, social mockups
Imagen 4 Standard imagen-4.0-generate-001 $0.04 Balanced quality and cost
Imagen 4 Ultra imagen-4.0-ultra-generate-001 $0.06 Hero images, commercial-grade photography

Additional Imagen 4 Costs

  • Image Editing (Inpainting): ~$0.02 per edit
  • Upscaling: ~$0.06 per image

Best deal alert: Imagen 4 Fast at $0.02/image is the cheapest high-quality image generation API on the market. It is 3x cheaper than DALL-E 3 and Midjourney API options.


Nano Banana vs. Imagen 4: Comparison Matrix

Feature Nano Banana 2 Nano Banana Pro Imagen 4 Fast Imagen 4 Ultra
Price (1K image) $0.067 $0.134 $0.020 $0.060
Text rendering Good Better Best Best
Multimodal I/O Native Native Image only Image only
Editing/Inpainting Native Native Dedicated API Dedicated API
Free tier Yes Limited Paid only Paid only

Real-World Cost Comparison

Scenario: Generate 10,000 marketing images at 1K resolution:

Model Total Cost Time / Speed
Imagen 4 Fast $200.00 Ultra-Fast
Imagen 4 Ultra $600.00 Fast
Nano Banana 2 $670.00 Fast
Nano Banana Pro $1,340.00 Moderate
Nano Banana 2 (Batch) $335.00 24-hour turnaround

Key Takeaways

  1. Imagen 4 Fast ($0.02/image) is the cheapest option for pure image generation.
  2. Nano Banana 2 is the best choice when you need text understanding + image output in one model.
  3. Nano Banana Pro delivers the highest quality but at 2× the cost.
  4. Batch API saves 50% on Nano Banana models — use it for non-urgent workloads.

Prices are current as of May 2026. Always verify with Google’s official documentation before production deployment.

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Professor XAI
Professor XAI ML Engineer passionate about advancing AI technologies and building intelligent systems.
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