// Cross-vendor image comparison

GPT Image 2.6 SunburstvsNano Banana Pro

By GPTProtoUpdated November 5, 2026

GPT Image 2.6 Sunburst (OpenAI) and Nano Banana Pro (Google). GPT Image 2.6 Sunburst is OpenAI's image model for detailed work and consistent edits. Nano Banana Pro is Google's higher per-image tier. The cards keep the token rates and the per-image rates apart.

Read each card in its own unit. Sunburst shows text input and image output per 1M tokens. Nano Banana Pro shows the 1K and 4K image rates. Price a Sunburst call from the response usage, and price Nano Banana Pro from the size you request.

Try GPT Image 2.6 Sunburst on GPTProto Try Nano Banana Pro on GPTProto

GPT Image 2.6 Sunburst↗OpenAI · gpt-image-2.6-sunburst

Best forOpenAI's image model for detailed compositions and consistent edits.

GPTProto catalog rate, list price struck through

Text input~~$5.00~~$4.75/M−5%

Image output~~$30.00~~$28.50/M−5%

View model page

Nano Banana Pro↗Google · gemini-3-pro-image-preview

Best forGoogle's higher per-image tier, catalog id gemini-3-pro-image-preview.

GPTProto catalog rate, list price struck through

1K image~~$0.134~~$0.0804/img−40%

4K image~~$0.24~~$0.144/img−40%

View model page

// Side by side

GPT Image 2.6 Sunburst vs Nano Banana ProCatalog rates.

Each price is the text-to-image scene from the GPTProto catalog at request time. A token row and a per-image row stay on their own lines.

Spec

GPT Image 2.6 Sunburst

Nano Banana Pro

Provider

OpenAI

Google

Model ID

gpt-image-2.6-sunburst

gemini-3-pro-image-preview

Billing

Per token

Per image

In the catalog since

November 5, 2026

November 20, 2025

Availability

Text input / 1M

$4.75~~$5.00~~ official list

—

Image input / 1M

$7.60~~$8.00~~ official list

—

Image output / 1M

$28.50~~$30.00~~ official list

—

1K image

—

$0.0804~~$0.134~~ official list

2K image

—

$0.0804~~$0.134~~ official list

4K image

—

$0.144~~$0.24~~ official list

Catalog multiplier

0.95

0.6

Routes

Text to imageImage edit

API usage

# Submit
curl --request POST "https://gptproto.com/api/v3/openai/gpt-image-2.6-sunburst/text-to-image" \
    --header "Authorization: Bearer $GPTPROTO_API_KEY" \
    --header "Content-Type: application/json" \
    --data '{
        "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
        "n": null,
        "quality": "auto",
        "size": "auto",
        "enable_sync_mode": false,
        "response_format": "url"
    }'

# Result
curl --request GET "https://gptproto.com/api/v3/predictions/$result_id/result" \
    --header "Authorization: Bearer $GPTPROTO_API_KEY"

# Submit
curl --request POST "https://gptproto.com/api/v3/google/gemini-3-pro-image-preview/text-to-image" \
    --header "Authorization: Bearer $GPTPROTO_API_KEY" \
    --header "Content-Type: application/json" \
    --data '{
        "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
        "size": "1K",
        "aspect_ratio": "1:1",
        "output_format": "png",
        "enable_sync_mode": false,
        "enable_base64_output": false
    }'

# Result
curl --request GET "https://gptproto.com/api/v3/predictions/$result_id/result" \
    --header "Authorization: Bearer $GPTPROTO_API_KEY"

List price is the platform rate divided by the catalog price multiplier. The page does not turn a token rate into a cost per image.

List rate beside the GPTProto rate. Each row scales to its own list price.

OfficialGPTProto

GPT Image 2.6 SunburstOpenAI

Text input / 1M$5.00

Text input / 1M−5%$4.75

Image input / 1M$8.00

Image input / 1M−5%$7.60

Image output / 1M$30.00

Image output / 1M−5%$28.50

Nano Banana ProGoogle

1K image$0.134

1K image−40%$0.0804

2K image$0.134

2K image−40%$0.0804

4K image$0.24

4K image−40%$0.144

// Price

Two catalog rates.Two units.

GPT Image 2.6 Sunburst is billed per token. Nano Banana Pro is billed per image. The table is the catalog. The struck-through figure is the list price, and the bold figure is the GPTProto rate.

OpenAI's image guide says equal token rates can still produce a different cost per image, because quality and size change how many tokens a render uses. See Image generation. This catalog does not publish that token count, so the page leaves a per-image dollar amount for the token-billed model off the table. Price that call from the usage field on the response, then compare the total with the size row on the per-image model.

On this catalog, GPT Image 2.6 Flare lists the same text-input, image-input, and image-output rates. Read that pair on GPT Image 2.6 Flare vs Nano Banana 2.1.

Google's two per-image models are on Nano Banana 2.1 vs Nano Banana Pro. The image-count calculator stays off this page because the two models here do not share a unit.

// Top-up

One balance.
Either model.

Top up once, then open the model you are calling. The rate on this page is the catalog rate for that model's unit.

$15

Straight credit · no bonus

Get started. Great for testing the endpoint and trying new models.

Which jobeach model is for.

OpenAI describes Flare for fast iteration and Sunburst for detailed compositions. Google's two per-image models have their own page.

Spec

GPT Image 2.6 Sunburst

Nano Banana Pro

Catalog role

Detailed edits

Higher per-image tier

Price it from

Response token usage

1K, 2K, or 4K row

// Choose

Start from the joband the unit.

Pick the model whose unit you can price for the brief in front of you.

GPT Image 2.6 Sunburstgpt-image-2.6-sunburst

Detailed edits

You want the detailed Images 2.6 model OpenAI describes for composition and edits.
You can price the call from the token usage on the response.
You need the catalog's text, image-input, and image-output rates side by side.

Open GPT Image 2.6 Sunburst

Nano Banana Progemini-3-pro-image-preview

Higher per-image tier

You want the higher Google per-image tier for a complex brief.
The brief is a 1K, 2K, or 4K image with a price you can read first.
You are comparing that flat price with Sunburst's token rates.

Open Nano Banana Pro

When both belong in the test

Run the same brief on both model pages when you need a token-billed render and a size-priced render. Keep each invoice on its own unit.

// Models

Same catalog.Different jobs.

Choose Sunburst when the brief needs the detailed Images 2.6 model and you can settle the token total after the response. Choose Nano Banana Pro when you want Google's higher per-image tier at a size you can price first.

OpenAI's Images 2.6 notes describe Flare for interactive generation and editing, and Sunburst for detailed compositions and edit consistency. Those notes are the vendor's description. This page does not add a latency or quality score of its own.

The rates above are the text-to-image scene. Check GPT Image 2.6 Sunburst and Nano Banana Pro before an edit call.

// How to read this

Use the rowthat matches the call.

A token rate and a per-image rate answer different questions. The token rate prices 1M tokens. The image rate prices one generated image at a named size. The page keeps those purchases on separate rows.

For the token-billed model, multiply the usage on the response by the matching row: text input, image input, or image output. For the per-image model, use the 1K, 2K, or 4K row for the size you send.

The bars under the table compare each row with its own list price. A full-width bar is the list rate. The shorter bar is the GPTProto rate for that same row.

// Next

Open the modelyou plan to call.

Start with GPT Image 2.6 Sunburst or Nano Banana Pro. The other Images 2.6 pair is GPT Image 2.6 Flare vs Nano Banana 2.1.

Open GPT Image 2.6 Sunburst Open Nano Banana Pro

// FAQ

Pricing questionsfor this pair.

Answers use the catalog rows above.

01Why are the prices in different units?+

GPT Image 2.6 Sunburst and Nano Banana Pro are sold on different catalog meters. One side is USD per 1M tokens. The other side is USD per image at 1K, 2K, and 4K. The table keeps those meters on separate rows.

02Which model is cheaper per image?+

The catalog does not publish how many tokens one GPT Image render uses, and that count changes with size and quality. Price the token-billed call from the usage field on the response. Price the Google call from the size row. Then compare those two totals for the brief you actually ran.

03Do Flare and Sunburst share a token rate?+

On this catalog request, Flare and Sunburst list the same text-input, image-input, and image-output rates. The difference on the two pages is the Google model beside them, and the job OpenAI describes for each Images 2.6 model.

04Does the card's discount apply to every row?+

Catalog multiplier is 0.95 for GPT Image 2.6 Sunburst and 0.6 for Nano Banana Pro. The card percent is the gap between the list price and the GPTProto rate. This table is the text-to-image scene, so check the model page before an edit call.

// Social proof

See how others use GPTProto.

Creators and developers share the models and workflows they built with.

Blogstra

Reddit · r/Bloggers

#Routing

For a team already juggling DeepSeek, Kimi, Qwen, or other providers, a shared routing layer can be reasonable if it removes duplicated work and the fallback behavior is tested. GPTProto is one implementation of this approach.

X (Twitter) · @ChillaiKalan__

#Cost

I've been testing GPTProto recently, and it's honestly made my creative workflow much simpler. Instead of paying for multiple subscriptions, I can access several leading AI models from one place.

Sanskriti Naruka

X (Twitter) · @snskritinaruka

#Video

I turned this single prompt into a cinematic fantasy video using GPTProto. "Continuous 15-second cinematic shot, 4K resolution, hyper-realistic dark fantasy photorealism…"

Caden Flux

X (Twitter) · @Caden_Flux

#Video

I challenged myself to create a cinematic AI cooking short in just 15 seconds. I used GPTProto to bring the entire workflow together, from image generation to video, all in one place.

Zara

X (Twitter) · @ZaraIrahh

#Creative

Made with Seedance 2.0 + GPT Image 2 on GPTProto. A Pixar-style commercial with the perfect glow.

Many-Operation2625

Reddit · r/LLMDevs

#Integration

What worked for me was pointing the cloud connections at GPTProto so the frontend only sees one endpoint and I just change the model name to swap. I am not rebuilding a connection from scratch every time.

// From the blog

AI Model Guides.Practical API Tutorials.

Compare models, learn API setup, and explore image and video workflows for real projects.

View all posts →

// Get started

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