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.
就绪
$0.1每次运行·~10 / $1
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A side-tracking shot follows a competitive cyclist in a red, white and blue racing kit powering along a wet road at full speed. He is crouched low over the handlebars in an aggressive aero position, legs driving the pedals in a fast, powerful cadence. The camera tracks him at pace from the left, keeping him centered in frame. Trees and guardrails blur into streaks of green and grey behind him. Rain mist rises off the road surface. His jersey ripples in the wind. The sound of spinning wheels, fast breathing, and wet road noise fill the audio. The camera slowly pushes in toward his focused expression as he accelerates.
A medium shot of a male teacher standing in front of a whiteboard in a bright classroom, holding a tablet. He smiles warmly at the students seated before him and begins speaking clearly in English. He gestures with his free hand as he talks, shifting his weight slightly and turning his gaze across the room. Two students are visible from behind in the foreground, listening attentively. The camera holds steady with a slight slow zoom in toward the teacher's face. Classroom ambient sound, natural light from the side.
A medium shot of two cute cartoon bears standing on a grassy clearing in an animated forest. The small white bear on the left looks at the brown bear, opens its arms wide, and waddles forward with short bouncy steps. The brown bear's eyes light up and it opens its arms in response. The two meet in the center and squeeze each other in a big round hug, their chubby bodies pressing together. The white bear buries its face into the brown bear's shoulder. Both sway gently left and right while hugging, tails wagging. Small pink hearts and light sparkles float up around them. The forest background glows warmly. Soft cheerful music and gentle bird sounds fill the scene.
相关模型
README
LTX-2.3 Image-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 animates your input image into a high-fidelity video with synchronized audio generated in a single pass.
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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Image-conditioned video with audio Transforms a static image into a moving video with synchronized audio in a single model pass.
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Preserves input composition Maintains the subject, framing, and lighting of your reference image while adding natural motion.
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DiT-based architecture Built on Diffusion Transformer technology for detailed, 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 |
|---|---|---|
| image | Yes | Reference image to animate (JPG or PNG) |
| prompt | Yes | Text description of motion, action, and audio cues |
| 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
- Upload your image — the reference image that defines subject, composition, and lighting.
- Write your prompt — describe the 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 animated 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
- Product Animation — Bring product photos to life with subtle motion and ambient audio.
- Portrait Animation — Animate headshots and portraits with natural movement.
- Social Media — Create engaging animated content from static images.
- Marketing — Transform key visuals into video ads with cohesive sound.
- Storytelling — Animate storyboard frames or concept art.
Pro Tips
- Audio is automatic — sound is generated based on visual motion and prompt context.
- Describe specific audio when needed (e.g., "rain", "jazz", "crowd noise").
- Use high-quality, sharp, well-exposed images for best results.
- Keep motion prompts simple — one clear action per prompt yields better results.
- Iterate at 480p to dial in motion, 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.
- The aspect ratio of output video is influenced by your input image.
- For longer content, generate multiple clips and edit together.
Related Models
- LTX-2.3 Text-to-Video — Generate video with audio from text only.
- LTX-2 19B Image-to-Video — Previous generation model.
Ltx 2.3 Image To Video API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2.3/image-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 Image To Video below.
HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2.3/image-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",
"image": "https://example.com/your-input.jpg",
"resolution": "720p",
"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/image-to-video", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"resolution": "720p",
"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/image-to-video",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"resolution": "720p",
"duration": 5,
"seed": -1
}
)
print(output["outputs"][0]) # → URL of the generated outputLtx 2.3 Image To Video API — Frequently asked questions
What is the Ltx 2.3 Image To Video API?
Ltx 2.3 Image To Video is a WaveSpeedAI model for video generation from images, 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 Image 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-image-to-video.
How much does Ltx 2.3 Image To Video cost per run?
Ltx 2.3 Image 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 Image To Video accept?
Key inputs: `prompt`, `image`, `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-image-to-video.
How do I get started with the Ltx 2.3 Image 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 Image 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.