Generate images using text prompts

Caution: Starting on June 24, 2025, Imagen versions 1 and 2 are deprecated. Imagen models imagegeneration@002, imagegeneration@005, and imagegeneration@006 will be removed on September 24, 2025 . For more information about migrating to Imagen 3, see Migrate to Imagen 3.

You can use Imagen on Vertex AI to generate new images from a text prompt. Supported interfaces include the Google Cloud console and the Vertex AI API.

For more information about writing text prompts for image generation and editing, see the prompt guide.

View Imagen for Generation model card

Try image generation (Vertex AI Studio)

Try Imagen in a Colab

Before you begin

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

3. Make sure that billing is enabled for your Google Cloud project.

4. Enable the Vertex AI API.

   Enable the API

5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

6. Make sure that billing is enabled for your Google Cloud project.

7. Enable the Vertex AI API.

   Enable the API

8. Set up authentication for your environment.

   Select the tab for how you plan to use the samples on this page:

   Console

   When you use the Google Cloud console to access Google Cloud services and APIs, you don't need to set up authentication.

   Python

   To use the Python samples on this page in a local development environment, install and initialize the gcloud CLI, and then set up Application Default Credentials with your user credentials.

   1. Install the Google Cloud CLI.

   2. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   3. To initialize the gcloud CLI, run the following command:

      gcloud init

   4. If you're using a local shell, then create local authentication credentials for your user account:

      gcloud auth application-default login

      You don't need to do this if you're using Cloud Shell.

      If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

   For more information, see Set up ADC for a local development environment in the Google Cloud authentication documentation.

   REST

   To use the REST API samples on this page in a local development environment, you use the credentials you provide to the gcloud CLI.

   After installing the Google Cloud CLI, initialize it by running the following command:

   gcloud init

   If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

   For more information, see Authenticate for using REST in the Google Cloud authentication documentation.

Generate images with text

You can generate novel images using only descriptive text as an input. The following samples show you basic instructions to generate images.

Console

1. In the Google Cloud console, go to the Vertex AI > Media Studio page.

   Go to Media Studio

2. Click Imagen. The Imagen Media Studio image generation page is displayed.

3. Optional: In the Settings pane, configure the following settings:

   • Model: choose a model from the available options.

     For more information about available models, see Imagen models

   • Aspect ratio: choose an aspect ratio from the available options.

   • Number of results: adjust the slider or enter a value between 1 and 4.

4. Optional: In the Advanced options section, select a Region to generate your images in.

5. In the Write your prompt box, enter your text prompt that describes the images to generate. For example, small boat on water in the morning watercolor illustration.

   For more information details about writing effective prompts, see Prompt and image attribute guide.

6. Click Generate.

   A digital watermark is automatically added to generated images. You can't disable digital watermark for image generation using the Google Cloud console.

   You can select an image to view in the Image detail window. Watermarked images contain a Digital watermark badge. You can also explicitly verify an image watermark.

   

   ^{Image detail view of a watermarked image generated with Imagen 2 from the prompt: small red boat on water in the morning watercolor illustration muted colors.}

Gen AI SDK for Python

Install

pip install --upgrade google-genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_VERTEXAI=True

In this sample you call the generate_images method on the ImageGenerationModel and save generated images locally. You then can optionally use the show() method in a notebook to show you the generated images. For more information on model versions and features, see Imagen models.

from google import genai

client = genai.Client()

# TODO(developer): Update and un-comment below line
# output_file = "output-image.png"

image = client.models.generate_images(
    model="imagen-4.0-generate-preview-06-06",
    prompt="A dog reading a newspaper",
)

image.generated_images[0].image.save(output_file)

print(f"Created output image using {len(image.generated_images[0].image.image_bytes)} bytes")
# Example response:
# Created output image using 1234567 bytes

REST

For more information about imagegeneration model requests, see the imagegeneration model API reference.

Before using any of the request data, make the following replacements:

• PROJECT_ID: Your Google Cloud project ID.

• MODEL_VERSION: The Imagen model version to use. For more information about available models, see Imagen models.

• LOCATION: Your project's region. For example, us-central1, europe-west2, or asia-northeast3. For a list of available regions, see Generative AI on Vertex AI locations.
• TEXT_PROMPT: The text prompt that guides what images the model generates. This field is required for both generation and editing.
• IMAGE_COUNT: The number of generated images. Accepted integer values: 1-8 (imagegeneration@002), 1-4 (all other model versions). Default value: 4.

Additional optional parameters

Use the following optional variables depending on your use case. Add some or all of the following parameters in the "parameters": {} object. This list shows common optional parameters and isn't meant to be exhaustive. For more information about optional parameters, see Imagen API reference: Generate images.

"parameters": {
  "sampleCount": IMAGE_COUNT,
  "addWatermark": ADD_WATERMARK,
  "aspectRatio": "ASPECT_RATIO",
  "enhancePrompt": ENABLE_PROMPT_REWRITING,
  "includeRaiReason": INCLUDE_RAI_REASON,
  "includeSafetyAttributes": INCLUDE_SAFETY_ATTRIBUTES,
  "outputOptions": {
    "mimeType": "MIME_TYPE",
    "compressionQuality": COMPRESSION_QUALITY
  },
  "personGeneration": "PERSON_SETTING",
  "safetySetting": "SAFETY_SETTING",
  "seed": SEED_NUMBER,
  "storageUri": "OUTPUT_STORAGE_URI"
}

• ADD_WATERMARK: boolean. Optional. Whether to enable a watermark for generated images. Any image generated when the field is set to true contains a digital SynthID that you can use to verify a watermarked image. If you omit this field, the default value of true is used; you must set the value to false to disable this feature. You can use the seed field to get deterministic output only when this field is set to false.
• ASPECT_RATIO: string. Optional. A generation mode parameter that controls aspect ratio. Supported ratio values and their intended use:
  • 1:1 (default, square)
  • 3:4 (Ads, social media)
  • 4:3 (TV, photography)
  • 16:9 (landscape)
  • 9:16 (portrait)
• ENABLE_PROMPT_REWRITING: boolean. Optional. A parameter to use an LLM-based prompt rewriting feature to deliver higher quality images that better reflect the original prompt's intent. Disabling this feature may impact image quality and prompt adherence. Default value: true.
• INCLUDE_RAI_REASON: boolean. Optional. Whether to enable the Responsible AI filtered reason code in responses with blocked input or output. Default value: true.
• INCLUDE_SAFETY_ATTRIBUTES: boolean. Optional. Whether to enable rounded Responsible AI scores for a list of safety attributes in responses for unfiltered input and output. Safety attribute categories: "Death, Harm & Tragedy", "Firearms & Weapons", "Hate", "Health", "Illicit Drugs", "Politics", "Porn", "Religion & Belief", "Toxic", "Violence", "Vulgarity", "War & Conflict". Default value: false.
• MIME_TYPE: string. Optional. The MIME type of the content of the image. Available values:
  • image/jpeg
  • image/gif
  • image/png
  • image/webp
  • image/bmp
  • image/tiff
  • image/vnd.microsoft.icon
• COMPRESSION_QUALITY: integer. Optional. Only applies to JPEG output files. The level of detail the model preserves for images generated in JPEG file format. Values: 0 to 100, where a higher number means more compression. Default: 75.
• PERSON_SETTING: string. Optional. The safety setting that controls the type of people or face generation the model allows. Available values:
  • allow_adult (default): Allow generation of adults only, except for celebrity generation. Celebrity generation is not allowed for any setting.
  • dont_allow: Disable the inclusion of people or faces in generated images.
• SAFETY_SETTING: string. Optional. A setting that controls safety filter thresholds for generated images. Available values:
  • block_low_and_above: The highest safety threshold, resulting in the largest amount of generated images that are filtered. Previous value: block_most.
  • block_medium_and_above (default): A medium safety threshold that balances filtering for potentially harmful and safe content. Previous value: block_some.
  • block_only_high: A safety threshold that reduces the number of requests blocked due to safety filters. This setting might increase objectionable content generated by Imagen. Previous value: block_few.
• SEED_NUMBER: integer. Optional. Any non-negative integer you provide to make output images deterministic. Providing the same seed number always results in the same output images. If the model you're using supports digital watermarking, you must set "addWatermark": false to use this field. Accepted integer values: 1 - 2147483647.
• OUTPUT_STORAGE_URI: string. Optional. The Cloud Storage bucket to store the output images. If not provided, base64-encoded image bytes are returned in the response. Sample value: gs://image-bucket/output/.

HTTP method and URL:

POST https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/publishers/google/models/MODEL_VERSION:predict

Request JSON body:

{
  "instances": [
    {
      "prompt": "TEXT_PROMPT"
    }
  ],
  "parameters": {
    "sampleCount": IMAGE_COUNT
  }
}

To send your request, choose one of these options:

curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/publishers/google/models/MODEL_VERSION:predict"

PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/publishers/google/models/MODEL_VERSION:predict" | Select-Object -Expand Content

The following sample response is for a request with "sampleCount": 2. The response returns two prediction objects, with the generated image bytes base64-encoded.

{
  "predictions": [
    {
      "bytesBase64Encoded": "BASE64_IMG_BYTES",
      "mimeType": "image/png"
    },
    {
      "mimeType": "image/png",
      "bytesBase64Encoded": "BASE64_IMG_BYTES"
    }
  ]
}

If you use a model that supports prompt enhancement, the response includes an additional prompt field with the enhanced prompt used for generation:

{
  "predictions": [
    {
      "mimeType": "MIME_TYPE",
      "prompt": "ENHANCED_PROMPT_1",
      "bytesBase64Encoded": "BASE64_IMG_BYTES_1"
    },
    {
      "mimeType": "MIME_TYPE",
      "prompt": "ENHANCED_PROMPT_2",
      "bytesBase64Encoded": "BASE64_IMG_BYTES_2"
    }
  ]
}

What's next

Read articles about Imagen and other Generative AI on Vertex AI products:

• A developer's guide to getting started with Imagen 3 on Vertex AI
• New generative media models and tools, built with and for creators
• New in Gemini: Custom Gems and improved image generation with Imagen 3
• Google DeepMind: Imagen 3 - Our highest quality text-to-image model