GPT Image 2 vs Nano Banana 2: Which to Choose?

Short answer: pick GPT Image 2 when you need tight control over quality and exact output sizes, and pick Nano Banana 2 when you need multi-image compositing, web-grounded visuals or extreme aspect ratios. Both are strong at rendering text inside images, both go up to 4K, and both are available through the same endpoint on APIMart, so you can test them side by side before you commit.

GPT Image 2 is OpenAI's image model, released in April 2026 as the successor to GPT Image 1.5. Nano Banana 2 is Google's name for Gemini 3.1 Flash Image, the fast Flash-tier member of the Nano Banana family. They solve the same problem from different directions: OpenAI exposes explicit quality tiers on a token meter, while Google prices by resolution and adds search grounding.

Key Takeaways

• GPT Image 2 offers low, medium and high quality tiers on its official route; at 1024x1024 OpenAI's list price runs from about $0.006 (low) to $0.211 (high) per image.
• Nano Banana 2 is billed per image by resolution; Google's list price is about $0.067 at 1K, $0.101 at 2K and $0.151 at 4K.
• On APIMart, the per-image routes cost $0.0085 to $0.021 for GPT Image 2 and $0.015 to $0.025 for Nano Banana 2, from 1K to 4K.
• Nano Banana 2 accepts up to 14 reference images and supports 1:8 and 8:1 formats; GPT Image 2 accepts up to 15 reference images and also takes custom pixel sizes.
• Nano Banana 2 can ground generations in Google Search results; GPT Image 2 has no web grounding and a December 2025 knowledge cutoff.
• Google watermarks every Nano Banana 2 output with SynthID; GPT Image 2 does not add a SynthID watermark.

GPT Image 2 vs Nano Banana 2 at a Glance

How Do GPT Image 2 and Nano Banana 2 Differ?

GPT Image 2: quality tiers and precise sizing

GPT Image 2 is built around a reasoning-driven generation process and gives you a direct quality dial. The official route exposes low, medium and high, and the price difference between them is large: at 1024x1024 the high tier costs roughly 35 times more than the low tier. That makes it practical to draft at low quality and render the final asset at high quality without changing models or endpoints.

It is also the more flexible model when an exact output size matters. Besides 15 preset ratios, it accepts pixel dimensions such as 1881x836, which helps when a layout, banner slot or print template has fixed measurements.

Nano Banana 2: grounding, references and speed

Nano Banana 2 sits on Gemini 3.1 Flash, so it is tuned for speed and predictable cost rather than a quality dial. Its strongest differentiator is grounding: with google_search enabled it can pull current text results into the generation, and google_image_search adds reference images found on the web. That is useful for visuals that need to match real products, landmarks or recent events.

Google also documents character consistency for up to five people per generation, which matters for storyboards and campaign series where the same faces must reappear.

Text rendering in both models

Text inside images is a headline feature for both. OpenAI highlights accurate spelling and spacing across Latin and East Asian scripts, and Google highlights per-character typography in multiple languages. In practice both are good choices for posters, UI mockups, packaging and infographics; run your own prompts in the languages you ship, because results vary by font style and text density.

Output Sizes, Aspect Ratios and Reference Images

Resolution and formats

Both models reach 4K. On APIMart, GPT Image 2 at 4K renders 16:9 at 3840x2160 and 1:1 at 2880x2880. Nano Banana 2 adds a 0.5K tier (about 512px) for cheap previews and thumbnails, and it supports very tall or wide formats such as 1:8 and 8:1 that GPT Image 2 does not offer.

Multi-image editing

Passing image_urls switches either model into image-to-image mode. Google recommends up to 10 object references plus 4 character references for Nano Banana 2, which is a helpful split when you composite products and people in one scene.

Pricing Compared

Prices below were read from the APIMart pricing API on October 9, 2026. Check the model pages for current rates before you budget.

Per-image prices on APIMart

The official Nano Banana 2 route is billed 20% below Google's list price ($0.067, $0.101 and $0.151). The official GPT Image 2 route follows OpenAI's token meter, also 20% below list:

Higher APIMart membership tiers increase the discount to 24% or 28%.

What 1,000 images cost

The pattern is simple: GPT Image 2's per-image route is the cheapest way to get volume, while its official high tier is the most expensive option in this comparison. Nano Banana 2 costs more than GPT Image 2 per image on the cheap routes, but its price does not change with a quality setting, which keeps budgets predictable.

How to Run Both Models on APIMart

Both models use the same endpoint, POST https://api.apimart.ai/v1/images/generations, so switching is a one-line change to model.

GPT Image 2 request

curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-image-2",
    "prompt": "A product poster for a ceramic coffee mug with the headline MORNING RITUAL",
    "n": 1,
    "size": "4:5",
    "resolution": "2k"
  }'

Nano Banana 2 request

curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "A product poster for a ceramic coffee mug with the headline MORNING RITUAL",
    "n": 1,
    "size": "4:5",
    "resolution": "2K"
  }'

Getting the result

Both calls are asynchronous and return a task_id with status submitted. Poll GET https://api.apimart.ai/v1/tasks/{task_id} until the status is completed, then read the image URL from result.images. Result URLs expire, so download images you want to keep.

Which One Should You Use?

Choose GPT Image 2 if

• You want to draft cheaply at low quality and finish at high quality on the same model.
• Your layout needs exact pixel dimensions instead of preset ratios.
• You generate large volumes and want the lowest per-image price.
• You need outputs without a SynthID watermark.

Choose Nano Banana 2 if

• Your images must match real-world products, places or recent events, using search grounding.
• You composite many references, such as products plus recurring characters.
• You need extreme formats like 1:8 banners or 8:1 strips, or 0.5K previews.
• You prefer a flat per-image price that does not depend on a quality setting.

Or use both

Many teams route by job: GPT Image 2 for text-heavy marketing assets and fixed-size placements, Nano Banana 2 for grounded or reference-heavy scenes. Because both share one endpoint and one API key on APIMart, A/B testing the same prompt costs only the images you generate. For more on OpenAI's model, see the GPT Image 2 deep dive.

FAQs

What is the main difference between GPT Image 2 and Nano Banana 2?

GPT Image 2 gives you explicit quality tiers and custom pixel sizes, billed on a token meter on its official route. Nano Banana 2 is priced per image by resolution and adds Google Search grounding, more extreme aspect ratios and a 0.5K preview tier.

Which model is cheaper?

On APIMart's per-image routes, GPT Image 2 is cheaper at every resolution: $0.0085 versus $0.015 at 1K and $0.021 versus $0.025 at 4K. On the official routes, GPT Image 2 is cheaper at low quality and much more expensive at high quality.

Which model is better at rendering text?

Both are strong. OpenAI emphasizes spelling and spacing across Latin and East Asian scripts, while Google emphasizes per-character typography in multiple languages. Test your own fonts and languages, because dense or stylized text still varies between runs.

How many reference images can I use?

GPT Image 2 accepts up to 15 reference images per request (20MB each, 256MB total). Nano Banana 2 accepts up to 14 (10MB each), with Google recommending up to 10 object references and 4 character references.

Can Nano Banana 2 use live web information?

Yes. Set google_search to true to ground the generation in search results, and add google_image_search to pull in reference images from the web. GPT Image 2 has no web grounding and relies on knowledge up to December 2025.

Are the outputs watermarked?

Google applies an invisible SynthID watermark to every Nano Banana 2 image. GPT Image 2 does not add a SynthID watermark. Both models allow commercial use under their providers' terms.

What to Watch Next

Both families move quickly: a Nano Banana 2.1 update focused on mask-based editing has already been reported, and GPT Image 2 itself replaced GPT Image 1.5 this year. Re-run your comparison prompts whenever either model updates, and re-check per-image prices on the model pages before you scale a workload.