Runway Gen-4 Turbo
Runway Gen-4 Turbo is a high speed variant of Gen-4 for rapid video ideation. It turns reference images into short cinematic clips with strong character consistency, smooth motion, and reduced credit cost. Ideal for fast iteration in production and previsualization pipelines.
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»frameImagesframeImages
array of strings or objects required items: 1 -
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.
Examples 2 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."frameImages": [ { "image": "aac49721-1964-481a-ae78-8a4e29b91402", "frame": "first" } ]Format 1: string[]
-
Image input (UUID, URL, Data URI, or Base64).
Format 2: object[] 2 properties
Generation Parameters
Core parameters for controlling the generated content.
-
model
string required value: runway:1@1 -
Identifier of the model to use for generation.
Learn more 3 resources
-
positivePrompt
string min: 1 max: 1000 -
Text prompt describing elements to include in the generated output.
Learn more 2 resources
-
width
integer paired with height -
Width of the generated media in pixels.
Learn more 2 resources
-
height
integer paired with width -
Height of the generated media in pixels.
Learn more 2 resources
-
duration
integer min: 2 max: 10 default: 10 -
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).
-
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.runway object.
providerSettings.runway object.-
providerSettings»runway»contentModerationcontentModeration
object -
Content moderation settings.
Properties 1 property
-
providerSettings»runway»contentModeration»publicFigureThresholdpublicFigureThreshold
string default: auto -
Public figure filtering strictness.
Allowed values 2 values
- Automatic filtering.
- Less strict filtering.
-
Iridescent Ice Cavern Pilgrims
{
"taskType": "videoInference",
"taskUUID": "eed2b1cd-1b23-48c7-a7bd-9afd6d0eb138",
"model": "runway:1@1",
"positivePrompt": "Animate the frozen cavern expedition with graceful cinematic motion: the camera slowly pushes forward along the ridge, loose snow skitters across the ice, flare smoke curls upward, banners ripple in the cold draft, tiny falling ice crystals catch the light, reflections shimmer across the floor, distant haze shifts softly, the travelers keep clear silhouette consistency, epic fantasy realism, atmospheric and immersive",
"width": 1280,
"height": 720,
"duration": 6,
"seed": 29718,
"providerSettings": {
"runway": {
"contentModeration": {
"publicFigureThreshold": "auto"
}
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/74a07e18-7e80-43f7-8e7e-e049af826c39.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "eed2b1cd-1b23-48c7-a7bd-9afd6d0eb138",
"videoUUID": "bd3f7acf-6f35-488a-a12c-48c90203b62c",
"videoURL": "https://vm.runware.ai/video/os/a04d20/ws/5/vi/bd3f7acf-6f35-488a-a12c-48c90203b62c.mp4",
"seed": 29718,
"cost": 0.3042
}Glasshouse Astronomer Tea Ritual
{
"taskType": "videoInference",
"taskUUID": "c77984bd-b060-46d3-9934-2cc26a3e1efd",
"model": "runway:1@1",
"positivePrompt": "Animate the reference image into a short cinematic shot. The astronomer remains seated and consistent in appearance while slowly turning their head toward the glass ceiling, blinking once, and making a small thoughtful motion with the teacup. Steam curls upward in delicate ribbons. Fern leaves sway softly as if stirred by a warm breeze. Sunlight shifts across the glasshouse, sending moving reflections over brass instruments and star charts. Dust motes drift through the beams. Add a gentle push-in camera move with subtle parallax and calm, refined motion throughout. Whimsical, scholarly, luminous, tactile realism.",
"width": 1104,
"height": 832,
"duration": 6,
"seed": 6390,
"providerSettings": {
"runway": {
"contentModeration": {
"publicFigureThreshold": "auto"
}
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/d772dba3-5ce1-496c-acb0-0bdb13dbd9e0.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "c77984bd-b060-46d3-9934-2cc26a3e1efd",
"videoUUID": "3dcbd1d5-f11b-4de5-8a05-46e8303c3ee8",
"videoURL": "https://vm.runware.ai/video/os/a08dlim3/ws/5/vi/3dcbd1d5-f11b-4de5-8a05-46e8303c3ee8.mp4",
"seed": 6390,
"cost": 0.3042
}Wind-Tossed Lighthouse Keeper Rooftop
{
"taskType": "videoInference",
"taskUUID": "857afef8-ce75-497e-9e38-8434d66e7121",
"model": "runway:1@1",
"positivePrompt": "A cinematic shot of a solitary lighthouse keeper on a rugged rooftop above a remote island beacon station, the camera easing forward as fierce wind drives motion through every detail: coat tails thrashing, laundry lines snapping, loose ropes twitching, gulls banking overhead, sea spray rising from below, clouds racing across a cold slate sky. Preserve the keeper's appearance faithfully from the reference image while adding natural body balance, subtle breathing, blinking, and a steady grip on a brass signal lamp. Emphasize realistic environmental animation, rich maritime textures, dramatic atmosphere, and grounded live-action cinematography.",
"width": 1280,
"height": 720,
"duration": 6,
"seed": 38621,
"providerSettings": {
"runway": {
"contentModeration": {
"publicFigureThreshold": "auto"
}
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/9196de33-4f64-4928-9f52-ac6bf0a03572.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "857afef8-ce75-497e-9e38-8434d66e7121",
"videoUUID": "ac69c59a-6038-4c95-8b89-27b170bbf429",
"videoURL": "https://vm.runware.ai/video/os/a10dlim3/ws/5/vi/ac69c59a-6038-4c95-8b89-27b170bbf429.mp4",
"seed": 38621,
"cost": 0.3042
}Lantern Archivist Canal Skiff
{
"taskType": "videoInference",
"taskUUID": "d03955f1-d66b-48e2-8dea-94916fee0dd6",
"model": "runway:1@1",
"positivePrompt": "The archivist steadies on the skiff as the canal gently carries the boat forward, lanterns swinging softly overhead, reflections shivering across the water, loose parchment edges fluttering in the breeze, ivy stirring along old stone walls, subtle dawn mist shifting under the bridges, cinematic camera drift with natural parallax, richly detailed fantasy atmosphere, smooth realistic motion, strong subject consistency, elegant lighting",
"width": 1280,
"height": 720,
"duration": 6,
"seed": 8192,
"providerSettings": {
"runway": {
"contentModeration": {
"publicFigureThreshold": "auto"
}
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/11068c61-4329-406a-ab7f-2be746b8bfdb.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "d03955f1-d66b-48e2-8dea-94916fee0dd6",
"videoUUID": "5e10044c-6729-4df9-980e-41f810e72882",
"videoURL": "https://vm.runware.ai/video/os/a02d21/ws/5/vi/5e10044c-6729-4df9-980e-41f810e72882.mp4",
"seed": 8192,
"cost": 0.3042
}Aerial Tram Through Stormglass Gorge
{
"taskType": "videoInference",
"taskUUID": "f1287a5a-fe34-4cbd-b110-ad7c312e49fb",
"model": "runway:1@1",
"positivePrompt": "A retro-futurist aerial tram glides into a vast storm-carved gorge of translucent mineral spires and fractured crystal walls. The shot begins with the tram entering frame, cables humming, mist peeling away from the canyon as wind pushes through the ravine. Subtle camera drift and forward motion create a thrilling sense of travel. Reflections slide across the tram windows, distant waterfalls shimmer through haze, loose droplets and fine debris streak past the lens, and the crystalline surfaces catch cold flashes of light from breaks in the clouds. Cinematic realism, strong environmental depth, coherent design details, smooth motion, atmospheric parallax, polished previsualization style.",
"width": 1584,
"height": 672,
"duration": 8,
"seed": 97753,
"providerSettings": {
"runway": {
"contentModeration": {
"publicFigureThreshold": "auto"
}
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/2c7bc4ab-13b9-4ad8-a90e-d2a2e3325b94.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "f1287a5a-fe34-4cbd-b110-ad7c312e49fb",
"videoUUID": "31bc7a99-895b-411c-b1e9-e9df24bb578f",
"videoURL": "https://vm.runware.ai/video/os/a02d21/ws/5/vi/31bc7a99-895b-411c-b1e9-e9df24bb578f.mp4",
"seed": 97753,
"cost": 0.4042
}