LTX-2 Pro
LTX-2 Pro is a cinematic video model by Lightricks. It supports text prompts and image inputs. It outputs high resolution clips with realistic motion and precise lighting. It targets professional workflows that need stable pacing, detailed subjects, and synchronized audio.
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 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: lightricks:2@0 -
Identifier of the model to use for generation.
Learn more 3 resources
-
positivePrompt
string required min: 2 max: 10000 -
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
float default: 6 -
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 3 values
-
fps
integer default: 25 -
Frames per second for video generation. Higher values create smoother motion but require more processing time.
Allowed values 2 values
Provider Settings
Parameters specific to this model provider. These must be nested inside the providerSettings.lightricks object.
providerSettings.lightricks object.-
providerSettings»lightricks»generateAudiogenerateAudio
boolean default: false -
Generate synchronized audio.
Rain-Slick Neon Alleyway Portrait
{
"taskType": "videoInference",
"taskUUID": "e8147fa8-025b-45f4-a1c3-55020aa1442d",
"model": "lightricks:2@0",
"positivePrompt": "Using the provided first frame as the exact opening composition, create a cinematic rainy-night sequence in a futuristic alley. The camera begins close on the musician beneath a transparent umbrella, then performs a slow subtle dolly with gentle handheld realism. Raindrops ripple in puddles, steam curls from street vents, neon reflections shimmer across the pavement, and holographic signs flicker softly in magenta and teal. The subject remains consistent and photorealistic, with natural micro-movements in posture, blinking, breath, and coat fabric reacting to the damp breeze. A few pedestrians pass as soft silhouettes in the deep background, preserving focus on the main figure. Emphasize precise lighting, stable pacing, realistic wet-surface physics, rich atmospheric depth, and premium filmic contrast. Generate synchronized ambient city audio with rain, distant traffic hum, soft electrical buzz, and faint footsteps.",
"width": 1920,
"height": 1080,
"duration": 8,
"fps": 25,
"providerSettings": {
"lightricks": {
"generateAudio": true
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/f4c0789f-eee2-407f-9145-110c82609f19.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "e8147fa8-025b-45f4-a1c3-55020aa1442d",
"videoUUID": "41761ba1-6292-4570-aef2-4ed3e7ce3bed",
"videoURL": "https://vm.runware.ai/video/os/a21d05/ws/5/vi/41761ba1-6292-4570-aef2-4ed3e7ce3bed.mp4",
"cost": 0.48
}Moonlit Monastery Cliffside Procession
{
"taskType": "videoInference",
"taskUUID": "2804a65f-6622-4c53-aca4-bd631680ed53",
"model": "lightricks:2@0",
"positivePrompt": "A solemn torchlit procession of saffron-robed monks winding along a narrow cliffside path toward an ancient mountain monastery under a giant moon, sheer rock walls on one side and a mist-filled abyss on the other, banners fluttering in cold alpine wind, drifting incense smoke, warm firelight contrasting with silver moonlight, cinematic wide establishing shot that slowly glides forward and slightly upward, realistic fabric movement, precise footsteps, subtle faces illuminated by lantern glow, prayer wheels turning, distant waterfalls vanishing into fog, ultra-detailed stone carvings, volumetric night mist, polished professional cinematography, natural pacing, grounded realism, serene spiritual atmosphere, high dynamic range, synchronized ambient audio of wind, bells, footsteps on stone, soft chanting, and crackling torches",
"width": 3840,
"height": 2160,
"duration": 8,
"fps": 25,
"providerSettings": {
"lightricks": {
"generateAudio": true
}
}
}{
"taskType": "videoInference",
"taskUUID": "2804a65f-6622-4c53-aca4-bd631680ed53",
"videoUUID": "20417af1-9d69-414b-ad89-424ddea60442",
"videoURL": "https://vm.runware.ai/video/os/a23d05/ws/5/vi/20417af1-9d69-414b-ad89-424ddea60442.mp4",
"cost": 1.92
}Moonlit Bioluminescent Cliff Shrine
{
"taskType": "videoInference",
"taskUUID": "81c6d9e9-60fd-40ed-b6a6-fffbd534d476",
"model": "lightricks:2@0",
"positivePrompt": "Using the provided first frame as the opening shot, create a cinematic night sequence of a secluded shrine on a rugged sea cliff. The camera begins with a slow forward drift and slight parallax around the lantern-bearing traveler, while moonlight catches the shrine roof, wet stone, and wind-tossed grasses. Bioluminescent flowers pulse softly in clusters, fog rolls along the cliff edge, and waves crash far below with occasional spray. Thin clouds slide across the moon, casting shifting silver light and delicate shadows. Preserve the composition and subject identity from the frame image while adding realistic environmental motion, subtle cloth movement, gentle lantern flicker, and polished filmic pacing. Naturalistic textures, high dynamic range, precise lighting, immersive ambience, premium cinematic realism.",
"width": 1920,
"height": 1080,
"duration": 8,
"fps": 25,
"providerSettings": {
"lightricks": {
"generateAudio": true
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/085e3f32-4bb6-445a-9e45-309f3d838ae6.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "81c6d9e9-60fd-40ed-b6a6-fffbd534d476",
"videoUUID": "32c216d2-8292-46ce-b520-c9a03aac5606",
"videoURL": "https://vm.runware.ai/video/os/a15d18/ws/5/vi/32c216d2-8292-46ce-b520-c9a03aac5606.mp4",
"cost": 0.48
}Stormlit Coastal Observatory Nightfall
{
"taskType": "videoInference",
"taskUUID": "6ebc0df3-e55c-4905-baef-7fa6407d6b6e",
"model": "lightricks:2@0",
"positivePrompt": "A cinematic ultra-detailed nighttime scene on a remote cliffside observatory above a turbulent sea, moments before a summer storm breaks. A lone glass-domed research station glows warm amber against deep cobalt sky, wet stone paths reflecting rotating beacon lights, wind-tossed grasses bending in gusts, distant waves crashing into black rocks below. The camera begins with a slow wide aerial drift toward the observatory, then gently lowers to reveal rain beginning to speckle the lens and windows, subtle lightning flickering inside dense storm clouds on the horizon. Realistic motion, natural pacing, precise reflections on wet surfaces, volumetric mist, layered cloud movement, believable ocean dynamics, tasteful cinematic contrast, atmospheric depth, premium live-action look, no text, no logos. Synchronized environmental audio: wind, low thunder, surf, faint metallic rattles from antenna equipment.",
"width": 3840,
"height": 2160,
"duration": 8,
"fps": 25,
"providerSettings": {
"lightricks": {
"generateAudio": true
}
}
}{
"taskType": "videoInference",
"taskUUID": "6ebc0df3-e55c-4905-baef-7fa6407d6b6e",
"videoUUID": "55c20e05-7c6d-415e-aea9-47ace761161d",
"videoURL": "https://vm.runware.ai/video/os/a05d22/ws/5/vi/55c20e05-7c6d-415e-aea9-47ace761161d.mp4",
"cost": 1.92
}