Veo on Vertex AI API

Veo is the name of the model that supports video generation. Veo generates a video from a text prompt or an image prompt that you provide.

To explore this model in the console, see the Video Generation model card in the Model Garden.

Try Veo on Vertex AI (Vertex AI Studio)

Try Veo in a Colab

Request access: Advanced features & Veo waitlist

Supported Models

Veo API supports the following models:

HTTP request

curl -X POST \
  -H "Authorization: Bearer $(gcloud auth print-access-token)" \
  -H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/publishers/google/models/MODEL_ID:predictLongRunning \

-d '{
  "instances": [
    {
      "prompt": string,
      "image": {
        // Union field can be only one of the following:
        "bytesBase64Encoded": string,
        "gcsUri": string,
        // End of list of possible types for union field.
        "mimeType": string
      },
      "lastFrame": {
        // Union field can be only one of the following:
        "bytesBase64Encoded": string,
        "gcsUri": string,
        // End of list of possible types for union field.
        "mimeType": string
      },
      "video": {
        // Union field can be only one of the following:
        "bytesBase64Encoded": string,
        "gcsUri": string,
        // End of list of possible types for union field.
        "mimeType": string
      }
    }
  ],
  "parameters": {
    "aspectRatio": string,
    "durationSeconds": integer,
    "enhancePrompt": boolean,
    "generateAudio": boolean,
    "negativePrompt": string,
    "personGeneration": string,
    "sampleCount": integer,
    "seed": uint32,
    "storageUri": string
  }
}'
Instances

prompt

string

Required for text-to-video.
Optional if an input image prompt is provided (image-to-video).

A text string to guide the first eight seconds in the video. For example:

  • A fast-tracking shot through a bustling dystopian sprawl with bright neon signs, flying cars and mist, night, lens flare, volumetric lighting
  • A neon hologram of a car driving at top speed, speed of light, cinematic, incredible details, volumetric lighting
  • Many spotted jellyfish pulsating under water. Their bodies are transparent and glowing in deep ocean
  • extreme close-up with a shallow depth of field of a puddle in a street. reflecting a busy futuristic Tokyo city with bright neon signs, night, lens flare
  • Timelapse of the northern lights dancing across the Arctic sky, stars twinkling, snow-covered landscape
  • A lone cowboy rides his horse across an open plain at beautiful sunset, soft light, warm colors

Union field image.

Optional. An image to guide video generation, which can be either a bytesBase64Encoded string that encodes an image or a gcsUri string URI to a Cloud Storage bucket location.

Union field lastFrame.

Optional. An image of the first frame of a video to fill the space between. lastFrame can be either a bytesBase64Encoded string that encodes an image or a gcsUri string URI to a Cloud Storage bucket location.

lastFrame is supported by veo-2.0-generate-001 only.

Union field video.

Optional. A Veo generated video to extend in length, which can be either a bytesBase64Encoded string that encodes a video or a gcsUri string URI to a Cloud Storage bucket location.

video is supported by veo-2.0-generate-001 only.

bytesBase64Encoded

string

A bytes Base64-encoded string of an image or video file.
gcsUri

string

A string URI to a Cloud Storage bucket location.
mimeType

string

Required for the following objects:

Specifies the mime type of a video or image.

For images, the following mime types are accepted:

  • image/jpeg
  • image/png

For videos, the following mime types are accepted:

  • video/mp4
Parameters
aspectRatio

string

Optional. Specifies the aspect ratio of generated videos. The following are accepted values:

  • 16:9 (default value)
  • 9:16 (not supported by veo-3.0-generate-preview)
durationSeconds

integer

Required. The length of video files that you want to generate.

The following are the accepted values for each model:

  • veo-2.0-generate-001: 5-8. The default is 8.
  • veo-3.0-generate-preview: 8.
enhancePrompt

boolean

Optional. Use Gemini to enhance your prompts. Accepted values are true or false. The default value is true.

generateAudio

boolean

Required for veo-3.0-generate-preview. Generate audio for the video. Accepted values are true or false.

generateAudio isn't supported by veo-2.0-generate-001.

negativePrompt

string

Optional. A text string that describes anything you want to discourage the model from generating. For example:

  • overhead lighting, bright colors
  • people, animals
  • multiple cars, wind
personGeneration

string

Optional. The safety setting that controls whether people or face generation is allowed. One of the following:

  • allow_adult (default value): allow generation of adults only
  • dont_allow: disallows inclusion of people/faces in images
sampleCount

int

Optional. The number of output videos requested. Accepted values are 1-4.

seed

uint32

Optional. A number to request to make generated videos deterministic. Adding a seed number with your request without changing other parameters will cause the model to produce the same videos.

The accepted range is 0-4,294,967,295.

storageUri

string

Optional. A Cloud Storage bucket URI to store the output video, in the format gs://BUCKET_NAME/SUBDIRECTORY. If a Cloud Storage bucket isn't provided, base64-encoded video bytes are returned in the response.

Sample request

Use the following requests to send a text-to-video request or an image-to-video request:

Text-to-video generation request

REST

To test a text prompt by using the Vertex AI Veo API, send a POST request to the publisher model endpoint.

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

  • PROJECT_ID: Your Google Cloud project ID.
  • MODEL_ID: The model ID to use. Available values:
    • veo-2.0-generate-001 (GA)
    • veo-3.0-generate-preview (Preview)
    • veo-3.0-fast-generate-preview (Preview)
  • TEXT_PROMPT: The text prompt used to guide video generation.
  • OUTPUT_STORAGE_URI: Optional: The Cloud Storage bucket to store the output videos. If not provided, video bytes are returned in the response. For example: gs://video-bucket/output/.
  • RESPONSE_COUNT: The number of video files you want to generate. Accepted integer values: 1-4.
  • DURATION: The length of video files that you want to generate. Accepted integer values are 5-8.

  • 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. 

    "parameters": {
  "aspectRatio": "ASPECT_RATIO",
  "negativePrompt": "NEGATIVE_PROMPT",
  "personGeneration": "PERSON_SAFETY_SETTING",
  "sampleCount": RESPONSE_COUNT,
  "seed": SEED_NUMBER
}
    • ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated videos. Values: 16:9 (default, landscape) or 9:16 (portrait).
    • NEGATIVE_PROMPT: string. Optional. A text string that describes what you want to discourage the model from generating.
    • PERSON_SAFETY_SETTING: string. Optional. The safety setting that controls whether people or face generation is allowed. Values:
      • allow_adult (default value): Allow generation of adults only.
      • disallow: Disallows inclusion of people or faces in images.
    • RESPONSE_COUNT: int. Optional. The number of output images requested. Values: 1-4.
    • SEED_NUMBER: uint32. Optional. A number to make generated videos deterministic. Specifying a seed number with your request without changing other parameters guides the model to produce the same videos. Values: 0 - 4294967295.

HTTP method and URL: 

POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning

Request JSON body: 

{
  "instances": [
    {
      "prompt": "TEXT_PROMPT"
    }
  ],
  "parameters": {
    "storageUri": "OUTPUT_STORAGE_URI",
    "sampleCount": "RESPONSE_COUNT"
  }
}

To send your request, choose one of these options:

curl

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://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning"

PowerShell

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://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning" | Select-Object -Expand Content
This request returns a full operation name with a unique operation ID. Use this full operation name to poll that status of the video generation request. 
{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/a1b07c8e-7b5a-4aba-bb34-3e1ccb8afcc8"
}

Image-to-video generation request

REST

To test a text prompt by using the Vertex AI Veo API, send a POST request to the publisher model endpoint.

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

  • PROJECT_ID: Your Google Cloud project ID.
  • MODEL_ID: The model ID to use. Available values:
    • veo-2.0-generate-001 (GA)
    • veo-3.0-generate-preview (Preview)
  • TEXT_PROMPT: The text prompt used to guide video generation.
  • INPUT_IMAGE: Base64-encoded bytes string representing the input image. To ensure quality, the input image should be 720p or higher (1280 x 720 pixels) and have a 16:9 or 9:16 aspect ratio. Images of other aspect ratios or sizes may be resized or centrally cropped during the upload process.
  • MIME_TYPE: The MIME type of the input image. Only the images of the following MIME types are supported: image/jpeg or image/png.
  • OUTPUT_STORAGE_URI: Optional: The Cloud Storage bucket to store the output videos. If not provided, video bytes are returned in the response. For example: gs://video-bucket/output/.
  • RESPONSE_COUNT: The number of video files you want to generate. Accepted integer values: 1-4.
  • DURATION: The length of video files that you want to generate. Accepted integer values are 5-8.

  • 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. 

    "parameters": {
  "aspectRatio": "ASPECT_RATIO",
  "negativePrompt": "NEGATIVE_PROMPT",
  "personGeneration": "PERSON_SAFETY_SETTING",
  "sampleCount": RESPONSE_COUNT,
  "seed": SEED_NUMBER
}
    • ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated videos. Values: 16:9 (default, landscape) or 9:16 (portrait).
    • NEGATIVE_PROMPT: string. Optional. A text string that describes what you want to discourage the model from generating.
    • PERSON_SAFETY_SETTING: string. Optional. The safety setting that controls whether people or face generation is allowed. Values:
      • allow_adult (default value): Allow generation of adults only.
      • disallow: Disallows inclusion of people or faces in images.
    • RESPONSE_COUNT: int. Optional. The number of output images requested. Values: 1-4.
    • SEED_NUMBER: uint32. Optional. A number to make generated videos deterministic. Specifying a seed number with your request without changing other parameters guides the model to produce the same videos. Values: 0 - 4294967295.

HTTP method and URL: 

POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning

Request JSON body: 

{
  "instances": [
    {
      "prompt": "TEXT_PROMPT",
      "image": {
        "bytesBase64Encoded": "INPUT_IMAGE",
        "mimeType": "MIME_TYPE"
      }
    }
  ],
  "parameters": {
    "storageUri": "OUTPUT_STORAGE_URI",
    "sampleCount": RESPONSE_COUNT
  }
}

To send your request, choose one of these options:

curl

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://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning"

PowerShell

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://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning" | Select-Object -Expand Content
This request returns a full operation name with a unique operation ID. Use this full operation name to poll that status of the video generation request. 
{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/a1b07c8e-7b5a-4aba-bb34-3e1ccb8afcc8"
}

Poll the status of the video generation long-running operation

Check the status of the video generation long-running operation.

REST

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

  • PROJECT_ID: Your Google Cloud project ID.
  • MODEL_ID: The model ID to use. Available values:
    • veo-2.0-generate-001 (GA)
    • veo-3.0-generate-preview (Preview)
  • OPERATION_ID: The unique operation ID returned in the original generate video request.

HTTP method and URL: 

POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:fetchPredictOperation

Request JSON body: 

{
  "operationName": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/OPERATION_ID"
}

To send your request, choose one of these options:

curl

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://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:fetchPredictOperation"

PowerShell

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://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:fetchPredictOperation" | Select-Object -Expand Content
This request returns information about the operation, including if the operation is still running or is done.

Response body (generate video request)

Sending a text-to-video or image-to-video request returns the following response:

{
  "name": string
}
Response element Description
name The full operation name of the long-running operation that begins after a video generation request is sent.

Sample response (generate video request)

{
  "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/OPERATION_ID"
}

Response body (poll long-running operation)

Polling the status of the original video generation long-running operation returns a response similar to the following:

{
   "name": string,
   "done": boolean,
   "response":{
      "@type":"type.googleapis.com/cloud.ai.large_models.vision.GenerateVideoResponse",
      "raiMediaFilteredCount": integer,
      "videos":[
         {
           "gcsUri": string,
           "mimeType": string
         },
         {
           "gcsUri": string,
           "mimeType": string
         },
         {
           "gcsUri": string,
           "mimeType": string
         },
         {
           "gcsUri": string,
           "mimeType": string
         },
      ]
   }
}
Response element Description
bytesBase64Encoded A Base64 bytes encoded string that represents the video object.
done A boolean value that indicates whether the operation is complete.
encoding The video encoding type.
gcsUri The Cloud Storage URI of the generated video.
name The full operation name of the long-running operation that begins after a video generation request is sent.
raiMediaFilteredCount Returns a count of videos that Veo filtered due to responsible AI policies. If no videos are filtered, the returned count is 0.
raiMediaFilteredReasons Lists the reasons for any Veo filtered videos due to responsible AI policies. For more information, see Safety filter code categories.
response The response body of the long-running operation.
video The generated video.

Sample response (poll long-running operation)

{
   "name": "projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID/operations/OPERATION_ID",
   "done":true,
   "response":{
      "@type":"type.googleapis.com/cloud.ai.large_models.vision.GenerateVideoResponse",
      "raiMediaFilteredCount": 0,
      "videos":[
        {
          "gcsUri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_0.mp4",
          "mimeType":"video/mp4"
        },
        {
          "gcsUri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_1.mp4",
          "mimeType":"video/mp4"
        },
        {
          "gcsUri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_2.mp4",
          "mimeType":"video/mp4"
        },
        {
          "gcsUri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_3.mp4",
          "mimeType":"video/mp4"
        }
      ]
   }
}

More information

What's next