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To use Nano Banana 2.1 programmatically, obtain a Gemini API key, send an authenticated request to Google’s interactions endpoint with the model ID gemini-nano-banana-2.1, then base64-decode the returned image data. Google’s documented REST workflow uses the x-goog-api-key header and exposes a simple image at interaction.output_image.data.
This guide covers Nano Banana 2.1 API setup, authentication, requests, image editing inputs, output controls, SDK integration, limits, token estimates, and the errors most likely to stop an implementation.
What Nano Banana 2.1 is and which endpoint to use
Nano Banana is Google’s name for Gemini’s native image-generation capabilities, as described in the Gemini API image-generation documentation. The API model identifier for this release is gemini-nano-banana-2.1; do not substitute a display name or an older model ID.
Google Cloud lists Nano Banana 2.1 as generally available, with a release date of October 6, 2026. The Google AI model page was updated October 6, 2026, and the Cloud model reference was updated October 12, 2026. Availability, quotas, supported regions, and account access can change, so confirm the model appears in the Google environment attached to your project before deploying.
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For the documented REST interface, send a POST request to:
https://generativelanguage.googleapis.com/v1beta/interactionsThe request contains the model name and an input. A text-only prompt can be a simple string. Image editing requests add image bytes, a MIME type, and written instructions. The API can also return conversational edits and responses that interleave text and images.
Choose an integration path before writing code
| Path | Best fit | What you configure | Important distinction |
|---|---|---|---|
| Gemini API REST | Any language or service that can make HTTPS requests | Gemini API key, HTTP headers, JSON body, and response parsing | Google’s example uses /v1beta/interactions and x-goog-api-key. |
| Google GenAI SDK | Applications that prefer a language SDK over hand-written HTTP | SDK client, configured API key, model ID, input, and interaction call | Official examples create a client before calling interactions.create. |
| Google Cloud Agent Platform | Teams already operating through Google Cloud projects and platform services | A Google Cloud project with billing and the Agent Platform API enabled for the documented example application | Project and platform configuration is separate from the basic API-key REST example. |
The REST and SDK approaches invoke the same model but differ in credential configuration, dependency management, error handling, and how image parts are represented. Pick one for the first working request; adding both before you have a successful response makes troubleshooting harder.
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- Create or obtain a Gemini API key in the Google environment used by your application.
- Store the key in a server-side secret manager or an environment variable rather than committing it to source control.
- Expose an application endpoint to your own clients if you need browser or mobile access; do not place the unrestricted key in browser JavaScript.
- Make the key available to the process that performs the request. The examples below use
GEMINI_API_KEY.
The official request example authenticates with the x-goog-api-key header. A missing, misspelled, expired, or unauthorized key normally fails before the model can process the prompt, so test authentication with the smallest text request first.
Send the first REST request
Set the key in your shell, then send JSON to the interactions endpoint. This example asks for one image and keeps the payload intentionally small:
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export GEMINI_API_KEY='your-key-value'
curl https://generativelanguage.googleapis.com/v1beta/interactions
-H "x-goog-api-key: $GEMINI_API_KEY"
-H 'Content-Type: application/json'
-d '{
"model": "gemini-nano-banana-2.1",
"input": "Create a square editorial illustration of a red fox reading beside a lantern."
}'The endpoint, header names, content type, model ID, and input fields are the parts that must match the documented interface. The prompt itself can be replaced with your application’s text. Keep the key out of the JSON body; Google’s example supplies it in the request header.
Save the complete response while you are integrating. A saved response makes it possible to distinguish an authentication error, a malformed request, and a response-parsing bug without sending repeated generations.
Construct inputs for text, editing, and reference images
Text-to-image input
A plain string is sufficient for a basic generation. Describe the subject, composition, lighting, style, aspect preference, and any constraints in ordinary language. You can also use a typed text block when your SDK or request format represents input parts explicitly; the two forms express the same textual instruction.
Image editing input
For an edit, provide the source image as base64-encoded bytes together with its MIME type, then include the requested change as text. State which elements must remain unchanged and which may change. Conversational editing is supported, so a later interaction can refine an earlier result when your application preserves the necessary conversation context.
Reference-image workflows
Nano Banana 2.1 supports up to 14 reference images in one prompt. Google’s model overview describes consistency workflows involving up to four characters and ten objects. Treat those as upper bounds, not a promise that every prompt will use every reference successfully: image relevance, prompt clarity, and the model’s response still determine the result.
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Supported image MIME types listed by Google Cloud are PNG, JPEG, WebP, HEIC, and HEIF. The maximum size depends on how the image enters the service:
| Input route | Maximum size per file | Formats listed by Google Cloud |
|---|---|---|
| Inline data or direct console upload | 7 MB | PNG, JPEG, WebP, HEIC, HEIF |
| Google Cloud Storage input | 30 MB | PNG, JPEG, WebP, HEIC, HEIF |
Resize or recompress an oversized source before encoding it. If you use inline data, account for the base64 expansion when estimating request size even though the stated limit applies to the image file itself.
Use an SDK when your application already has a Google client layer
Google’s official SDK examples configure a GenAI client with the API key and call interactions.create. The exact import and configuration syntax depends on the language SDK version, so follow the SDK’s current package documentation for installation and authentication. The essential call shape is:
client = configured_genai_client(api_key=GEMINI_API_KEY)
interaction = client.interactions.create(
model='gemini-nano-banana-2.1',
input='Create a square editorial illustration of a red fox reading beside a lantern.'
)The snippet shows the sequence rather than a language-specific package declaration: configure the client, call the interactions API, pass the canonical model ID, and retain the returned interaction object. Use the SDK’s typed content-part classes when sending an image plus text, and keep the key in server-side configuration.
SDKs can simplify authentication plumbing and response objects, while REST gives you direct control over headers and serialized JSON. Do not mix a REST response parser with an SDK object model without checking the SDK’s return type; a convenience property may not contain every part of a complex response.
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Decode the returned image bytes
For a simple image response, Google’s examples read interaction.output_image.data. The value is base64-encoded image data, not a ready-to-display file. Decode it before writing the bytes to disk, object storage, or an HTTP response.
If you saved the JSON response from the REST request as response.json, standard Python can extract and decode the field:
import base64
import json
from pathlib import Path
payload = json.loads(Path('response.json').read_text())
encoded = payload['interaction']['output_image']['data']
image_bytes = base64.b64decode(encoded)
Path('output-image.bin').write_bytes(image_bytes)Use an extension and MIME type appropriate to the format your application receives or declares. The important operation is base64 decoding; writing the encoded text directly creates a corrupt image.
When output_image is not enough
Google notes that convenience properties do not capture all content in complex interleaved text-and-image outputs. If the interaction contains explanatory text, multiple images, or other steps, iterate through the interaction’s steps or content parts using the SDK or response schema, identify each image block, decode its data, and preserve the order. Do not assume that the first convenience image represents the complete response.
Control resolution, aspect ratio, and output size
The image-generation guide documents a response_format option for image output, including aspect ratio and image size. Use the parameter names and nesting shown in the current endpoint-specific guide rather than copying a configuration object from a different Gemini endpoint. The documented resolution tiers are 1K, 2K, and 4K; the model overview identifies 1K as the default.
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| Output tier | Google-published output-image estimate | Use when |
|---|---|---|
| 1K | 1,120 tokens | You need the default, lower-cost output for drafts, previews, or rapid iteration. |
| 2K | 1,680 tokens | You need more detail for a normal production asset without the largest published estimate. |
| 4K | 3,780 tokens | You need the highest documented tier and accept the greater output-token estimate. |
These are Google’s published specifications or estimates, not independent benchmark measurements. Image size affects token consumption and may affect latency or account limits. Choose the smallest tier that meets the actual delivery requirement, then increase it for a final render.
Aspect ratio is a separate decision from resolution. Match it to the destination—such as a square card, a landscape banner, or a portrait asset—so you do not rely on a later crop that removes important content. Put both settings in the documented response-format object when your endpoint version supports them.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Know the context and image-token limits
Google Cloud lists a 131,072-token context window and a maximum output of 32,768 tokens for Nano Banana 2.1. Each input image consumes 1,120 tokens according to the same reference. Those figures are model specifications and should be treated as published limits or estimates rather than measurements of your particular prompt.
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- Long instructions, conversation history, and many reference images all consume context.
- Fourteen reference images at the published per-image estimate would consume substantial context before text and output are counted.
- Reducing unnecessary history or sending only the most relevant references leaves room for instructions and generated content.
- Output-image estimates rise from 1,120 tokens at 1K to 3,780 at 4K, so resolution is part of capacity planning.
Do not send unsupported generic generation parameters
Google Cloud explicitly lists seed, topK, logprobs, temperature, and topP as unsupported for this model. Setting any of them returns an API error. This is a common failure when an application reuses a generic Gemini generation configuration for an image request.
Start with only the documented model, input, and image-response settings. Add an option only after confirming that Nano Banana 2.1 supports it in the endpoint you are calling. Remove unsupported fields from shared configuration objects instead of sending them with null or default values.
Gemini API and Cloud platform considerations
The Cloud model reference lists global availability, batch inference, pay-as-you-go consumption, image generation, search grounding, thinking, and Batch API support. These capability labels do not guarantee that every account, region, quota, or interface exposes every feature immediately. Verify access and operational terms in the console and the current documentation before designing a production dependency around one of them.
If you deploy the example application through Google Cloud’s Agent Platform, the Cloud documentation states that the project needs billing enabled and the Agent Platform API enabled. That requirement is distinct from the simple Gemini API key and REST call shown earlier. Use the account and project model that matches your organization’s logging, billing, IAM, and deployment requirements.
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Authentication or permission error
- Confirm the environment variable is populated in the same process that runs
curlor the SDK. - Check that the header is exactly
x-goog-api-keyand that the key has access to the selected API. - Do not put the key in the JSON body or expose it in browser source.
Model-not-found or availability error
- Use the exact identifier
gemini-nano-banana-2.1. - Check the model page and Cloud reference for current availability, project access, and quota.
- Confirm that you are calling the interactions endpoint expected by your chosen client or SDK version.
Invalid-argument error
- Validate JSON syntax and the
Content-Type: application/jsonheader. - Remove unsupported fields such as
temperature,topP, orseed. - Check that image data is valid base64, its MIME type matches the bytes, and each file is within the limit for its upload route.
The request succeeds but the file will not open
- Inspect the response before writing it and confirm that
interaction.output_image.datais present. - Base64-decode the value exactly once.
- If the response is interleaved, iterate its steps and decode the image part instead of assuming the convenience property contains everything.
The output is cropped or too small
- Set the documented aspect ratio to match the destination.
- Choose 2K or 4K only when the delivery requirement justifies the higher published token estimate.
- Describe subject placement and protected regions explicitly so important details are not placed at the crop edge.
Production checklist
- Verify that
gemini-nano-banana-2.1is available to the account and project you will operate. - Keep the API key in server-side secret storage and rotate it according to your organization’s policy.
- Start with a text-only request and save the raw response for diagnostics.
- Add the documented
response_formatsettings for aspect ratio and resolution only after the basic call works. - For edits, validate MIME type, base64 encoding, reference count, and per-file size before sending.
- Budget context for each input image at Google’s published 1,120-token estimate.
- Budget output according to the selected tier: 1,120 tokens at 1K, 1,680 at 2K, or 3,780 at 4K.
- Decode simple results from
interaction.output_image.data; iterate interaction steps for interleaved responses. - Log request IDs and error responses without logging API keys or sensitive source images.
- Recheck the model page and Cloud reference before launch because identifiers, limits, availability, and examples are version-sensitive.
The canonical documentation for the model is Google AI’s Nano Banana 2.1 model page. Use the image-generation guide for current input and output formatting, and the Google Cloud model reference for limits, supported formats, and platform-specific requirements.
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