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Ltx 2.3 Text To Video LoRA

Ltx 2.3 Text To Video LoRA

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LTX-2.3 with LoRA support is a DiT-based audio-video foundation model designed to generate synchronized video and audio with custom styles, motion, or likeness training. Improved audio and visual quality with enhanced prompt adherence. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

LTX-2.3 Text-to-Video LoRA

LTX-2.3 is a significant update to the LTX-2 model, featuring improved audio and visual quality with enhanced prompt adherence. As a DiT-based (Diffusion Transformer) audio-video foundation model, it generates synchronized video and audio from text prompts in a single pass, bringing together the core building blocks of modern video generation with open weights and practical execution.


Why Choose This?

  • Improved quality Enhanced audio and visual quality compared to LTX-2, with better prompt adherence and more coherent outputs.

  • Synchronized audio-video Generates video with matching audio in a single model pass, no separate audio production needed.

  • DiT-based architecture Built on Diffusion Transformer technology for high-fidelity, temporally consistent video generation.

  • Flexible resolution Supports 480p, 720p, and 1080p outputs to balance quality and cost.

  • Variable duration Generate clips from 5 to 20 seconds.


Parameters

ParameterRequiredDescription
lorasNoList of LoRA models to apply (max 3, each with path and scale)
promptYesText description of the video scene, motion, and audio
resolutionNoOutput resolution: 480p, 720p (default), or 1080p
durationNoVideo length in seconds (5-20)
seedNoRandom seed for reproducibility (-1 for random)

Resolution Options

ResolutionBest For
480pFast previews, iteration, lowest cost
720pBalanced quality and cost (default)
1080pFinal delivery, maximum detail

How to Use

  1. Write your prompt — describe the scene, motion, camera movement, and audio cues.
  2. Select resolution — 480p for iteration, 720p for balance, 1080p for final output.
  3. Set duration — 5-20 seconds based on your content needs.
  4. Run — submit and download the video with synchronized audio.

Pricing

Resolution5s10s15s20s
480p$0.15$0.30$0.45$0.60
720p$0.20$0.40$0.60$0.80
1080p$0.25$0.50$0.75$1.00

Best Use Cases

  • Content Creation — Generate video content with synchronized audio from text descriptions.
  • Social Media — Create engaging video posts with cohesive sound.
  • Marketing — Produce video ads with matching audio from creative briefs.
  • Storytelling — Bring written narratives to life with video and audio.
  • Prototyping — Quickly visualize concepts with audio-visual output.

Pro Tips

  • Audio is automatic — sound is generated based on visual content and prompt context.
  • Describe specific audio when needed (e.g., “rain”, “jazz”, “crowd noise”).
  • Keep prompts clear and specific for better prompt adherence.
  • Iterate at 480p to dial in content, then render at higher resolution for final output.
  • Use fixed seed when comparing prompt variations to isolate changes.

Notes

  • Maximum video duration is 20 seconds.
  • Width & height must be divisible by 32, frame count must be divisible by 8 + 1.
  • For longer content, generate multiple clips and edit together.
  • Model is not intended to provide factual information.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2.3/text-to-video-lora" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "duration": 5,
    "seed": -1
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
resolutionstringNo720p480p, 720p, 1080pVideo resolution.
aspect_ratiostringNo16:916:9, 9:16Aspect ratio of the video.
durationintegerNo55 ~ 20The duration of the generated media in seconds.
lorasarrayNomax 3 itemsList of LoRAs to apply (max 3).
loras[].pathstringYes-Path to the LoRA model
loras[].scalefloatYes-0.0 ~ 4.0Scale of the LoRA model
seedintegerNo-1-1 ~ 2147483647The random seed to use for the generation. -1 means a random seed will be used.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray of URLs to the generated content (empty when status is not completed).
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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