# LTX Video-0.9.7 13B > Generate videos from prompts using LTX Video-0.9.7 13B and custom LoRA ## Overview - **Endpoint**: `https://fal.run/fal-ai/ltx-video-13b-dev` - **Model ID**: `fal-ai/ltx-video-13b-dev` - **Category**: text-to-video - **Kind**: inference **Tags**: video, ltx-video, text-to-video ## Pricing Your request will cost **$0.20** per video. For $1 you can run this model approximately **5 times**. For more details, see [fal.ai pricing](https://fal.ai/pricing). ## 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: - **`prompt`** (`string`, _required_): Text prompt to guide generation - Examples: "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene." - **`negative_prompt`** (`string`, _optional_): Negative prompt for generation Default value: `"worst quality, inconsistent motion, blurry, jittery, distorted"` - Default: `"worst quality, inconsistent motion, blurry, jittery, distorted"` - **`loras`** (`list`, _optional_): LoRA weights to use for generation - Default: `[]` - Array of LoRAWeight - **`resolution`** (`ResolutionEnum`, _optional_): Resolution of the generated video. Default value: `"720p"` - Default: `"720p"` - Options: `"480p"`, `"720p"` - Examples: "720p" - **`aspect_ratio`** (`AspectRatioEnum`, _optional_): Aspect ratio of the generated video. Default value: `"16:9"` - Default: `"16:9"` - Options: `"9:16"`, `"1:1"`, `"16:9"` - Examples: "16:9" - **`seed`** (`integer`, _optional_): Random seed for generation - **`num_frames`** (`integer`, _optional_): The number of frames in the video. Default value: `121` - Default: `121` - Range: `9` to `1441` - Examples: 121 - **`first_pass_num_inference_steps`** (`integer`, _optional_): Number of inference steps during the first pass. Default value: `30` - Default: `30` - Range: `2` to `50` - Examples: 30 - **`second_pass_num_inference_steps`** (`integer`, _optional_): Number of inference steps during the second pass. Default value: `30` - Default: `30` - Range: `2` to `50` - Examples: 30 - **`second_pass_skip_initial_steps`** (`integer`, _optional_): The number of inference steps to skip in the initial steps of the second pass. By skipping some steps at the beginning, the second pass can focus on smaller details instead of larger changes. Default value: `17` - Default: `17` - Range: `0` to `49` - **`frame_rate`** (`integer`, _optional_): The frame rate of the video. Default value: `24` - Default: `24` - Range: `1` to `60` - Examples: 24 - **`expand_prompt`** (`boolean`, _optional_): Whether to expand the prompt using a language model. - Default: `false` - Examples: false - **`reverse_video`** (`boolean`, _optional_): Whether to reverse the video. - Default: `false` - Examples: false - **`enable_safety_checker`** (`boolean`, _optional_): Whether to enable the safety checker. Default value: `true` - Default: `true` - Examples: true - **`enable_detail_pass`** (`boolean`, _optional_): Whether to use a detail pass. If True, the model will perform a second pass to refine the video and enhance details. This incurs a 2.0x cost multiplier on the base price. - Default: `false` - Examples: false - **`temporal_adain_factor`** (`float`, _optional_): The factor for adaptive instance normalization (AdaIN) applied to generated video chunks after the first. This can help deal with a gradual increase in saturation/contrast in the generated video by normalizing the color distribution across the video. A high value will ensure the color distribution is more consistent across the video, while a low value will allow for more variation in color distribution. Default value: `0.5` - Default: `0.5` - Range: `0` to `1`, step: `0.05` - Examples: 0.5 - **`tone_map_compression_ratio`** (`float`, _optional_): The compression ratio for tone mapping. This is used to compress the dynamic range of the video to improve visual quality. A value of 0.0 means no compression, while a value of 1.0 means maximum compression. - Default: `0` - Range: `0` to `1`, step: `0.05` - Examples: 0 **Required Parameters Example**: ```json { "prompt": "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene." } ``` **Full Example**: ```json { "prompt": "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene.", "negative_prompt": "worst quality, inconsistent motion, blurry, jittery, distorted", "loras": [], "resolution": "720p", "aspect_ratio": "16:9", "num_frames": 121, "first_pass_num_inference_steps": 30, "second_pass_num_inference_steps": 30, "second_pass_skip_initial_steps": 17, "frame_rate": 24, "expand_prompt": false, "reverse_video": false, "enable_safety_checker": true, "enable_detail_pass": false, "temporal_adain_factor": 0.5, "tone_map_compression_ratio": 0 } ``` ### Output Schema The API returns the following output format: - **`video`** (`File`, _required_): The generated video file. - Examples: {"url":"https://storage.googleapis.com/falserverless/example_outputs/ltxv-multiscale-text-to-video.mp4"} - **`prompt`** (`string`, _required_): The prompt used for generation. - Examples: "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene." - **`seed`** (`integer`, _required_): The seed used for generation. **Example Response**: ```json { "video": { "url": "https://storage.googleapis.com/falserverless/example_outputs/ltxv-multiscale-text-to-video.mp4" }, "prompt": "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene." } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/ltx-video-13b-dev \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene." }' ``` ### Python Ensure you have the Python client installed: ```bash pip install fal-client ``` Then use the API client to make requests: ```python import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/ltx-video-13b-dev", arguments={ "prompt": "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene." }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ### JavaScript Ensure you have the JavaScript client installed: ```bash npm install --save @fal-ai/client ``` Then use the API client to make requests: ```javascript import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/ltx-video-13b-dev", { input: { prompt: "A cinematic fast-tracking shot follows a vintage, teal camper van as it descends a winding mountain trail. The van, slightly weathered but well-maintained, is the central focus, its retro design emphasized by the motion blur. Medium shot reveals the dusty, ochre trail, edged with vibrant green pine trees. Close-up on the van's tires shows the gravel spraying, highlighting the speed and rugged terrain. Sunlight filters through the trees, casting dappled shadows on the van and the trail. The background is a hazy, majestic mountain range bathed in warm, golden light. The overall mood is adventurous and exhilarating. High resolution 4k movie scene." }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Additional Resources ### Documentation - [Model Playground](https://fal.ai/models/fal-ai/ltx-video-13b-dev) - [API Documentation](https://fal.ai/models/fal-ai/ltx-video-13b-dev/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/ltx-video-13b-dev) ### fal.ai Platform - [Platform Documentation](https://docs.fal.ai) - [Python Client](https://docs.fal.ai/clients/python) - [JavaScript Client](https://docs.fal.ai/clients/javascript)