Extend videos

You can use Gemini Omni Flash or Veo on Gemini Enterprise Agent Platform to extend videos. The input video is limited between 1 and 30 seconds in length. Videos can be extended up to 40 seconds for Gemini Omni Flash or 37 seconds for Veo on Gemini Enterprise Agent Platform. You can extend videos using either the Google Cloud console or the Agent Platform API.

The following models support extending videos:

Gemini Omni Flash

Click to expand supported models

• gemini-omni-1.1-flash-preview preview

Veo

Click to expand supported models

• veo-3.1-lite-generate-001 preview
• veo-3.1-generate-preview preview
• veo-3.1-generate-001
• veo-3.1-fast-generate-preview preview
• veo-3.1-fast-generate-001
• veo-2.0-generate-exp preview
• veo-2.0-generate-preview preview

For information about writing effective text prompts for video generation, see the Video prompt guide.

Before you begin

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.

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

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

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

Enable the Agent Platform API.

Roles required to enable APIs

To enable APIs, you need the serviceusage.services.enable permission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.

Enable the API

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

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

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

Enable the Agent Platform API.

Roles required to enable APIs

To enable APIs, you need the serviceusage.services.enable permission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.

Enable the API

1. 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.

   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.

   Install the Google Cloud CLI.

   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.

Veo limitations

When using Veo to extend videos, input videos are subject to the following limitations:

• The input file must be MP4.
• The length must be 1 to 30 seconds.
• The frame rate must be 24 frames per second.
• The resolution must be one of: 720p, 1080p, or 4k.
• The aspect ratio for input videos can be either 9:16 or 16:9.

When using Veo to extend videos, output videos are subject to the following limitations

• The output file is MP4.
• The extended length is 7 seconds.
• The frame rate is 24 frames per second.
• The resolution can be 720p, 1080p, or 4k.
• The aspect ratio for output videos can be either 9:16 or 16:9.

Extend videos using Gemini Omni Flash

To extend videos using Gemini Omni Flash, do the following:

REST

Video generation can take over a minute to complete. To generate a video to download immediately after completion, use a synchronous request. To generate a video that you can download later, send an asynchronous request by setting the background parameter to true. Asynchronous requests are retained for up to 14 days.

For more information about using the Gemini Omni Flash API, seek Interactions API.

Synchronous request

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

• PROJECT_ID: A string representing your Google Cloud project ID.
• MODEL_ID: A string representing the model ID to use. The following are accepted values:
  • "gemini-omni-1.1-flash-preview"
• TEXT_PROMPT: The text prompt used to guide video generation.
• CLOUD_STORAGE_INPUT_URI: A string representing the Cloud Storage bucket that contains the input media. For example: "gs://video-bucket/input/".
• CLOUD_STORAGE_OUTPUT_URI: Optional: A string representing 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/".
• ASPECT_RATIO: Optional: A string representing the expected aspect ratio of the output video. If not provided, the aspect ratio is inferred from the prompt. The following are accepted values:
  • "16:9"
  • "9:16"
• DURATION: A string representing the length of the generated video files. Allowed strings are integers between 3 and 10, followed by "s" for seconds. For example, "10s".

HTTP method and URL:

POST https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions

Request JSON body:

{
  "model": "MODEL_ID",
  "input": [
    {
      "type": "text",
      "text": "TEXT_PROMPT"
    },
    {
      "type": "image",
      "uri": "CLOUD_STORAGE_INPUT_URI",
      "mime_type": "image/png"
    }
  ],
  "response_format": [
    {
      "type": "video",
      "delivery": "uri",
      "gcs_uri": "CLOUD_STORAGE_OUTPUT_URI",
      "aspect_ratio": "ASPECT_RATIO",
      "duration": "DURATION"
    }
  ],
  "generation_config": {
    "video_config": {
      "task": "extend"
    }
  }
}

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 TOKEN" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions"

PowerShell

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

$headers = @{ "Authorization" = "Bearer TOKEN" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions" | Select-Object -Expand Content

The response contains an interaction which includes the model thoughts and an output video.

{
  "id":"INTERACTION_ID",
  "model":"gemini-omni-flash-preview",
  "status":"completed",
  "usage":{
    "total_tokens":479,
    "total_input_tokens":26,
    "input_tokens_by_modality":[
      {
        "modality":"text",
        "tokens":26
      },
      {
        "modality":"image",
        "tokens":124
      }
    ],
    "output_tokens_by_modality": [
      {
        "modality": "video",
        "tokens": 28832
      }
    ],
    "total_output_tokens":28832,
    "total_thought_tokens":453
  },
  "steps":[
    {
      "type":"thought",
      "summary":[
        {
          "type":"text",
          "text":"MODEL THOUGHTS"
        }
      ],
    },
    { 
      "type":"model_output",
      "content":[
        {
          "type":"video",
          "uri":"gs://some/output_path/123.mp4",
          "mime_type":"video/mp4" 
        }
      ]
    }
  ],
  "object":"interaction",
  "role":"model",
  "created":"2026-05-29T02:17:56Z",
  "updated":"2026-05-29T02:17:56Z",
}

Asynchronous request

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

• PROJECT_ID: A string representing your Google Cloud project ID.
• MODEL_ID: A string representing the model ID to use. The following are accepted values:
  • "gemini-omni-1.1-flash-preview"
• TEXT_PROMPT: The text prompt used to guide video generation.
• CLOUD_STORAGE_INPUT_URI: A string representing the Cloud Storage bucket that contains the input media. For example: "gs://video-bucket/input/".
• CLOUD_STORAGE_OUTPUT_URI: Optional: A string representing 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/".
• ASPECT_RATIO: Optional: A string representing the expected aspect ratio of the output video. If not provided, the aspect ratio is inferred from the prompt. The following are accepted values:
  • "16:9"
  • "9:16"
• DURATION: A string representing the length of the generated video files. Allowed strings are integers between 3 and 10, followed by "s" for seconds. For example, "10s".

HTTP method and URL:

POST https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions

Request JSON body:

{
  "model": "MODEL_ID",
  "input": [
    {
      "background": true,
      "type": "text",
      "text": "TEXT_PROMPT"
    },
    {
      "type": "image",
      "uri": "CLOUD_STORAGE_INPUT_URI",
      "mime_type": "image/png"
    }
  ],
  "response_format": [
    {
      "type": "video",
      "delivery": "uri",
      "gcs_uri": "CLOUD_STORAGE_OUTPUT_URI",
      "aspect_ratio": "ASPECT_RATIO",
      "duration": "DURATION"
    }
  ],
  "generation_config": {
    "video_config": {
      "task": "extend"
    }
  }
}

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 TOKEN" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions"

PowerShell

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

$headers = @{ "Authorization" = "Bearer TOKEN" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions" | Select-Object -Expand Content

The response contains an interaction ID, which you'll use to get the video you generated.

{
  "id":"INTERACTION_ID",
  "status":"in_progress",
  "object":"interaction"
}

Later, use the INTERACTION_ID to get the generated video:

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

• PROJECT_ID: A string representing your Google Cloud project ID.
• INTERACTION_ID: The interaction ID from the asynchronous request.

HTTP method and URL:

POST https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions/INTERACTION_ID

To send your request, choose one of these options:

curl

Execute the following command:

curl -X POST \
     -H "Authorization: Bearer TOKEN" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d "" \
     "https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions/INTERACTION_ID"

PowerShell

Execute the following command:

$headers = @{ "Authorization" = "Bearer TOKEN" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -Uri "https://aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/global/interactions/INTERACTION_ID" | Select-Object -Expand Content

The response is in a format similar to the following:

{
  "id":"INTERACTION_ID",
  "model":"gemini-omni-flash-preview",
  "status":"completed",
  "usage":{
    "total_tokens":479,
    "total_input_tokens":26,
    "input_tokens_by_modality":[
      {
        "modality":"text",
        "tokens":26
      },
      {
        "modality":"image",
        "tokens":124
      }
    ],
    "output_tokens_by_modality": [
      {
        "modality": "video",
        "tokens": 28832
      }
    ],
    "total_output_tokens":28832,
    "total_thought_tokens":453
  },
  "steps":[
    {
      "type": "user_input",
      "content": [
        {
          "type": "text",
          "text": "5 second, 9:16 video. Use the image as the first frame."
        },
        {
          "type": "image",
          "uri": "gs://some/path",
          "mime_type": "image/png"
        }
      ]
    },
    {
      "type":"thought"
      "summary":[
        {
          "type":"text",
          "text":"MODEL THOUGHTS"
        }
      ],
    },
    { 
      "type":"model_output",
      "content":[
        {
          "type":"video",
          "data":"VIDEO DATA",
          "mime_type":"video/mp4" 
        }
      ]
    }
  ],
  "object":"interaction"
  "role":"model",
  "created":"2026-05-29T02:17:56Z",
  "updated":"2026-05-29T02:17:56Z",
}

Extend videos using Veo

The following examples show how you can extend a Veo video:

Console

1. In the Google Cloud console, go to the Agent Platform > Media Studio page.

   Media Studio

2. Click Video.

3. In the Task menu, select Video extension.

4. From the Model menu, select a model from the displayed options.

5. In the Input video section, click Add.

6. In the Prompt box, enter a text prompt that describes the videos to generate.

7. Optional: Adjust the following Parameters:

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

   • Video length: select a video length from the menu.

• Output directory: click Browse to create or select a Cloud Storage bucket to store the generated files.

1. Click Run.

Python

Install

pip install --upgrade google-genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Google 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_ENTERPRISE=True

import time
from google import genai
from google.genai.types import GenerateVideosConfig, Video

client = genai.Client()

# TODO(developer): Update and un-comment below line
# output_gcs_uri = "gs://your-bucket/your-prefix"

operation = client.models.generate_videos(
    model="veo-3.1-generate-preview",
    prompt="a butterfly flies in and lands on the flower",
    video=Video(
        uri="gs://cloud-samples-data/generative-ai/video/flower.mp4",
        mime_type="video/mp4",
    ),
    config=GenerateVideosConfig(
        output_gcs_uri=output_gcs_uri,
    ),
)

while not operation.done:
    time.sleep(15)
    operation = client.operations.get(operation)
    print(operation)

if operation.response:
    print(operation.result.generated_videos[0].video.uri)

# Example response:
# gs://your-bucket/your-prefix

REST

For more information about the Veo API, see the following:

• Method: endpoints.predict
• VideoGenerationModelInstance
• VideoGenerationModelParams
• VideoGenerationModelResult

1. Use the following command to send a video generation request. This request begins a long-running operation and stores output to a Cloud Storage bucket you specify.

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

   • PROJECT_ID: A string representing your Google Cloud project ID.
   • MODEL_ID: A string that represents the model ID to use. Use one of the following when specifying a first or last video frame:
     • Veo 3: veo-3.1-generate-001
     • Veo 3: veo-3.1-fast-generate-001
   • TEXT_PROMPT: The text prompt used to guide video generation.
   • PATH_TO_VIDEO: A string that represents the Cloud Storage path to the Veo video that you're extending. For example: "gs://video-bucket/input/veo-video.mp4".
   • OUTPUT_STORAGE_URI: Optional: A string representing 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 to generate. The accepted range of values is 1-4.

   • 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.

     "parameters": {
       "aspectRatio": "ASPECT_RATIO",
       "negativePrompt": "NEGATIVE_PROMPT",
       "personGeneration": "PERSON_SAFETY_SETTING",
       // "resolution": RESOLUTION, // Veo 3 models only
       "sampleCount": RESPONSE_COUNT,
       "seed": SEED_NUMBER
     }

     • ASPECT_RATIO: Optional: A string value that describes the aspect ratio of the generated videos. You can use the following values:
       • "16:9" for landscape
       • "9:16" for portrait

       The default value is "16:9"

     • NEGATIVE_PROMPT: Optional: A string value that describes content that you want to prevent the model from generating.
     • PERSON_SAFETY_SETTING: Optional: A string value that controls the safety setting for generating people or face generation. You can use the following values:
       • "allow_adult": Only allow generation of adult people and faces.
       • "disallow": Doesn't generate people or faces.

       The default value is "allow_adult".

     • RESOLUTION: Optional: A string value that controls the resolution of the generated video. Supported by Veo 3 models only. You can use the following values:
       • "720p"
       • "1080p"
       • "4k" (Veo 3.1 Preview models only)

       The default value is "720p".

     • RESPONSE_COUNT: Optional. An integer value that describes the number of videos to generate. The accepted range of values is 1-4.
     • SEED_NUMBER: Optional. An uint32 value that the model uses to generate deterministic videos. Specifying a seed number with your request without changing other parameters guides the model to produce the same videos. The accepted range of values is 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",
          "video": {
            "gcsUri": "PATH_TO_VIDEO",
            "mimeType": "video/mp4"
          }
       }
     ],
     "parameters": {
       "storageUri": "OUTPUT_STORAGE_URI",
       "sampleCount": RESPONSE_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://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/publishers/google/models/MODEL_ID:predictLongRunning"

   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://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"
   }
   

2. Optional: Check the status of the video generation long-running operation.

   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.
   • 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

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

   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://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

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

What's next

• Video generation prompt guide

• Best practices for generating videos

• Generate videos from text prompts

• Generate videos from an image

• Generate videos using first and last video frames

• Generate videos from references

• Edit videos

• Understand responsible AI and usage guidelines for Veo on Gemini Enterprise Agent Platform