Migrate from Imagen to a Gemini Image model ("Nano Banana")


All Imagen models are deprecated and will shut down on June 24, 2026. This deprecation and shutdown is applicable across Google and for both the Gemini Developer API and Vertex AI Gemini API.

Before this shutdown date, to avoid service disruption, you should migrate your apps from using Imagen models to using Gemini Image models (the "Nano Banana" models), as described in this guide.

If you have an urgent issue involving this deprecation and shutdown, reach out to Firebase Support.

Replacement Gemini Image models

Review the following table to choose a replacement Gemini Image model for your app.

Imagen model Gemini Image models ("Nano Banana")
imagen-4.0-fast-generate-001 gemini-2.5-flash-image (GA)
gemini-3.1-flash-image-preview (with thinking level MINIMAL)
imagen-4.0-generate-001 gemini-2.5-flash-image (GA)
gemini-3.1-flash-image-preview (with thinking level HIGH)
imagen-4.0-ultra-generate-001 gemini-2.5-flash-image (GA)
gemini-3-pro-image-preview
imagen-3.0-capability-001 gemini-2.5-flash-image (GA)
gemini-3.1-flash-image-preview

Migrate your app

This section shows before and after examples for migrating from an Imagen model to a Gemini Image model.

Generate an image from text

Click your Gemini API provider to view provider-specific content and code on this page.

To generate an image from text, migrate your app:

  • Use an appropriate replacement Gemini Image model (such as gemini-2.5-flash-image).

  • Create a GenerativeModel instance (instead of an ImagenModel instance).

  • Update the model configuration options to accommodate Gemini Image models.

    • As part of this configuration, set a response modality of IMAGE.
      Note that Gemini Image models can be configured to return both images and text.

  • (Vertex AI Gemini API only) Update the location where you access the model to a supported location for Gemini Image models. We recommend global.

Swift

Before


import FirebaseAILogic

// Initialize the Gemini Developer API backend service
let ai = FirebaseAI.firebaseAI(backend: .googleAI())

// Create an `ImagenModel` instance with a model that supports your use case
let model = ai.imagenModel(modelName: "IMAGEN_MODEL_NAME")

// Provide an image generation prompt
let prompt = "An astronaut riding a horse"

// To generate an image, call `generateImages` with the text prompt
let response = try await model.generateImages(prompt: prompt)

// Handle the generated image
guard let image = response.images.first else {
  fatalError("No image in the response.")
}
let uiImage = UIImage(data: image.data)

After


import FirebaseAILogic

// Initialize the Gemini Developer API backend service
let ai = FirebaseAI.firebaseAI(backend: .googleAI())

// Create a `GenerativeModel` instance with a Gemini model that supports image output
let model = ai.generativeModel(
  modelName: "GEMINI_IMAGE_MODEL_NAME",
  generationConfig: GenerationConfig(
    responseModalities: [.image],
    imageConfig: ImageConfig(aspectRatio: .landscape4x3)
  )
)

// Provide an image generation prompt
let prompt = "An astronaut riding a horse"

// To generate an image, call `generateContent` with the text prompt
let response = try await model.generateContent(prompt)

// Handle the case where no images were generated
guard let inlineDataPart = response.inlineDataParts.first else {
  fatalError("No image in the response.")
}

// Process the image
guard let uiImage = UIImage(data: inlineDataPart.data) else {
  fatalError("Failed to convert data to UIImage.")
}

Kotlin

Before


// Initialize the Gemini Developer API backend service
val ai = Firebase.ai(backend = GenerativeBackend.googleAI())

// Create an `ImagenModel` instance with an Imagen model that supports your use case
val model = ai.imagenModel("IMAGEN_MODEL_NAME")

// Provide an image generation prompt
val prompt = "An astronaut riding a horse"

// To generate an image, call `generateImages` with the text prompt
val imageResponse = model.generateImages(prompt)

// Handle the generated image
val image = imageResponse.images.first()

val bitmapImage = image.asBitmap()

After


// Initialize the Gemini Developer API backend service
val ai = Firebase.ai(backend = GenerativeBackend.googleAI())

// Create a `GenerativeModel` instance with a Gemini model that supports image output
val model = ai.generativeModel(
    modelName = "GEMINI_IMAGE_MODEL_NAME",
    generationConfig = generationConfig {
      responseModalities = listOf(ResponseModality.IMAGE),
      imageConfig = imageConfig {
        aspectRatio = AspectRatio.LANDSCAPE_4x3
      }
    }
)

// Provide an image generation prompt
val prompt = "An astronaut riding a horse"

// To generate an image, call `generateContent` with the text prompt
val imageResponse = model.generateContent(prompt)

if (imageResponse.finishReason == FinishReason.NO_IMAGE) {
  // Handle the case where no images were generated
} else {
  // Handle the generated image
  val bitmapImage = imageResponse.candidates.first().content.parts.filterIsInstance().firstOrNull()?.image
}

Java

Before


// Initialize the Gemini Developer API backend service
// Create an `ImagenModel` instance with an Imagen model that supports your use case
ImagenModel imagenModel = FirebaseAI.getInstance(GenerativeBackend.googleAI())
        .imagenModel(
                /* modelName */ "IMAGEN_MODEL_NAME");

ImagenModelFutures model = ImagenModelFutures.from(imagenModel);

// Provide an image generation prompt
String prompt = "An astronaut riding a horse";

// To generate an image, call `generateImages` with the text prompt
Futures.addCallback(model.generateImages(prompt), new FutureCallback<ImagenGenerationResponse>() {
    @Override
    public void onSuccess(ImagenGenerationResponse result) {
        if (result.getImages().isEmpty()) {
            Log.d("TAG", "No images generated");
        }
        Bitmap bitmap = result.getImages().get(0).asBitmap();
        // Use the bitmap to display the image in your UI
    }

    @Override
    public void onFailure(Throwable t) {
        // ...
    }
}, Executors.newSingleThreadExecutor());

After


// Initialize the Gemini Developer API backend service
// Create a `GenerativeModel` instance with a Gemini model that supports image output
GenerativeModel ai = FirebaseAI.getInstance(GenerativeBackend.googleAI()).generativeModel(
    "GEMINI_IMAGE_MODEL_NAME",
    new GenerationConfig.Builder()
        .setResponseModalities(Arrays.asList(ResponseModality.IMAGE))
        .setImageConfig(new ImageConfig(AspectRatio.LANDSCAPE_4x3, null))
        .build()
);

GenerativeModelFutures model = GenerativeModelFutures.from(ai);

// Provide a text prompt instructing the model to generate an image
Content prompt = new Content.Builder()
        .addText("An astronaut riding a horse")
        .build();

// To generate an image, call `generateContent` with the text input
Executor executor = Executors.newSingleThreadExecutor();
ListenableFuture response = model.generateContent(prompt);
Futures.addCallback(response, new FutureCallback() {
    @Override
    public void onSuccess(GenerateContentResponse result) {
        if (result.finishReason == FinishReason.NO_IMAGE) {
            // handle the case where no images were generated
            return;
        }
        // iterate over all the parts in the first candidate in the result object
        for (Part part : result.getCandidates().get(0).getContent().getParts()) {
            if (part instanceof ImagePart) {
                ImagePart imagePart = (ImagePart) part;
                // The returned image as a bitmap
                Bitmap generatedImageAsBitmap = imagePart.getImage();
                break;
            }
        }
    }

    @Override
    public void onFailure(Throwable t) {
        t.printStackTrace();
    }
}, executor);

Web

Before


import { initializeApp } from "firebase/app";
import { getAI, getGenerativeModel, getImagenModel, GoogleAIBackend } from "firebase/ai";

// TODO(developer) Replace the following with your app's Firebase configuration
const firebaseConfig = {
  // ...
};

// Initialize FirebaseApp
const firebaseApp = initializeApp(firebaseConfig);

// Initialize the Gemini Developer API backend service
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

// Create an `ImagenModel` instance with an Imagen model that supports your use case
const model = getImagenModel(ai, { model: "IMAGEN_MODEL_NAME" });

// Provide an image generation prompt
const prompt = "An astronaut riding a horse.";

// To generate an image, call `generateImages` with the text prompt
const response = await model.generateImages(prompt)

// If fewer images were generated than were requested,
// then `filteredReason` will describe the reason they were filtered out
if (response.filteredReason) {
  console.log(response.filteredReason);
}

if (response.images.length == 0) {
  throw new Error("No images in the response.")
}

const image = response.images[0];

After


import { initializeApp } from "firebase/app";
import {
  getAI,
  getGenerativeModel,
  GoogleAIBackend,
  ResponseModality,
  ImageConfigAspectRatio,
  FinishReason
} from "firebase/ai";

// TODO(developer) Replace the following with your app's Firebase configuration
const firebaseConfig = {
  // ...
};

// Initialize FirebaseApp
const firebaseApp = initializeApp(firebaseConfig);

// Initialize the Gemini Developer API backend service
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });

// Create a `GenerativeModel` instance with a model that supports your use case
const model = getGenerativeModel(ai, {
  model: "GEMINI_IMAGE_MODEL_NAME",
  generationConfig: {
    responseModalities: [ResponseModality.IMAGE],
    imageConfig: {
      aspectRatio: ImageConfigAspectRatio.LANDSCAPE_4x3
    }
  },
});

// Provide an image generation prompt
const prompt = "An astronaut riding a horse.";

// To generate an image, call `generateContent` with the text prompt
const result = await model.generateContent(prompt);

// Handle the generated image
try {
  const response = result.response;
  if (response.candidates?.[0].finishReason == FinishReason.NO_IMAGE) {
    // Handle the case where no images were generated
  }
  const inlineDataParts = response.inlineDataParts();
  if (inlineDataParts?.[0]) {
    const image = inlineDataParts[0].inlineData;
    // Use this mimeType and base64 data to display the image using
    // your preferred tooling
    console.log(image.mimeType, image.data);
  }
} catch (err) {
  console.error('Prompt or candidate was blocked:', err);
}

Dart

Before


import 'package:firebase_ai/firebase_ai.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';

// Initialize FirebaseApp
await Firebase.initializeApp(
  options: DefaultFirebaseOptions.currentPlatform,
);

// Initialize the Gemini Developer API backend service
final ai = FirebaseAI.googleAI();

// Create an `ImagenModel` instance with an Imagen model that supports your use case
final model = ai.imagenModel(model: 'IMAGEN_MODEL_NAME');

// Provide an image generation prompt
const prompt = 'An astronaut riding a horse.';

// To generate an image, call `generateImages` with the text prompt
final response = await model.generateImages(prompt);

if (response.images.isNotEmpty) {
  final image = response.images[0];
  // Process the image
} else {
  // Handle the case where no images were generated
  print('Error: No images were generated.');
}

After


import 'package:firebase_ai/firebase_ai.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';

// Initialize FirebaseApp
await Firebase.initializeApp(
  options: DefaultFirebaseOptions.currentPlatform,
);

// Initialize the Gemini Developer API backend service
final ai = FirebaseAI.googleAI();

// Create a `GenerativeModel` instance with a Gemini model that supports image output
final model = ai.generativeModel(
  model: 'GEMINI_IMAGE_MODEL_NAME',
  generationConfig: GenerationConfig(
    responseModalities: [ResponseModalities.image],
    imageConfig: ImageConfig(aspectRatio: ImageAspectRatio.landscape4x3)
  ),
);

// Provide a text prompt instructing the model to generate an image
final prompt = [Content.text('An astronaut riding a horse.')];

// To generate an image, call `generateContent` with the text prompt
final response = await model.generateContent(prompt);
if (response.inlineDataParts.isNotEmpty) {
  final imageBytes = response.inlineDataParts.first.bytes;
  // Process the image
} else {
  // Handle the case where no images were generated
  print('Error: No images were generated.');
}

Unity

Before


using Firebase.AI;

// Initialize the Gemini Developer API backend service
var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());

// Create an `ImagenModel` instance with a model that supports your use case
var model = ai.GetImagenModel(modelName: "IMAGEN_MODEL_NAME");

// Provide an image generation prompt
var prompt = "An astronaut riding a horse";

// To generate an image, call `generateImages` with the text prompt
var response = await model.GenerateImagesAsync(prompt: prompt);

// Handle the generated image
if (response.Images.Count == 0) {
  throw new Exception("No image in the response.");
}
var image = response.Images[0].AsTexture2D();

After


using Firebase;
using Firebase.AI;

// Initialize the Gemini Developer API backend service
var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());

// Create a `GenerativeModel` instance with a Gemini model that supports image output
var model = ai.GetGenerativeModel(
  modelName: "GEMINI_IMAGE_MODEL_NAME",
  generationConfig: new GenerationConfig(
    responseModalities: new[] { ResponseModality.Image },
    imageConfig: new ImageConfig(aspectRatio: ImageConfig.AspectRatio.Landscape4x3)
  )
);

// Provide an image generation prompt
var prompt = "An astronaut riding a horse";

// To generate an image, call `GenerateContentAsync` with the text prompt
var response = await model.GenerateContentAsync(prompt);

if (response.Candidates.First().FinishReason == FinishReason.NoImage) {
  // Handle the case where no images were generated
}

// Handle the generated image
var imageParts = response.Candidates.First().Content.Parts
                         .OfType<ModelContent.InlineDataPart>()
                         .Where(part => part.MimeType == "image/png");

foreach (var imagePart in imageParts) {
  // Load the Image into a Unity Texture2D object
  UnityEngine.Texture2D texture2D = new(2, 2);
  if (texture2D.LoadImage(imagePart.Data.ToArray())) {
    // Do something with the image
  }
}

Replacement configuration options

This section describes replacement options for various model configuration options to help control the response of the model.

Safety settings

You configure the safety settings for Imagen models using ImagenSafetySettings. However, for Gemini Image models, you need to migrate to using SafetySetting.

Model configuration parameters

You configure Imagen models with an ImagenGenerationConfig. However, for Gemini Image models, you need to migrate to using a GenerationConfig and optionally a nested ImageConfig (this is available starting with the early May 2026 versions of the SDKs).

As part of the GenerationConfig, set a response modality of IMAGE (as shown in the "after" code samples earlier in this guide). Note that you can optionally configure Gemini Image models to return both IMAGE and TEXT.

Review the following table to understand how to migrate your model configuration parameters from Imagen to Gemini Image models:

Imagen models Gemini Image models ("Nano Banana")
addWatermark

Not supported

Gemini Image models always return generated images with a SynthID watermark.

aspectRatio

Use aspectRatio in an ImageConfig

For code samples and supported values, see Configure image generation in the Gemini Image models guide.

imageFormat

Not supported

Gemini Image models always return generated images in PNG format.

negativePrompt

Not supported

Note that negative prompts are a legacy feature, and they haven't been supported since imagen-3.0-generate-002 (or by any of the Imagen 4 models).

numberOfImages

Not supported

Gemini Image models always return a single generated image.
As a workaround, you can run your generation in a loop to achieve the same result. Note that candidate count doesn't work as a replacement.

personGeneration

Not supported

By default, Gemini Image models allow generating images of people.