ltx-2.3-quality/extend-video

Video a Video

Ltx 2.3 Quality Extend Video API

ltx-2.3-quality/extend-video

Extend-video

Generate high-quality video with audio from images using LTX-2.3

Entrada

Prompt *

Video url *

Arrastra archivos aquí o haz clic para subir

MAX:1

Extend direction

Num frames

Resolución

Match input fps

Generar Audio

Semilla

Salida

Inactivo

Los videos generados se mostrarán aquí

Configura los parámetros y haz clic en ejecutar para comenzar a generar

Cada ejecución costará $0.002. Con $10 puedes ejecutar aproximadamente 5000 veces.

Puedes continuar con:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parámetros

Ejemplo de código
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "ltx-2.3-quality/extend-video",  # Required. model name
    "prompt": "Continue the scene naturally, maintaining the same style, lighting, and motion dynamics",  # Required. Text description of the extended scene
    "video_url": "example_value",  # Required. URL of the input video to extend
    "extend_direction": "forward",  # Direction in which to extend the video. options: forward | backward
    "num_frames": 81,  # Number of frames to generate for the extension. (min: 9, max: 481)
    "resolution": "landscape_16_9",  # Output video resolution preset. options: square_hd | square | portrait_3_4 | portrait_9_16 | landscape_4_3 | landscape_16_9
    "match_input_fps": True,  # Whether to match the frame rate of the source video
    "generate_audio": False,  # Whether to generate accompanying audio for the extended video
    "seed": 0,  # Random seed for reproducibility. (min: 0)
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

Instalar

Instala el paquete de dependencias necesario.

pip install requests

Autenticación

Todas las solicitudes de API requieren autenticación mediante una clave de API. Puedes obtener tu clave de API desde el panel de Atlas Cloud.

export ATLASCLOUD_API_KEY="your-api-key-here"

Encabezados HTTP

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Mantén tu clave de API segura

Nunca expongas tu clave de API en código del lado del cliente ni en repositorios públicos. Usa variables de entorno o un proxy de backend en su lugar.

Enviar una solicitud

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Enviar una solicitud

Envía una solicitud de generación asíncrona. La API devuelve un ID de predicción que puedes usar para verificar el estado y obtener el resultado.

POST/api/v1/model/generateVideo

Cuerpo de la solicitud

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "ltx-2.3-quality/extend-video",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

Respuesta

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Verificar estado

Consulta el endpoint de predicción para verificar el estado actual de tu solicitud.

GET/api/v1/model/prediction/{prediction_id}

Ejemplo de polling

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Valores de estado

processingLa solicitud aún se está procesando.

completedLa generación está completa. Las salidas están disponibles.

succeededLa generación fue exitosa. Las salidas están disponibles.

failedLa generación falló. Verifica el campo de error.

Respuesta completada

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Subir archivos

Sube archivos al almacenamiento de Atlas Cloud y obtén una URL que puedes usar en tus solicitudes de API. Usa multipart/form-data para subir.

POST/api/v1/model/uploadMedia

Ejemplo de carga

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Respuesta

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Schema de entrada

Los siguientes parámetros se aceptan en el cuerpo de la solicitud.

Total: 9Obligatorio: 3Opcional: 6

modelstringrequired

model name

Default: "ltx-2.3-quality/extend-video"

promptstringrequired

Text description of the extended scene. Maximum 2,000 characters.

Default: "Continue the scene naturally, maintaining the same style, lighting, and motion dynamics"

video_urlstringrequired

URL of the input video to extend. Supported formats: mp4, mov, webm, m4v, gif.

Format: uri

extend_directionstring

Direction in which to extend the video.

Default: "forward"

forwardbackward

num_framesinteger

Number of frames to generate for the extension. Must be a multiple of 8 plus 1 (e.g. 25, 41, 81, 121).

Default: 81Min: 9Max: 481

resolutionstring

Output video resolution preset.

Default: "landscape_16_9"

square_hdsquareportrait_3_4portrait_9_16landscape_4_3landscape_16_9

match_input_fpsboolean

Whether to match the frame rate of the source video.

Default: true

generate_audioboolean

Whether to generate accompanying audio for the extended video.

Default: false

seedinteger

Random seed for reproducibility. Use the same seed and prompt to reproduce results.

Min: 0

Ejemplo de cuerpo de solicitud

{
  "model": "ltx-2.3-quality/extend-video",
  "prompt": "Continue the scene naturally, maintaining the same style, lighting, and motion dynamics",
  "video_url": "example_video_url",
  "extend_direction": "forward",
  "num_frames": 81,
  "resolution": "landscape_16_9",
  "match_input_fps": true,
  "generate_audio": false
}

Schema de salida

La API devuelve una respuesta de predicción con las URL de salida generadas.

modelstring

model name

Default: "ltx-2.3-quality/extend-video"

created_atstring

ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

idstring

Unique identifier for the prediction.

outputsarray

Array of URLs to the generated videos. Null when status is not completed.

statusstring

Status of the task: created, processing, completed, or failed.

Ejemplo de respuesta

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integra más de 400 modelos de IA directamente en tu asistente de codificación con IA. Un solo comando para instalar y luego usa lenguaje natural para generar imágenes, videos y chatear con LLM.

Clientes compatibles

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ clientes compatibles

Instalar

npx skills add AtlasCloudAI/atlas-cloud-skills

Configurar clave de API

Obtén tu clave de API desde el panel de Atlas Cloud y configúrala como variable de entorno.

export ATLASCLOUD_API_KEY="your-api-key-here"

Funcionalidades

Una vez instalado, puedes usar lenguaje natural en tu asistente de IA para acceder a todos los modelos de Atlas Cloud.

Generación de imágenesGenera imágenes con modelos como Nano Banana 2, Z-Image y más.

Creación de videosCrea videos a partir de texto o imágenes con Kling, Vidu, Veo, etc.

Chat con LLMChatea con Qwen, DeepSeek y otros modelos de lenguaje de gran escala.

Carga de mediosSube archivos locales para flujos de trabajo de edición de imágenes e imagen a video.

Más información

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server conecta tu IDE con más de 400 modelos de IA a través del Model Context Protocol. Funciona con cualquier cliente compatible con MCP.

Clientes compatibles

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ clientes compatibles

Instalar

npx -y atlascloud-mcp

Configuración

Agrega la siguiente configuración al archivo de configuración de MCP de tu IDE.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Herramientas disponibles

atlas_generate_imageGenera imágenes a partir de indicaciones de texto.

atlas_generate_videoCrea videos a partir de texto o imágenes.

atlas_chatChatea con modelos de lenguaje de gran escala.

atlas_list_modelsExplora más de 400 modelos de IA disponibles.

atlas_quick_generateCreación de contenido en un solo paso con selección automática de modelo.

atlas_upload_mediaSube archivos locales para flujos de trabajo de API.

Más información

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        },
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        },
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "schema": {
              "type": "string",
              "description": "Request ID"
            },
            "required": true
          }
        ]
      },
      "x-api-name": "model_result"
    }
  },
  "openapi": "3.0.0",
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "ltx-2.3-quality/extend-video"
          },
          "prompt": {
            "description": "Text description of the extended scene. Maximum 2,000 characters.",
            "type": "string",
            "minLength": 1,
            "maxLength": 2000,
            "default": "Continue the scene naturally, maintaining the same style, lighting, and motion dynamics"
          },
          "video_url": {
            "description": "URL of the input video to extend. Supported formats: mp4, mov, webm, m4v, gif.",
            "type": "string",
            "format": "uri",
            "x-ui-component": "file-upload",
            "x-accepted-formats": [
              "mp4",
              "mov",
              "webm",
              "m4v",
              "gif"
            ]
          },
          "extend_direction": {
            "description": "Direction in which to extend the video.",
            "type": "string",
            "default": "forward",
            "enum": [
              "forward",
              "backward"
            ],
            "x-ui-component": "select",
            "x-enum-labels": {
              "forward": "Forward (append after)",
              "backward": "Backward (prepend before)"
            }
          },
          "num_frames": {
            "description": "Number of frames to generate for the extension. Must be a multiple of 8 plus 1 (e.g. 25, 41, 81, 121).",
            "type": "integer",
            "default": 81,
            "minimum": 9,
            "maximum": 481,
            "x-ui-component": "slider"
          },
          "resolution": {
            "description": "Output video resolution preset.",
            "type": "string",
            "default": "landscape_16_9",
            "enum": [
              "square_hd",
              "square",
              "portrait_3_4",
              "portrait_9_16",
              "landscape_4_3",
              "landscape_16_9"
            ],
            "x-ui-component": "select",
            "x-enum-labels": {
              "square_hd": "Square HD (1024×1024)",
              "square": "Square (512×512)",
              "portrait_3_4": "Portrait 3:4",
              "portrait_9_16": "Portrait 9:16",
              "landscape_4_3": "Landscape 4:3",
              "landscape_16_9": "Landscape 16:9"
            },
            "x-enum-mapping": {
              "portrait_3_4": "portrait_4_3"
            }
          },
          "match_input_fps": {
            "description": "Whether to match the frame rate of the source video.",
            "type": "boolean",
            "default": true,
            "x-ui-component": "switch"
          },
          "generate_audio": {
            "description": "Whether to generate accompanying audio for the extended video.",
            "type": "boolean",
            "default": false,
            "x-ui-component": "switch"
          },
          "seed": {
            "description": "Random seed for reproducibility. Use the same seed and prompt to reproduce results.",
            "type": "integer",
            "minimum": 0
          }
        },
        "required": [
          "model",
          "prompt",
          "video_url"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "video_url",
          "extend_direction",
          "num_frames",
          "resolution",
          "match_input_fps",
          "generate_audio",
          "seed"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "ltx-2.3-quality/extend-video"
          },
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., \"2023-04-01T12:34:56.789Z\").",
            "format": "date-time",
            "type": "string"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated videos. Null when status is not completed.",
            "items": {
              "type": "string"
            },
            "nullable": true,
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  }
}

Plantilla de Prompt Compatible con LLM

# ltx-2.3-quality/extend-video

> Generate high-quality video with audio from images using LTX-2.3


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `ltx-2.3-quality/extend-video`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"ltx-2.3-quality/extend-video"`

- **`prompt`** (`string`, _required_):
  Text description of the extended scene. Maximum 2,000 characters.
  - Default: `"Continue the scene naturally, maintaining the same style, lighting, and motion dynamics"`

- **`video_url`** (`string`, _required_):
  URL of the input video to extend. Supported formats: mp4, mov, webm, m4v, gif.

- **`extend_direction`** (`string`, _optional_):
  Direction in which to extend the video.
  - Default: `"forward"`
  - Options: "forward", "backward"

- **`num_frames`** (`integer`, _optional_):
  Number of frames to generate for the extension. Must be a multiple of 8 plus 1 (e.g. 25, 41, 81, 121).
  - Default: `81`
  - Min: 9
  - Max: 481

- **`resolution`** (`string`, _optional_):
  Output video resolution preset.
  - Default: `"landscape_16_9"`
  - Options: "square_hd", "square", "portrait_3_4", "portrait_9_16", "landscape_4_3", "landscape_16_9"

- **`match_input_fps`** (`boolean`, _optional_):
  Whether to match the frame rate of the source video.
  - Default: `true`

- **`generate_audio`** (`boolean`, _optional_):
  Whether to generate accompanying audio for the extended video.
  - Default: `false`

- **`seed`** (`integer`, _optional_):
  Random seed for reproducibility. Use the same seed and prompt to reproduce results.
  - Min: 0



**Required Parameters Example**:

```json
{
  "model": "ltx-2.3-quality/extend-video",
  "prompt": "Continue the scene naturally, maintaining the same style, lighting, and motion dynamics",
  "video_url": ""
}
```


**Full Example**:

```json
{
  "model": "ltx-2.3-quality/extend-video",
  "prompt": "Continue the scene naturally, maintaining the same style, lighting, and motion dynamics",
  "video_url": "",
  "extend_direction": "forward",
  "num_frames": 81,
  "resolution": "landscape_16_9",
  "match_input_fps": true,
  "generate_audio": false,
  "seed": 0
}
```


### Output Schema

The API returns the following output format:


- **`model`** (`string`, _optional_):
  model name
  - Default: `"ltx-2.3-quality/extend-video"`

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated videos. Null when status is not completed.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "model": "ltx-2.3-quality/extend-video",
  "created_at": "",
  "id": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "ltx-2.3-quality/extend-video",
  "prompt": "Continue the scene naturally, maintaining the same style, lighting, and motion dynamics",
  "video_url": "",
  "extend_direction": "forward",
  "num_frames": 81,
  "resolution": "landscape_16_9",
  "match_input_fps": true,
  "generate_audio": false,
  "seed": 0
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/ltx-2.3-quality/extend-video)

After the spacecraft landed, the soldiers stepped off one by one.

Cargando...

LTX 2.3 Quality Extend Video

LTX 2.3 Quality Extend Video seamlessly extends an existing video forward or backward, generating new frames that match the source video's style, lighting, and motion dynamics. Only the generated extension is billed — source frames are never charged.

🌟 Key Features

⏩ Bidirectional Extension

Extend a video forward to continue the scene, or backward to generate a natural-looking prequel — all from the same model.

🎨 Style-Consistent Generation

The model analyzes the source video's visual style, color grading, and motion patterns, producing extensions that blend seamlessly with the original.

🎞 Frame Rate Matching

Optionally match the source video's frame rate for a perfectly smooth, artifact-free result.

🔊 Optional Audio Generation

Optionally generate audio for the extended segment.

🔁 Reproducible Results

Pin a seed value to reproduce or iterate on a specific generation.

⚙️ Parameters

Parameter	Required	Description
`prompt`	✅	Text description of the extended scene. Maximum 2,000 characters.
`video_url`	✅	URL of the input video to extend. Supported: mp4, mov, webm, m4v, gif.
`extend_direction`	❌	Direction of extension: `forward` (default) or `backward`.
`num_frames`	❌	Number of frames to generate for the extension (default: `81`).
`resolution`	❌	Output video resolution preset (default: `landscape_16_9`). See options below.
`match_input_fps`	❌	Whether to match the source video's frame rate (default: `true`).
`generate_audio`	❌	Whether to generate accompanying audio (default: `false`).
`seed`	❌	Random seed for reproducibility. Omit for random results.

Resolution Options

Value	Description
`square_hd`	Square HD (1024×1024)
`square`	Square (512×512)
`portrait_3_4`	Portrait 3:4
`portrait_9_16`	Portrait 9:16
`landscape_4_3`	Landscape 4:3
`landscape_16_9`	Landscape 16:9

Extend Direction Options

Value	Description
`forward`	Append new frames after the end of the source video
`backward`	Prepend new frames before the start of the source video

💲 Pricing

Billed at $0.0024075 per megapixel of generated video data (width × height × num_frames), rounded upward. Source video frames are not billed.

Example: landscape_16_9 (1280×720) at 81 frames ≈ 75 MP ≈ $0.18

💡 Prompt Tips

Continue the scene naturally — the character keeps walking down the moonlit street, footsteps echoing, same cinematic lighting.

For forward: describe what happens next — new actions, camera movements, scene transitions.
For backward: describe the preceding context — where the scene came from, setup shots.
Keep the style description consistent with the source video to avoid jarring transitions.
Reference the source video's existing elements (characters, lighting, environment) to anchor the generation.

🎯 Use Cases

Film & Short Video — Extend short clips into longer sequences without re-shooting.
Loop Creation — Generate seamless extensions to create looping background videos.
Scene Padding — Add establishing or trailing shots to existing footage.
Creative Exploration — Explore alternate continuations of a scene with different prompts.

📝 Notes

Both prompt and video_url are required.
num_frames must satisfy: (num_frames - 1) % 8 == 0 (e.g. 25, 33, 41, 81, 121).
Only the generated extension segment is billed; source video frames are never charged.
Task status values: created, processing, completed, failed.
Generated video URLs are returned in outputs once status is completed.

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Ltx 2.3 Quality Extend Video API

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LTX 2.3 Quality Extend Video

🌟 Key Features

⏩ Bidirectional Extension

🎨 Style-Consistent Generation

🎞 Frame Rate Matching

🔊 Optional Audio Generation

🔁 Reproducible Results

⚙️ Parameters

Resolution Options

Extend Direction Options

💲 Pricing

💡 Prompt Tips

🎯 Use Cases

📝 Notes

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Seedance 2.0 Mini Image-to-Video

Seedance 2.0 Mini Text-to-Video

HappyHorse-1.1 Text-to-video

HappyHorse-1.1 Image-to-video

HappyHorse-1.1 Reference-to-video

Gemini Omni Flash Reference-to-Video

Gemini Omni Flash Image-to-Video

Gemini Omni Flash Video Edit

Gemini Omni Flash Text-to-Video

Gemini Omni Flash Reference-to-Video Developer

Avatar Omni Human 1.5

Kling V3.0 Turbo Text-to-Video

Kling V3.0 Turbo Image-to-Video

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