LTX Video-0.9.7 I2V 720p
Generate videos from prompts and images using LTX Video-0.9.7
Features
ltx-video-v097/i2v-720p is the first DiT-based video generation model capable of generating high-quality videos in real-time.Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content.
Key Features
- High-Quality Output: Leveraging advanced 3D VAE technology, the model ensuring high-resolution video quality without compromising performance or temporal consistency.
- Hardware Optimization and Compatibility: The model is optimized for widely used GPUs and runs efficiently across a range of hardware platforms, with particular optimization for NVIDIA RTX series GPUs.
- Open Source: LTX-Video allows developers and researchers to freely access and modify the code to suit various application needs, with the flexibility to extend it for generating longer video content.
ComfyUI
ltx-video-v097/i2v-720p Reference to Video is available on ComfyUI, providing local inference capabilities through a node-based workflow, ensuring flexible and efficient image generation on your system.
Use Cases
- Digital influencers & avatars
- Story-driven video characters
- Personalization in marketing
Accelerated Inference
Our accelerated inference approach leverages advanced optimization technology from WavespeedAI. This innovative fusion technique significantly reduces computational overhead and latency, enabling rapid image generation without compromising quality. The entire system is designed to efficiently handle large-scale inference tasks while ensuring that real-time applications achieve an optimal balance between speed and accuracy. For further details, please refer to the blog post.
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/v2/wavespeed-ai/ltx-video-v097/i2v-720p" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"image": "https://d2g64w682n9w0w.cloudfront.net/media/images/1745136833067505009_dqvqnjhd.jpg",
"prompt": "A confident young tech professional standing in a modern office space, talking to the camera with calm gestures. Soft daylight, clean environment, business casual outfit, focused expression. Center frame, smooth motion",
"negative_prompt": "worst quality, inconsistent motion, blurry, jittery, distorted",
"size": "1280*720"
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v2/requests/${requestId}/status" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
Parameter | Type | Required | Default | Range | Description |
---|---|---|---|---|---|
image | string | Yes | https://d2g64w682n9w0w.cloudfront.net/media/images/1745136833067505009_dqvqnjhd.jpg | - | Image URL for Image-to-Video task |
prompt | string | Yes | A confident young tech professional standing in a modern office space, talking to the camera with calm gestures. Soft daylight, clean environment, business casual outfit, focused expression. Center frame, smooth motion | - | Text prompt to guide generation |
negative_prompt | string | No | worst quality, inconsistent motion, blurry, jittery, distorted | - | Negative prompt for generation |
size | string | No | 1280*720 | 720*1280, 1280*720 | The size of the output. |
seed | integer | No | - | -1 ~ 9999999999 | Random seed for generation |
Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data.id | string | Unique identifier for the prediction, Task Id |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |
Result Query Parameters
Result Request Parameters
Parameter | Type | Required | Default | Description |
---|---|---|---|---|
id | string | Yes | - | Task ID |
Result Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data | object | The prediction data object containing all details |
data.id | string | Unique identifier for the prediction |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |