Veo is the name of the model that supports video generation. Veo generates a video from a text prompt or an image prompt (/products#product-launch-stages) 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)
Request access: Experimental features
Supported Models
Model | Model ID |
---|---|
Video Generation | veo-2.0-generate-001 |
HTTP request
POST https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning
Request body
{
"instances": [
{
"prompt": string,
// Optional. An image to guide video generation.
"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
}
}
],
"parameters": {
"aspectRatio": string,
"negativePrompt": string,
"personGeneration": string,
"sampleCount": integer,
"seed": uint32,
"storageUri": string,
"durationSeconds": integer,
"enhancePrompt": boolean
}
}
Use the following parameters for the Veo model. For more information, see Generate videos using text and image prompts using Veo.
Parameter | Description | Type | Acceptable values and description | |
---|---|---|---|---|
image | Mandatory (image-to-video) Optional if a text prompt is provided (text-to-video) Image input for guiding video generation. |
string |
Recommended: 1280 x 720 pixels or 720 x 1280 pixels If the aspect ratio of the image is different, the image is cropped using a center crop tool. If the aspect ratio of the image is the same but the resolution is larger, the image is resized. |
|
prompt | Mandatory (text-to-video) Optional if an input image prompt is provided (image-to-video) A text string to guide the first eight seconds ( veo-2.0-generate-001 ) in the video.
|
string |
Any text string to guide video generation. For example:
|
|
durationSeconds | Required The length of video files that you want to generate. |
integer | Accepted integer values are 5-8. The default is 8. | |
negativePrompt | Optional A text string that describes anything you want to discourage the model from generating. |
string |
Any text string to instruct the model to omit from generated videos. For example:
|
|
enhancePrompt | Optional Use gemini to enhance your prompts. |
boolean |
Accepted values are yes or no . The default is yes .
|
|
seed | 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. |
uint32 | 0 - 4,294,967,295 |
|
storageURI | Optional A Cloud Storage bucket URI to store the output video. If not provided, base64-encoded video bytes are returned in the response. |
string | The Cloud Storage location for saving the generated videos. Pattern: gs://BUCKET_NAME/SUBDIRECTORY | |
sampleCount | Optional The number of output images requested. |
int | 1-4 | |
aspectRatio | Optional Defines the aspect ratio of the generated video. |
string | 16:9 (default, landscape) 9:16 (portrait) | ∏
|
personGeneration | Optional The safety setting that controls whether people or face generation is allowed. |
string | allow_adult (default value): allow generation of adults only disallow: disallows inclusion of people/faces in images |
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 allowlist)
- 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) or9:16
(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
.
- ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated
videos. Values:
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
{ "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 allowlist)
- 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
orimage/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) or9:16
(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
.
- ASPECT_RATIO: string. Optional. Defines the aspect ratio of the generated
videos. Values:
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
{ "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 allowlist)
- 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
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 the following response:
{
"name": string,
"done": boolean,
"response":{
"@type":"type.googleapis.com/cloud.ai.large_models.vision.GenerateVideoResponse",
"videos":[
{
"gcsUri": string,
"mimeType": string
},
{
"gcsUri": string,
"mimeType": string
},
{
"gcsUri": string,
"mimeType": string
},
{
"gcsUri": string,
"mimeType": string
},
]
}
}
Response element | Description |
---|---|
name |
The full operation name of the long-running operation that begins after a video generation request is sent. |
done |
A boolean value that indicates whether the operation is complete. |
response |
The response body of the long-running operation. |
generatedSamples |
An array of the generated video sample objects. |
video |
The generated video. |
uri |
The Cloud Storage URI of the generated video. |
encoding |
The video encoding type. |
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",
"generatedSamples":[
{
"video":{
"uri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_0.mp4",
"encoding":"video/mp4"
}
},
{
"video":{
"uri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_1.mp4",
"encoding":"video/mp4"
}
},
{
"video":{
"uri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_2.mp4",
"encoding":"video/mp4"
}
},
{
"video":{
"uri":"gs://STORAGE_BUCKET/TIMESTAMPED_SUBDIRECTORY/sample_3.mp4",
"encoding":"video/mp4"
}
}
]
}
}
More information
- For more information about using Veo on Vertex AI, see Generate videos using text and image prompts using Veo.
What's next
- Read Google DeepMind's information on the Veo model.
- Read the blog post "Veo and Imagen 3: Announcing new video and image generation models on Vertex AI".
- Read the blog post "New generative media models and tools, built with and for creators".