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LTX 2.5 Image-to-Video animates a first-frame image into high-fidelity synchronized audio-video content, with optional last-frame guidance and 720P / 1080P / 2K / 4K output for cinematic videos, social content, ads, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
Input

Idle

$0.5per run·~20 / $10

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ExamplesView all

She slowly opens the conference room door and finds all the office furniture pushed aside, coworkers dancing inside under improvised party lights. Everyone stops and looks at her for one second, then cheers and pulls her in. The camera starts behind her in the quiet hallway, pushes toward the glowing door, then swings into the bright room as the energy suddenly changes. Fun workplace comedy, strong contrast, satisfying reveal.

Related Models

README

LTX-2.5 Image-to-Video

LTX-2.5 Image-to-Video animates a first-frame image into a synchronized video with native audio. You can also provide an optional last-frame image to guide the ending of the clip, making it useful for controlled image animation and start-to-end-frame video generation.

Why Choose This?

  • Image-to-video generation
    Animate a still image into a coherent video with prompt-guided motion.

  • Optional last-frame control
    Use last_image to guide the final frame and improve transition direction.

  • Native audio generation
    Generate synchronized audio together with the video output.

  • Multiple resolution options
    Choose from 720p, 1080p, 2k, or 4k depending on quality and cost needs.

  • Controlled duration
    Generate videos from 5 to 20 seconds.

  • Simple workflow
    Provide a first-frame image, write a prompt, choose resolution and duration, then generate the final video.

Parameters

ParameterRequiredDescription
imageYesFirst-frame image URL or Base64-encoded image.
last_imageNoOptional last-frame image URL or Base64-encoded image used to guide the ending of the clip.
promptYesText description of the motion, scene, camera movement, visual style, and audio direction.
resolutionNoOutput resolution: 720p, 1080p, 2k, or 4k. Default: 720p.
durationNoVideo length in seconds. Range: 5–20.
seedNoRandom seed. Use -1 for a random seed.

How to Use

  1. Upload the first-frame image — Provide the image that should guide the beginning of the video.
  2. Add last-frame guidance optional — Use last_image when you want more control over the final frame.
  3. Write your prompt — Describe the subject motion, scene development, camera movement, style, and audio direction.
  4. Choose resolution — Select 720p, 1080p, 2k, or 4k.
  5. Set duration — Choose a video length from 5 to 20 seconds.
  6. Set seed optional — Use a fixed seed for more reproducible results, or -1 for a random seed.
  7. Submit — Generate the final image-to-video output with synchronized audio.

Pricing

Pricing is based on generated video duration and selected resolution.

Native audio is included at every resolution and does not add a separate charge.

ResolutionPer second5s10s20s
720p$0.10$0.50$1.00$2.00
1080p$0.14$0.70$1.40$2.80
2k$0.21$1.05$2.10$4.20
4k$0.33$1.65$3.30$6.60

Best Use Cases

  • Image animation — Turn still images into short motion clips.
  • Start-and-end-frame control — Use image and last_image to guide both the beginning and ending of the video.
  • Product videos — Animate product images into polished promotional clips.
  • Character motion — Add movement, expression, or camera motion to character images.
  • Social media content — Create short videos for vertical, square, or widescreen formats.
  • Creative prototyping — Test motion direction, audio style, and scene pacing from a still image.

Pro Tips

  • Use a clear, high-quality first-frame image for stronger subject preservation.
  • Use last_image when the final pose, composition, or ending frame matters.
  • Keep first and last frames visually compatible for smoother transitions.
  • Describe motion, camera movement, lighting, mood, and audio cues in the prompt.
  • Use shorter durations for quick iteration and longer durations when the action needs more time.
  • Set a fixed seed when you want more reproducible outputs.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Ltx 2.5 Image To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2.5/image-to-video 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 2.5 Image To Video 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-2.5/image-to-video" \
  -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-2.5/image-to-video";
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-2.5/image-to-video", 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 2.5 Image To Video API — Frequently asked questions

What is the Ltx 2.5 Image To Video API?

Ltx 2.5 Image To Video is a WaveSpeedAI model for video generation from images, exposed as a REST API on WaveSpeedAI. LTX 2.5 Image-to-Video animates a first-frame image into high-fidelity synchronized audio-video content, with optional last-frame guidance and 720P / 1080P / 2K / 4K output for cinematic videos, social content, ads, and production workflows. 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 2.5 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 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-2.5-image-to-video.

How much does Ltx 2.5 Image To Video cost per run?

Ltx 2.5 Image To Video starts at $0.50 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 2.5 Image To Video accept?

Key inputs: `prompt`, `image`, `resolution`, `duration`, `seed`, `last_image`. 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-2.5-image-to-video.

How long does Ltx 2.5 Image To Video take to generate?

Median end-to-end generation time on WaveSpeedAI is around 94 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Ltx 2.5 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.

LTX 2.5 Image to Video API on WaveSpeedAI