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Lightricks modelsvideo generation api

lightricks/ltx-2.3-22b/distilled/text-to-video/lora

Ltx 2.3 22b Distilled Lora by Lightricks - generate cinematic videos from text descriptions with AI. Create high-quality video content with natural motion, camera control, and optional audio generation.

Input
The prompt to generate the video from.
Whether to generate audio for the video.
The seed for the random number generator.
The output type of the generated video. Allowed values: X264 (.mp4), VP9 (.webm), PRORES4444 (.mov), GIF (.gif).
The write mode of the generated video. Allowed values: fast, balanced, small.
01
The scale of the distill LoRA to use for the second and subsequent passes. Range: 0 to 1.
9481
The number of frames to generate. Range: 9 to 481.
Whether to use multi-scale generation. If True, the model will generate the video at a smaller scale first, then use the smaller video to guide the generation of a video at or above your requested size. This results in better coherence and details.
The scheduler to use. Allowed values: ltx2, linear_quadratic, beta.
The LoRAs to use for the generation.
01
The scale of the camera LoRA to use. This allows you to control the camera movement of the generated video more accurately than just prompting the model to move the camera. Range: 0 to 1.
The size of the generated video. Allowed values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9.
160
The frames per second of the generated video. Range: 1 to 60.
The quality of the generated video. Allowed values: low, medium, high, maximum.
The camera LoRA to use. This allows you to control the camera movement of the generated video more accurately than just prompting the model to move the camera. Allowed values: dolly_in, dolly_out, dolly_left, dolly_right, jib_up, jib_down, static, none.
Idle

Example output — click Run to generate your own

API README

LTX-2.3 22B Distilled

LTX-2.3 22B Distilled is a text-to-video creation with custom LoRA adapters endpoint in the LTX 2.3 family. It is built for creators who need to turn a concrete creative brief into a controlled visual sequence: the request establishes the source material, the intended subject behavior, the camera language, and the atmosphere of the finished shot. The distilled, LoRA-enabled route keeps that workflow explicit instead of hiding its input assumptions behind a generic video-generation label.

In practice, this route accepts loras as creative context and exposes num frames, video size, generate audio, camera lora for delivery planning. That makes it suitable for shot-based pipelines where teams must preserve a source, direct a transformation, or control the final format without losing sight of the model's central task. Write prompts as a compact shot plan—subject, action, setting, camera, light, and timing—then use the structured fields for constraints that should remain deterministic across iterations.

Highlights

  • Prompt-to-scene generation. Builds the shot from written direction, including subject action, environment, lighting, lens language, and pacing.
  • Synchronized audio path. Audio conditioning or generation is available in the same request, helping sound and picture share one creative plan.
  • Adapter-based styling. LoRA inputs let teams layer specialized looks or learned concepts onto the base generation path.
  • Directed camera motion. Camera-motion presets provide a repeatable way to ask for dollies, jibs, or a locked shot.

Pricing

Billing unitPrice
Base request$0.001405

When to Use

ScenarioRecommendation
Choose this routeUse it when the deliverable specifically calls for text-to-video creation with custom LoRA adapters, rather than a neighboring generation mode.
Prepare the sourceProvide a precise written brief in the format described by the request schema.
Direct the shotDescribe the subject, action, environment, camera movement, lighting, and temporal progression in that order.
Control continuityUse endpoint frames, reference media, strength, or audio controls when those fields are available instead of burying hard constraints in prose.
Plan deliverySet duration, frame count, resolution, and aspect ratio explicitly when the schema exposes them, then compare iterations with a stable seed where supported.

Prompt Guide

For text-to-video creation with custom LoRA adapters, describe one coherent shot rather than a list of visual keywords. Put the main subject and action first, follow with location and staging, then add camera movement, lens or framing, lighting, mood, and any timed change. Keep URLs and hard delivery choices in their dedicated fields.

{
  "prompt": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain.",
  "generate_audio": true
}

Technical Specs

SpecificationValue
Model IDlightricks/ltx-2.3-22b/distilled/text-to-video/lora
Required inputsprompt
ExecutionAsynchronous generation job
Request controls15 documented fields
Outputurl, content_type

Request fields

FieldType and constraints
fpsnumber; Optional; Range: 1–60; Default: 24
seedinteger; Optional
lorasarray; Optional
promptstring; Required
schedulerstring; Optional; Options: ltx2, linear_quadratic, beta; Default: "ltx2"
num_framesinteger; Optional; Range: 9–481; Default: 121
video_sizestring; Optional; Options: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9; Default: "landscape_16_9"
camera_lorastring; Optional; Options: dolly_in, dolly_out, dolly_left, dolly_right, jib_up, jib_down, static, none; Default: "none"
video_qualitystring; Optional; Options: low, medium, high, maximum; Default: "high"
generate_audioboolean; Optional; Default: true
use_multiscaleboolean; Optional; Default: true
video_write_modestring; Optional; Options: fast, balanced, small; Default: "balanced"
camera_lora_scalenumber; Optional; Range: 0–1; Default: 1
video_output_typestring; Optional; Options: X264 (.mp4), VP9 (.webm), PRORES4444 (.mov), GIF (.gif); Default: "X264 (.mp4)"
distill_lora_second_pass_scalenumber; Optional; Range: 0–1; Default: 0.5

Related Models

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