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Nano Banana Across Ten Aspect Ratios

Nano Banana Across Ten Aspect Ratios

Nano Banana brings Google’s Gemini image generation and editing models to developers through Atlas Cloud. Create visuals from text or revise existing images, then deliver them in PNG or JPEG across square, portrait, landscape, and ultrawide layouts. Optional Base64 output supports API workflows. Atlas Cloud adds an OpenAI-compatible interface, Day-0 access, and transparent pay-as-you-go pricing. Start building today.

Nano Banana is developed by Google. Atlas Cloud (operated by Atlas Cloud AI LLC) provides access to it and does not own it. All trademarks belong to their respective owners.

Explore the Leading Nano Banana

Atlas Cloud provides you with the latest industry-leading creative models.

Choose the Right Nano Banana Image Endpoint

Compare Nano Banana text-to-image and editing modalities, endpoint profiles, and standard per-call pricing.

ModalityDescription
Nano Banana Text-to-Image Developer APITurn text prompts into images through an endpoint profiled for open, advanced large-scale image generation. Its standard price is $0.038 per image, making it suitable for concept exploration, web graphics, and repeatable content workflows.
Nano Banana Edit Developer APIProvide an existing image and editing instructions to produce a revised visual with the Developer endpoint. Built for open, advanced large-scale image generation workflows, it supports iterative asset updates at a standard price of $0.038 per edit.
Nano Banana Text-to-Image APICreate new visual output directly from a text prompt using Google's image generation model. At the verified standard price of $0.038 per image, this endpoint fits social assets, marketing visuals, and rapid creative production.
Nano Banana Edit APIWhen an existing visual needs revision, send the image to this endpoint with instructions for the desired edit. The $0.038 standard per-edit price supports product asset updates, creative variations, and ongoing content refinement.

Inside the Nano Banana Image Workflow

Nano Banana combines prompt-based image generation, natural-language editing, multi-image inputs, flexible formats, developer controls, and transparent Atlas Cloud access in one production-ready workflow.

Nano Banana Generation and Editing

Nano Banana Generation and Editing

Nano Banana turns text prompts into images and applies natural-language changes to existing visuals through separate generation and editing model slugs. Editing requires only a prompt and source images, with no mask field in the request schema. Request background, object, or compositional changes through the same image API workflow. This suits product refreshes, social assets, and rapid creative iteration.

Up to Ten Source Images

Up to Ten Source Images

Submit between one and ten source images to the Nano Banana editing endpoint, then describe how they should inform the result. The schema accepts image URLs alongside a positive prompt and a selected aspect ratio. Developers can organize reference-driven transformations without adding masks or layer files. It is a practical fit for product combinations, wardrobe concepts, and scene variations built from several visual inputs.

Ten Ratios, Two Output Formats

Ten Ratios, Two Output Formats

Choose from ten output ratios spanning 1:1, portrait, landscape, and 21:9, then request PNG or JPEG delivery. The same ratio set is available for text-to-image generation and image editing. Compose each asset for its final placement instead of relying on a single fixed canvas. Campaign teams can prepare square posts, vertical stories, standard banners, and cinematic panoramas through one workflow.

Developer Controls for Nano Banana

Developer Controls for Nano Banana

For structured experimentation, the Developer endpoints expose seed, top_p, and temperature controls. The default seed is -1, top_p is 0.95, and temperature is 1.0, while the documentation notes that a seed may improve repeatability without guaranteeing identical results. Tune sampling behavior without changing your integration. These controls help teams organize prompt tests and compare creative directions more systematically.

Flexible API Delivery

Flexible API Delivery

Both standard workflows can return PNG or JPEG files, wait for uploaded results with synchronous mode, or encode outputs as Base64 for API-only delivery. Editing also exposes low, medium, and high media-resolution settings for controlling how input media is processed. Match transport and input detail to the needs of your application. This flexibility supports server pipelines, previews, and automated asset processing.

One Key, Pay-as-You-Go Access

One Key, Pay-as-You-Go Access

Atlas Cloud serves Nano Banana generation and editing under one OpenAI-compatible key with transparent pay-as-you-go billing. Standard pricing is $0.038 per generated or edited image, using the verified origin price rather than a temporary discount. Switch between the text-to-image and edit model slugs while keeping the same authentication and request endpoint. This keeps integration overhead predictable for prototypes, production services, and recurring content workloads.

Nano Banana in a One Prompt Image Showdown

Compare how Nano Banana and two Atlas Cloud alternatives interpret identical prompts across typography driven design and cinematic street photography.

Prompt

A decisive-moment fashion photograph seen through the storefront window of a vintage clothing shop moments before closing on a rainy night: a stylish young shop assistant snaps open a scarlet fringed cape, the fabric sweeping dramatically past the lens with slight authentic motion blur, accidentally startling a tabby cat hidden atop the clothing rail—the cat recoils mid-leap with arched body, splayed paws, alert ears, and wide eyes. Layer complex yet spatially coherent reflections across the glass: a passing streetcar and umbrella-carrying pedestrians outside, while every subject inside remains clearly separated and anatomically consistent. Handwritten directly on the window in crisp, perfectly legible lettering: “SECOND CHANCE, FIRST IMPRESSION”. Wide horizontal frame-within-a-frame composition using the storefront architecture, repeating rows of metal hangers creating graphic rhythm and leading lines, and a tall mirror on the right extending the shop into convincing depth; softly defocused raindrops cling to the near glass. Strong direct on-camera flash in the style of a bold 1990s fashion magazine editorial, balanced against warm directional tungsten light inside and cool cyan-blue rainy street light outside, controlled blue-orange contrast with the scarlet cape as the visual accent. Tactile, photorealistic surfaces: cracked old leather jackets, worn velvet with flattened nap, scratched chrome hangers, wet glass, damp pavement, individual cat hairs, and sharply resolved flying fringe. Candid, energetic, slightly imperfect analog film character, fine grain, restrained highlights, natural youthful skin texture, realistic reflections and perspective, no greasy over-rendering, no HDR look, no plastic skin, no muddy colors, no ubiquitous glow, no cheap cinematic epic effect. 35mm film photography, 28mm wide-angle lens, close storefront viewpoint, direct flash, subtle film halation, editorial realism, full-frame environmental storytelling, wide 16:9 aspect ratio, full-bleed.

Generated with Nano Banana 2 Text-to-Image on Atlas Cloud

Generated with Nano Banana 2 Text-to-Image on Atlas Cloud

Generated with Seedream v5.0 Pro Text-to-Image on Atlas Cloud

Generated with Seedream v5.0 Pro Text-to-Image on Atlas Cloud

Generated with Nano Banana Text-to-image on Atlas Cloud

Generated with Nano Banana Text-to-image on Atlas Cloud

Prompt

An abandoned indoor diving hall transformed into a floating library, captured at the decisive instant when a precarious stack of books tumbles from a high diving platform: a young librarian balances on a narrow wooden punt gliding between shallow-water bookshelves, reaching upward in startled determination to catch the falling volumes, their expression surprised with a touch of absurd comedy, while dozens of loose ivory pages burst outward like startled white birds, each sheet preserving consistent paper weight, scale, folds, and believable gravity-driven motion. Intricate stop-motion animation aesthetic with handcrafted paper-diorama construction, visibly tactile paper fibers, softened water stains, chipped pool paint, cracked vintage ceramic tiles, damp book cloth, warped page edges, tiny model seams, subtle glue marks, and delicate imperfections—never glossy or plastic. Tall clerestory windows cast crisp diagonal shafts of cool indoor daylight through suspended dust, creating clean directional highlights and long-edged shadows; the shallow turquoise water produces a lucid reflection that overlays the librarian, boat, shelves, diving platforms, and grand arches into a poetic double-layered image. Use faded swimming-lane lines as strong leading lines through the complex space, with softly out-of-focus book spines in the near foreground forming a natural frame-within-a-frame; cinematic wide-angle depth, clear spatial hierarchy, controlled detail, and slight motion blur only on the fastest pages. Strict limited palette of swimming-pool cyan, paper ivory, and lifebuoy vermilion, with no muddy colors and no additional dominant hues. Sophisticated handcrafted miniature cinematography, whimsical yet restrained, tactile and photographic, subtle film grain, no oily over-rendering, no HDR look, no plastic skin, no ubiquitous glow, no cheap epic atmosphere, no dark underwater or space-ruin imagery, wide horizontal 16:9 aspect ratio, full-bleed composition.

Generated with Nano Banana 2 Text-to-Image on Atlas Cloud

Generated with Nano Banana 2 Text-to-Image on Atlas Cloud

Generated with Seedream v5.0 Pro Text-to-Image on Atlas Cloud

Generated with Seedream v5.0 Pro Text-to-Image on Atlas Cloud

Generated with Nano Banana Text-to-image on Atlas Cloud

Generated with Nano Banana Text-to-image on Atlas Cloud

Nano Banana Workflows Built for Visual Continuity

Across storytelling, commerce, design, and creator tools, Nano Banana turns text and reference images into consistent visual series, targeted edits, style variations, and campaign assets through Atlas Cloud.

Character Continuity with Nano Banana

Nano Banana preserves a character’s likeness while changing outfits, poses, lighting, or surroundings across successive images. Story teams can build coherent storyboards, comics, and campaign narratives without recreating the cast for every frame.

Product Scenes with the Nano Banana API

Blend product references with new settings through the Nano Banana API, then direct composition and context in natural language. Commerce teams can create lifestyle scenes, catalog variations, and seasonal campaign concepts from existing assets.

Targeted Image Revisions

Describe an object replacement, background change, or localized adjustment, and the model edits the supplied image without manual masks. Designers produce polished variants and fast revisions while preserving the broader scene.

Identity Preserving Style Transfers

Transform a portrait, pet, or subject into a different visual style while retaining recognizable likeness across edits. Creator apps can offer personalized avatars, themed portraits, and shareable transformations from one reference.

Campaign Assets for Every Format

Choose from ten supported aspect ratios, spanning square, portrait, landscape, and ultrawide formats for generated images. Marketing teams can prepare social posts, banners, thumbnails, and web graphics for varied placements.

Rapid Visual Prototyping with Nano Banana

Designed for speed and efficient large volume generation, Nano Banana turns text prompts into images through a production API. Product teams can prototype visual features, test creative directions, and automate recurring asset production.

Nano Banana Across Leading Image API Alternatives

Compare Nano Banana with Qwen and Grok endpoints by workflow, input format, resolution, reference capacity, and standard Atlas Cloud pricing.

ModelProviderWorkflowMax ResolutionReference ImagesStandard Price
Nano Banana Text-to-imageGoogleText to image1024px-$0.038 per image
Nano Banana EditGoogleImage editing1024pxUp to 3 recommended$0.038 per image
Qwen Image 3.0 Pro Text-to-ImageQwenText to image2048 × 2048-$0.04 per image
Qwen Image 3.0 Pro EditQwenImage editing2048 × 2048Up to 3$0.04 per image
Grok Imagine Image 2.0 Text-to-ImagexAIText to image2K-$0.04 per image
Grok Imagine Image 2.0 EditxAIImage editing2KUp to 5$0.04 per image

How to Use Nano Banana on Atlas Cloud

Get started in minutes — follow these simple steps to integrate and deploy models through Atlas Cloud's platform.

Create an Atlas Cloud Account

Sign up at atlascloud.ai and complete verification. New users receive free credits to explore the platform and test models.

Why Use Nano Banana on Atlas Cloud

Combining the advanced Nano Banana models with Atlas Cloud's GPU-accelerated platform provides unmatched performance, scalability, and developer experience.

Why use 1
Why use 2
Why use 3

Performance & flexibility

Low Latency:
GPU-optimized inference for real-time reasoning.

Unified API:
Run Nano Banana, GPT, Gemini, and DeepSeek with one integration.

Transparent Pricing:
Predictable per-token billing with serverless options.

Enterprise & Scale

Developer Experience:
SDKs, analytics, fine-tuning tools, and templates.

Reliability:
99.99% uptime, RBAC, and compliance-ready logging.

Security & Compliance:
SOC 2 Type II, HIPAA alignment, data sovereignty in US.

Nano Banana API Questions Developers Actually Ask

Nano Banana is Google's name for Gemini 2.5 Flash Image, a model that generates images from text and edits existing images with natural language instructions. Atlas Cloud provides separate text-to-image and editing endpoints through one API account.

Create new visuals from prompts or modify uploaded images by describing changes to subjects, backgrounds, composition, and style. The model is designed for high-volume generation, conversational editing, and creative workflows where speed and efficiency matter.

Start by sending an authenticated POST request to `/api/v1/model/generateImage` with your Atlas Cloud API key, model identifier, and prompt. Use `google/nano-banana/text-to-image` for generation or `google/nano-banana/edit` with an `images` array for editing. The response includes a prediction ID, status, and output data.

Generation requests support a prompt, aspect ratio, output format, media resolution setting, seed, temperature, and top-p sampling. You can also request synchronous or Base64 output. Editing uses similar controls and additionally requires an array of input image URLs.

Choose from 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, and 21:9. Atlas Cloud can return the default format, PNG, or JPEG, while Google's documentation lists 1024 by 1024 pixels for square output and corresponding dimensions for the other ratios.

Atlas Cloud accepts between one and ten image URLs in an editing request. Google notes that the underlying Gemini 2.5 Flash Image model works best with up to three input images, so accepting more files does not guarantee equal fidelity across every reference.

The standard list price is $0.038 per call for each of the four listed Atlas Cloud endpoints, including the text-to-image, edit, and Developer variants. Billing is pay-as-you-go, with no subscription required for these per-call rates.

A fixed seed may improve repeatability, but Atlas Cloud does not guarantee deterministic output. Leave the seed at its default value of `-1` when you want a random seed, and store prompts, parameters, and source images when tracking production results.

The original model prioritizes fast, efficient generation and produces images at approximately 1024-pixel resolution. Nano Banana Pro is intended for complex professional asset creation, with stronger creative control, greater world knowledge, and output up to 4K.

Google applies built-in safety policies to image generation, so restricted prompts may be blocked even when the request is technically valid. Check the returned status, outputs, and `has_nsfw_contents` field before retrying. If filtering is involved, revise the prompt to remove ambiguous or restricted content instead of repeatedly submitting the same request.

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