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LTX 2 19B Image to Video LoRA | Custom LoRA Image API

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LTX-2 19b Image-to-Video LoRA is the first DiT-based audio-video foundation model with synchronized audio and video generation. This LoRA version supports custom style adapters for personalized video generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

lora-support
Input

Idle

$0.1per run·~10 / $1

ExamplesView all

City lights twinkle softly, cars move along the streets below, light trails flowing through the roads, subtle atmospheric haze drifts

Ultra-realistic close-up photo of a cat with paw raised near mouth, tongue just finishing a lick, relaxed posture, soft eyes, warm cozy indoor lighting, creamy pastel background, extreme fur detail, shallow depth of field, cinematic portrait realism, no stylization

Ukrainian girls standing in a circle (khorovod) near a river at night, moonlight reflecting on water, stars in the night sky, mystical and cinematic atmosphere, ultra detailed, high fashion editorial style

The door slowly opens a few inches, light flickers and buzzes, dust motes drift. Slow push-in. Door creak, low ominous drone, faint floorboard groan.

toy in motion, slight blur, dynamic pose, frozen action moment, cinematic lighting, storytelling frame

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README

LTX-2 19B Image-to-Video LoRA

LTX-2 Image-to-Video LoRA generates customized videos from images with synchronized audio and full LoRA support. Apply up to 3 custom LoRA adapters for style personalization — perfect for branded content, custom characters, and unique visual styles.

Looking for the standard version? Try LTX-2 19B Image-to-Video without LoRA support.

Why Choose This?

  • LoRA support Apply up to 3 custom LoRA adapters to personalize style, characters, or visual aesthetics.

  • Image-conditioned video with audio Transforms a static image into a moving video with synchronized audio generated in a single pass.

  • Preserves input composition Maintains the subject, framing, and lighting of your reference image while adding natural motion.

  • High-fidelity output Leverages a 19B-parameter DiT architecture for detailed, temporally consistent video.

  • Flexible resolution Supports 480p, 720p, and 1080p outputs to balance quality and cost.

Parameters

ParameterRequiredDescription
imageYesSource image to animate (upload or public URL)
promptYesText description of motion, action, and audio cues
resolutionNoOutput resolution: 480p, 720p (default), or 1080p
durationNoVideo length in seconds (5-20, default: 5)
lorasNoList of LoRA adapters to apply (up to 3)
seedNoRandom seed for reproducibility (-1 for random)

LoRA Format

Each LoRA in the loras array has:

  • path (required) — URL to the LoRA weights file
  • scale (optional) — Weight multiplier from 0-4, default 1

How to Use

  1. Upload your image — drag and drop or paste a public URL.
  2. Write your prompt — describe motion, style, and audio cues.
  3. Add LoRAs — click "+ Add Item" to include custom LoRA adapters.
  4. Adjust LoRA scale — use 0.5-1.0 for subtle effects, 1.0-2.0 for stronger influence.
  5. Set resolution and duration — choose based on quality needs.
  6. Run — submit and download the generated video.

Pricing

Resolution5s10s15s20s
480p$0.075$0.15$0.225$0.30
720p$0.10$0.20$0.30$0.40
1080p$0.15$0.30$0.45$0.60

Billing Rules

  • Base price: $0.10 (720p, 5 seconds)
  • Resolution multiplier: 480p = 0.75×, 720p = 1×, 1080p = 1.5×
  • Duration: Scales linearly (per 5 seconds)
  • Total cost = duration × $0.10 × resolution_multiplier / 5

Best Use Cases

  • Custom Character Animation — Apply character LoRAs for consistent identity across videos.
  • Brand Content — Use trained LoRAs for consistent brand visual identity.
  • Artistic Styles — Apply style LoRAs for anime, painterly, or other aesthetics.
  • Product Visualization — Customize product appearance with trained adapters.

Pro Tips

  • Start with scale 1.0 and adjust up or down based on results.
  • Combine LoRAs carefully — multiple LoRAs can conflict; test combinations.
  • Match LoRA to content — use character LoRAs for character content, style LoRAs for aesthetics.
  • Audio adapts automatically — the model generates appropriate audio even with custom styles.
  • Use high-quality, sharp input images for best results.

Notes

  • Maximum video duration is 20 seconds.
  • Up to 3 LoRAs can be applied simultaneously.
  • LoRA version pricing is 25% higher than standard version.
  • The aspect ratio of output video is influenced by your input image.

Related Models

Reference

Note:This website uses AI models provided by third parties.

Ltx 2 19b Image To Video Lora API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2-19b/image-to-video-lora with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ltx 2 19b Image To Video Lora below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "resolution": "720p",
    "duration": 5,
    "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2-19b/image-to-video-lora" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2-19b/image-to-video-lora";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "resolution": "720p",
        "duration": 5,
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "resolution": "720p",
    "duration": 5,
    "seed": -1
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2-19b/image-to-video-lora", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Ltx 2 19b Image To Video Lora API — Frequently asked questions

What is the Ltx 2 19b Image To Video Lora API?

Ltx 2 19b Image To Video Lora is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. LTX-2 19b Image-to-Video LoRA is the first DiT-based audio-video foundation model with synchronized audio and video generation. This LoRA version supports custom style adapters for personalized video generation. 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 19b Image To Video Lora 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/ltx-2-19b-image-to-video-lora.

How much does Ltx 2 19b Image To Video Lora cost per run?

Ltx 2 19b Image To Video Lora 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 19b Image To Video Lora accept?

Key inputs: `prompt`, `image`, `resolution`, `duration`, `seed`, `loras`. 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-2-19b-image-to-video-lora.

How do I get started with the Ltx 2 19b Image To Video Lora 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 19b Image To Video Lora 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.