To learn about video understanding, see the Video understanding guide.

Veo 3.1 is Google's state-of-the-art model for generating high-fidelity, 8-second 720p, 1080p or 4k videos featuring stunning realism and natively generated audio. You can access this model programmatically using the Gemini API. To learn more about the available Veo model variants, see the Model Versions section.

Veo 3.1 excels at a wide range of visual and cinematic styles and introduces several new capabilities:

• Portrait videos: Choose between landscape (16:9) and portrait (9:16) videos.
• Video extension: Extend videos that were previously generated using Veo.
• Frame-specific generation: Generate a video by specifying the first and/or last frames.
• Image-based direction: Use up to three reference images to guide the content of your generated video.

For more information about writing effective text prompts for video generation, see the Veo prompt guide

Text to video generation

Choose an example to see how to generate a video with dialogue, cinematic realism, or creative animation:

Dialogue & Sound Effects Cinematic Realism Creative Animation

import time
from google import genai
from google.genai import types

client = genai.Client()

prompt = """A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.
A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'"""

operation = client.models.generate_videos(
    model="veo-3.1-generate-preview",
    prompt=prompt,
)

# Poll the operation status until the video is ready.
while not operation.done:
    print("Waiting for video generation to complete...")
    time.sleep(10)
    operation = client.operations.get(operation)

# Download the generated video.
generated_video = operation.response.generated_videos[0]
client.files.download(file=generated_video.video)
generated_video.video.save("dialogue_example.mp4")
print("Generated video saved to dialogue_example.mp4")

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const prompt = `A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.
A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'`;

let operation = await ai.models.generateVideos({
    model: "veo-3.1-generate-preview",
    prompt: prompt,
});

// Poll the operation status until the video is ready.
while (!operation.done) {
    console.log("Waiting for video generation to complete...")
    await new Promise((resolve) => setTimeout(resolve, 10000));
    operation = await ai.operations.getVideosOperation({
        operation: operation,
    });
}

// Download the generated video.
ai.files.download({
    file: operation.response.generatedVideos[0].video,
    downloadPath: "dialogue_example.mp4",
});
console.log(`Generated video saved to dialogue_example.mp4`);

package main

import (
    "context"
    "log"
    "os"
    "time"

    "google.golang.org/genai"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    prompt := `A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.
    A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'`

    operation, _ := client.Models.GenerateVideos(
        ctx,
        "veo-3.1-generate-preview",
        prompt,
        nil,
        nil,
    )

    // Poll the operation status until the video is ready.
    for !operation.Done {
    log.Println("Waiting for video generation to complete...")
        time.Sleep(10 * time.Second)
        operation, _ = client.Operations.GetVideosOperation(ctx, operation, nil)
    }

    // Download the generated video.
    video := operation.Response.GeneratedVideos[0]
    client.Files.Download(ctx, video.Video, nil)
    fname := "dialogue_example.mp4"
    _ = os.WriteFile(fname, video.Video.VideoBytes, 0644)
    log.Printf("Generated video saved to %s
", fname)
}

import com.google.genai.Client;
import com.google.genai.types.GenerateVideosOperation;
import com.google.genai.types.Video;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;

class GenerateVideoFromText {
  public static void main(String[] args) throws Exception {
    Client client = new Client();

    String prompt = "A close up of two people staring at a cryptic drawing on a wall, torchlight flickering.
" +
"A man murmurs, 'This must be it. That's the secret code.' The woman looks at him and whispering excitedly, 'What did you find?'";

    GenerateVideosOperation operation =
        client.models.generateVideos("veo-3.1-generate-preview", prompt, null, null);

    // Poll the operation status until the video is ready.
    while (!operation.done().isPresent() || !operation.done().get()) {
      System.out.println("Waiting for video generation to complete...");
      Thread.sleep(10000);
      operation = client.operations.getVideosOperation(operation, null);
    }

    // Download the generated video.
    Video video = operation.response().get().generatedVideos().get().get(0).video().get();
    Path path = Paths.get("dialogue_example.mp4");
    client.files.download(video, path.toString(), null);
    if (video.videoBytes().isPresent()) {
      Files.write(path, video.videoBytes().get());
      System.out.println("Generated video saved to dialogue_example.mp4");
    }
  }
}

# Note: This script uses jq to parse the JSON response.
# GEMINI API Base URL
BASE_URL="https://generativelanguage.googleapis.com/v1beta"

# Send request to generate video and capture the operation name into a variable.
operation_name=$(curl -s "${BASE_URL}/models/veo-3.1-generate-preview:predictLongRunning" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -X "POST" \
  -d '{
    "instances": [{
        "prompt": "A close up of two people staring at a cryptic drawing on a wall, torchlight flickering. A man murmurs, \"This must be it. That'\''s the secret code.\" The woman looks at him and whispering excitedly, \"What did you find?\""
      }
    ]
  }' | jq -r .name)

# Poll the operation status until the video is ready
while true; do
  # Get the full JSON status and store it in a variable.
  status_response=$(curl -s -H "x-goog-api-key: $GEMINI_API_KEY" "${BASE_URL}/${operation_name}")

  # Check the "done" field from the JSON stored in the variable.
  is_done=$(echo "${status_response}" | jq .done)

  if [ "${is_done}" = "true" ]; then
    # Extract the download URI from the final response.
    video_uri=$(echo "${status_response}" | jq -r '.response.generateVideoResponse.generatedSamples[0].video.uri')
    echo "Downloading video from: ${video_uri}"

    # Download the video using the URI and API key and follow redirects.
    curl -L -o dialogue_example.mp4 -H "x-goog-api-key: $GEMINI_API_KEY" "${video_uri}"
    break
  fi
  # Wait for 5 seconds before checking again.
  sleep 10
done

Control the aspect ratio

Veo 3.1 lets you create landscape (16:9, the default setting) or portrait (9:16) videos. You can tell the model which one you want using the aspect_ratio parameter:

import time
from google import genai
from google.genai import types

client = genai.Client()

prompt = """A montage of pizza making: a chef tossing and flattening the floury dough, ladling rich red tomato sauce in a spiral, sprinkling mozzarella cheese and pepperoni, and a final shot of the bubbling golden-brown pizza, upbeat electronic music with a rhythmical beat is playing, high energy professional video."""

operation = client.models.generate_videos(
    model="veo-3.1-generate-preview",
    prompt=prompt,
    config=types.GenerateVideosConfig(
      aspect_ratio="9:16",
    ),
)

# Poll the operation status until the video is ready.
while not operation.done:
    print("Waiting for video generation to complete...")
    time.sleep(10)
    operation = client.operations.get(operation)

# Download the generated video.
generated_video = operation.response.generated_videos[0]
client.files.download(file=generated_video.video)
generated_video.video.save("pizza_making.mp4")
print("Generated video saved to pizza_making.mp4")

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const prompt = `A montage of pizza making: a chef tossing and flattening the floury dough, ladling rich red tomato sauce in a spiral, sprinkling mozzarella cheese and pepperoni, and a final shot of the bubbling golden-brown pizza, upbeat electronic music with a rhythmical beat is playing, high energy professional video.`;

let operation = await ai.models.generateVideos({
    model: "veo-3.1-generate-preview",
    prompt: prompt,
    config: {
      aspectRatio: "9:16",
    },
});

// Poll the operation status until the video is ready.
while (!operation.done) {
    console.log("Waiting for video generation to complete...")
    await new Promise((resolve) => setTimeout(resolve, 10000));
    operation = await ai.operations.getVideosOperation({
        operation: operation,
    });
}

// Download the generated video.
ai.files.download({
    file: operation.response.generatedVideos[0].video,
    downloadPath: "pizza_making.mp4",
});
console.log(`Generated video saved to pizza_making.mp4`);

package main

import (
    "context"
    "log"
    "os"
    "time"

    "google.golang.org/genai"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    prompt := `A montage of pizza making: a chef tossing and flattening the floury dough, ladling rich red tomato sauce in a spiral, sprinkling mozzarella cheese and pepperoni, and a final shot of the bubbling golden-brown pizza, upbeat electronic music with a rhythmical beat is playing, high energy professional video.`

  videoConfig := &genai.GenerateVideosConfig{
      AspectRatio: "9:16",
  }

    operation, _ := client.Models.GenerateVideos(
        ctx,
        "veo-3.1-generate-preview",
        prompt,
        nil,
        videoConfig,
    )

    // Poll the operation status until the video is ready.
    for !operation.Done {
    log.Println("Waiting for video generation to complete...")
        time.Sleep(10 * time.Second)
        operation, _ = client.Operations.GetVideosOperation(ctx, operation, nil)
    }

    // Download the generated video.
    video := operation.Response.GeneratedVideos[0]
    client.Files.Download(ctx, video.Video, nil)
    fname := "pizza_making.mp4"
    _ = os.WriteFile(fname, video.Video.VideoBytes, 0644)
    log.Printf("Generated video saved to %s
", fname)
}

# Note: This script uses jq to parse the JSON response.
# GEMINI API Base URL
BASE_URL="https://generativelanguage.googleapis.com/v1beta"

# Send request to generate video and capture the operation name into a variable.
operation_name=$(curl -s "${BASE_URL}/models/veo-3.1-generate-preview:predictLongRunning" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -X "POST" \
  -d '{
    "instances": [{
        "prompt": "A montage of pizza making: a chef tossing and flattening the floury dough, ladling rich red tomato sauce in a spiral, sprinkling mozzarella cheese and pepperoni, and a final shot of the bubbling golden-brown pizza, upbeat electronic music with a rhythmical beat is playing, high energy professional video."
      }
    ],
    "parameters": {
      "aspectRatio": "9:16"
    }
  }' | jq -r .name)

# Poll the operation status until the video is ready
while true; do
  # Get the full JSON status and store it in a variable.
  status_response=$(curl -s -H "x-goog-api-key: $GEMINI_API_KEY" "${BASE_URL}/${operation_name}")

  # Check the "done" field from the JSON stored in the variable.
  is_done=$(echo "${status_response}" | jq .done)

  if [ "${is_done}" = "true" ]; then
    # Extract the download URI from the final response.
    video_uri=$(echo "${status_response}" | jq -r '.response.generateVideoResponse.generatedSamples[0].video.uri')
    echo "Downloading video from: ${video_uri}"

    # Download the video using the URI and API key and follow redirects.
    curl -L -o pizza_making.mp4 -H "x-goog-api-key: $GEMINI_API_KEY" "${video_uri}"
    break
  fi
  # Wait for 5 seconds before checking again.
  sleep 10
done

Control the resolution

Veo 3.1 can also directly generate 720p, 1080p or 4k videos.

Note that the higher the resolution, the higher the latency will be. 4k videos are also more pricey (cf. pricing).

Video extension is also limited to 720p videos.

import time
from google import genai
from google.genai import types

client = genai.Client()

prompt = """A stunning drone view of the Grand Canyon during a flamboyant sunset that highlights the canyon's colors. The drone slowly flies towards the sun then accelerates, dives and flies inside the canyon."""

operation = client.models.generate_videos(
    model="veo-3.1-generate-preview",
    prompt=prompt,
    config=types.GenerateVideosConfig(
      resolution="4k",
    ),
)

# Poll the operation status until the video is ready.
while not operation.done:
    print("Waiting for video generation to complete...")
    time.sleep(10)
    operation = client.operations.get(operation)

# Download the generated video.
generated_video = operation.response.generated_videos[0]
client.files.download(file=generated_video.video)
generated_video.video.save("4k_grand_canyon.mp4")
print("Generated video saved to 4k_grand_canyon.mp4")

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const prompt = `A stunning drone view of the Grand Canyon during a flamboyant sunset that highlights the canyon's colors. The drone slowly flies towards the sun then accelerates, dives and flies inside the canyon.`;

let operation = await ai.models.generateVideos({
    model: "veo-3.1-generate-preview",
    prompt: prompt,
    config: {
      resolution: "4k",
    },
});

// Poll the operation status until the video is ready.
while (!operation.done) {
    console.log("Waiting for video generation to complete...")
    await new Promise((resolve) => setTimeout(resolve, 10000));
    operation = await ai.operations.getVideosOperation({
        operation: operation,
    });
}

// Download the generated video.
ai.files.download({
    file: operation.response.generatedVideos[0].video,
    downloadPath: "4k_grand_canyon.mp4",
});
console.log(`Generated video saved to 4k_grand_canyon.mp4`);

package main

import (
    "context"
    "log"
    "os"
    "time"

    "google.golang.org/genai"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }

    prompt := `A stunning drone view of the Grand Canyon during a flamboyant sunset that highlights the canyon's colors. The drone slowly flies towards the sun then accelerates, dives and flies inside the canyon.`

  videoConfig := &genai.GenerateVideosConfig{
      Resolution: "4k",
  }

    operation, _ := client.Models.GenerateVideos(
        ctx,
        "veo-3.1-generate-preview",
        prompt,
        nil,
        videoConfig,
    )

    // Poll the operation status until the video is ready.
    for !operation.Done {
    log.Println("Waiting for video generation to complete...")
        time.Sleep(10 * time.Second)
        operation, _ = client.