LTX-2.3 is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model, with improved audio and visual quality as well as enhanced prompt adherence. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.1per run·~10 / $1
ExamplesView all
A wide aerial shot slowly drifts over a dense rainforest at golden hour. Thick mist rises from the canopy as shafts of warm orange light pierce through the trees. A winding river reflects the fading sky below. The camera tilts down gradually, revealing a waterfall cascading into a dark green pool. Ambient sounds of water and distant birds fill the scene.
A street-level tracking shot moves through a rain-soaked Tokyo alley at night. Neon signs in red and blue reflect off the wet pavement. People walk past with umbrellas, faces partially lit by shop windows. Steam rises from a ramen stall on the left. The camera drifts forward at a slow, steady pace, passing lanterns swaying gently in the wind.
A medium shot of a young woman in a flowing white dress standing on a cliff overlooking the ocean. Strong wind blows her hair and dress sideways. She slowly raises both arms outward, closes her eyes, and tilts her face upward toward the overcast sky. The camera slowly circles her from left to right. Waves crash loudly against the rocks far below.
A cinematic wide shot of a massive spacecraft descending through thick storm clouds over a futuristic city at night. Lightning flashes illuminate the underbelly of the ship as it breaks through the clouds. City lights stretch across the horizon below. The camera holds still as the ship passes directly overhead, its engines roaring, displacement wind bending the clouds outward.
Related Models
README
LTX-2.3 Text-to-Video
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?
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Improved quality Enhanced audio and visual quality compared to LTX-2, with better prompt adherence and more coherent outputs.
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Synchronized audio-video Generates video with matching audio in a single model pass, no separate audio production needed.
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DiT-based architecture Built on Diffusion Transformer technology for high-fidelity, temporally consistent video generation.
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Flexible resolution Supports 480p, 720p, and 1080p outputs to balance quality and cost.
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Variable duration Generate clips from 5 to 20 seconds.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the video scene, motion, and audio |
| resolution | No | Output resolution: 480p, 720p (default), or 1080p |
| duration | No | Video length in seconds (5-20) |
| seed | No | Random seed for reproducibility (-1 for random) |
Resolution Options
| Resolution | Best For |
|---|---|
| 480p | Fast previews, iteration, lowest cost |
| 720p | Balanced quality and cost (default) |
| 1080p | Final delivery, maximum detail |
How to Use
- Write your prompt — describe the scene, motion, camera movement, and audio cues.
- Select resolution — 480p for iteration, 720p for balance, 1080p for final output.
- Set duration — 5-20 seconds based on your content needs.
- Run — submit and download the video with synchronized audio.
Pricing
| Resolution | 5s | 10s | 15s | 20s |
|---|---|---|---|---|
| 480p | $0.10 | $0.20 | $0.30 | $0.40 |
| 720p | $0.15 | $0.30 | $0.45 | $0.60 |
| 1080p | $0.20 | $0.40 | $0.60 | $0.80 |
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.
Related Models
- LTX-2.3 Image-to-Video — Animate images with synchronized audio.
- LTX-2 19B Text-to-Video — Previous generation model.
Ltx 2.3 Text To Video API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2.3/text-to-video with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Ltx 2.3 Text To Video below.
HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2.3/text-to-video" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"aspect_ratio": "16:9",
"duration": 5,
"seed": -1
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].Node.js example
// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/ltx-2.3/text-to-video", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"aspect_ratio": "16:9",
"duration": 5,
"seed": -1
});
console.log(result.outputs[0]); // → URL of the generated outputPython example
# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/ltx-2.3/text-to-video",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"aspect_ratio": "16:9",
"duration": 5,
"seed": -1
}
)
print(output["outputs"][0]) # → URL of the generated outputLtx 2.3 Text To Video API — Frequently asked questions
What is the Ltx 2.3 Text To Video API?
Ltx 2.3 Text To Video is a WaveSpeedAI model for video generation, exposed as a REST API on WaveSpeedAI. LTX-2.3 is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model, with improved audio and visual quality as well as enhanced prompt adherence. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
How do I call the Ltx 2.3 Text To Video API?
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/ltx-2.3-text-to-video.
How much does Ltx 2.3 Text To Video cost per run?
Ltx 2.3 Text To Video starts at $0.10 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
What inputs does Ltx 2.3 Text To Video accept?
Key inputs: `prompt`, `aspect_ratio`, `resolution`, `duration`, `seed`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/ltx-2.3-text-to-video.
How do I get started with the Ltx 2.3 Text To Video API?
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
Can I use Ltx 2.3 Text To Video outputs commercially?
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.