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
GenerativeModelinstance (instead of anImagenModelinstance). -
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.
- As part of this configuration, set a response modality of
-
( 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 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 |
numberOfImages
|
Not supported Gemini
Image models always return a single generated image. |
personGeneration
|
Not supported By default, Gemini Image models allow generating images of people. |
