Veo 3.1
Veo 3.1 is a cinematic video generation model for developers. It turns text prompts or reference images into high fidelity scenes with richer native audio, better prompt adherence, and granular shot control. Use it for story driven clips with smoother motion and consistent style.
API Options
Platform-level options for task execution and delivery.
-
taskType
string required value: videoInference -
Identifier for the type of task being performed
-
taskUUID
string required UUID v4 -
UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.
-
outputType
string default: URL -
Video output type.
Allowed values 1 value
-
outputFormat
string default: MP4 -
Specifies the file format of the generated output. The available values depend on the task type and the specific model's capabilities.
- `MP4`: Widely supported video container (H.264), recommended for general use.
- `WEBM`: Optimized for web delivery.
- `MOV`: QuickTime format, common in professional workflows (Apple ecosystem).
Allowed values 3 values
-
outputQuality
integer min: 20 max: 99 default: 95 -
Compression quality of the output. Higher values preserve quality but increase file size.
-
webhookURL
string URI -
Specifies a webhook URL where JSON responses will be sent via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available.
Learn more 1 resource
- Webhooks PLATFORM
- Webhooks
-
deliveryMethod
string default: async -
Determines how the API delivers task results.
Allowed values 1 value
- Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse. Required for long-running tasks like video generation.
Learn more 1 resource
- Task Polling PLATFORM
-
uploadEndpoint
string URI -
Specifies a URL where the generated content will be automatically uploaded using the HTTP PUT method. The raw binary data of the media file is sent directly as the request body. For secure uploads to cloud storage, use presigned URLs that include temporary authentication credentials.
Common use cases:
- Cloud storage: Upload directly to S3 buckets, Google Cloud Storage, or Azure Blob Storage using presigned URLs.
- CDN integration: Upload to content delivery networks for immediate distribution.
// S3 presigned URL for secure upload https://your-bucket.s3.amazonaws.com/generated/content.mp4?X-Amz-Signature=abc123&X-Amz-Expires=3600 // Google Cloud Storage presigned URL https://storage.googleapis.com/your-bucket/content.jpg?X-Goog-Signature=xyz789 // Custom storage endpoint https://storage.example.com/uploads/generated-image.jpgThe content data will be sent as the request body to the specified URL when generation is complete.
-
safety
object -
Content safety checking configuration for video generation.
Properties 2 properties
-
safety»checkContentcheckContent
boolean default: false -
Enable or disable content safety checking. When enabled, defaults to
fastmode.
-
safety»modemode
string default: none -
Safety checking mode for video generation.
Allowed values 3 values
- Disables checking.
- Checks key frames.
- Checks all frames.
-
-
ttl
integer min: 60 -
Time-to-live (TTL) in seconds for generated content. Only applies when
outputTypeisURL.
-
includeCost
boolean default: false -
Include task cost in the response.
-
numberResults
integer min: 1 max: 4 default: 1 -
Number of results to generate. Each result uses a different seed, producing variations of the same parameters.
Inputs
Input resources for the task (images, audio, etc). These must be nested inside the inputs object.
inputs object.-
inputs»referenceImagesreferenceImages
array of strings min items: 1max items: 3 -
Images to use as a reference for the generation (UUID, URL, Data URI, or Base64). Up to 3 asset images or 1 style image. Asset and style images cannot be mixed.
-
inputs»frameImagesframeImages
array of strings or objects min items: 1max items: 2 -
An array of frame-specific image inputs to guide video generation. Each item can be either a plain image input (UUID, URL, Data URI, or Base64) or an object that pairs an image with a target frame position.
The
frameImagesparameter allows you to constrain specific frames within the video sequence, ensuring that particular visual content appears at designated points. This is different fromreferenceImages, which provide overall visual guidance without constraining specific timeline positions.When the
frameparameter is omitted, automatic distribution rules apply:- 1 image: Used as the first frame.
- 2 images: First and last frames.
Examples 3 examples
Shorthand format: When you don't need to specify a frame position, you can pass a plain image input directly.
"frameImages": [ "aac49721-1964-481a-ae78-8a4e29b91402" ]Object format: When you need to specify a frame position, use an object with
imageandframe.First and last frames: With two images, they automatically become the first and last frames of the video sequence. You can mix shorthand and object formats."frameImages": [ { "image": "aac49721-1964-481a-ae78-8a4e29b91402", "frame": "first" } ]"frameImages": [ "aac49721-1964-481a-ae78-8a4e29b91402", { "image": "3ad204c3-a9de-4963-8a1a-c3911e3afafe", "frame": "last" } ]Format 1: string[]
-
Image input (UUID, URL, Data URI, or Base64).
Format 2: object[] 2 properties
-
inputs»frameImages»imageimage
string required -
Image input (UUID, URL, Data URI, or Base64).
-
inputs»frameImages»frameframe
object -
Target frame position for the image. Supports first and last frame.
Allowed values 4 values
- First frame of the video.
- Last frame of the video.
- Frame index 0 (first frame).
- Frame index -1 (last frame).
-
inputs»videovideo
string -
Video to extend (UUID or URL).
Generation Parameters
Core parameters for controlling the generated content.
-
model
string required value: google:3@2 -
Identifier of the model to use for generation.
Learn more 3 resources
-
positivePrompt
string required min: 2 max: 3000 -
Text prompt describing elements to include in the generated output.
Learn more 2 resources
-
Width of the generated media in pixels.
Learn more 2 resources
-
Height of the generated media in pixels.
Learn more 2 resources
-
resolution
string -
Resolution preset for the output. When used with input media, automatically matches the aspect ratio from the input.
Allowed values 3 values
-
duration
float default: 8 -
Length of the generated video in seconds. The total number of frames produced is determined by duration multiplied by the model's frame rate (fps).
Allowed values 2 values
-
seed
integer min: 0 max: 4294967295 -
Random seed for reproducible generation. When not provided, a random seed is generated in the unsigned 32-bit range.
Provider Settings
Parameters specific to this model provider. These must be nested inside the providerSettings.google object.
providerSettings.google object.-
providerSettings»google»enhancePromptenhancePrompt
boolean value: true -
Enable automatic prompt enhancement. Affects reproducibility. Always active for Veo 3.1.
-
providerSettings»google»generateAudiogenerateAudio
boolean default: true -
Generate video with synchronized audio including ambient sounds and music.
-
providerSettings»google»resizeModeresizeMode
string -
Resize mode for the input media.
Allowed values 2 values
Bioluminescent Cliffside Lighthouse Twilight
{
"taskType": "videoInference",
"taskUUID": "f212d8ca-ed2d-43f8-9ca5-00f725c866bb",
"model": "google:3@2",
"positivePrompt": "A cinematic 8-second evolution between two anchored frames: begin at a tranquil cliffside lighthouse at twilight with glowing bioluminescent flowers and tide pools, then gradually transform into a stormy midnight seascape while preserving the same location, composition, and lighthouse identity. The camera performs a subtle slow push-in from a wide shot. Wind rises through the grass, fog thickens, waves become rougher, the lighthouse beacon starts rotating, seabirds disappear, clouds gather, rain begins lightly and intensifies, and a distant lightning flash reveals dramatic ocean spray near the end. Natural, physically believable motion, rich environmental detail, cohesive continuity between frames, high-fidelity cinematic realism, atmospheric depth, volumetric mist, dynamic water simulation, synchronized ambient audio with ocean surf, wind, faint gulls at the start, then thunder, rain, and the lighthouse horn in the final moments.",
"width": 1920,
"height": 1080,
"duration": 8,
"seed": 21150,
"providerSettings": {
"google": {
"enhancePrompt": true,
"generateAudio": true
}
},
"inputs": {
"frameImages": [
{
"inputImage": "https://assets.runware.ai/assets/inputs/17246021-8303-4a4c-8a50-6c14f28d1162.jpg",
"frame": "first"
},
{
"inputImage": "https://assets.runware.ai/assets/inputs/dad0315b-c7b4-41b4-aeea-014069121823.jpg",
"frame": "last"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "f212d8ca-ed2d-43f8-9ca5-00f725c866bb",
"videoUUID": "43fb21c7-2c81-4dfe-9ea1-b22222ee06c6",
"videoURL": "https://vm.runware.ai/video/os/a18d05/ws/5/vi/43fb21c7-2c81-4dfe-9ea1-b22222ee06c6.mp4",
"seed": 21150,
"cost": 3.2
}Moonlit Desert Train Platform
{
"taskType": "videoInference",
"taskUUID": "5c2130bb-19f0-48fd-8d99-1d7b1da9d508",
"model": "google:3@2",
"positivePrompt": "Begin from the provided first frame image. A cinematic nighttime scene at a remote desert train platform beneath an enormous moon. The camera slowly pushes forward along the platform as warm station lamps flicker in the wind, fine sand skims across the ground, the sleeper train hums softly, and distant lightning flashes inside towering clouds on the horizon. A lone traveler in a pale coat steps into frame near the carriage door, fabric moving in the breeze. Rich contrast, realistic textures, elegant shot continuity from the input frame, subtle atmospheric depth, premium film look, immersive ambient night audio with wind, metal creaks, low train engine rumble, and a faint mournful whistle.",
"width": 1920,
"height": 1080,
"duration": 8,
"seed": 3967,
"providerSettings": {
"google": {
"enhancePrompt": true,
"generateAudio": true,
"resizeMode": "crop"
}
},
"inputs": {
"frameImages": [
{
"inputImage": "https://assets.runware.ai/assets/inputs/c5f27ba0-48e9-4d95-b584-c49b1d6cd0d5.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "5c2130bb-19f0-48fd-8d99-1d7b1da9d508",
"videoUUID": "28d61059-f5bd-4df4-bf49-c3747776c06b",
"videoURL": "https://vm.runware.ai/video/os/a05d22/ws/5/vi/28d61059-f5bd-4df4-bf49-c3747776c06b.mp4",
"seed": 3967,
"cost": 3.2
}