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Pruna AI P-Video Text to Video is a fast AI video generation model that creates high-quality videos from text prompts. Ready-to-use REST inference API for cinematic clips, social media videos, advertising creatives, product visuals, motion design, and AI video generation workflows with simple integration, no coldstarts, and affordable pricing.

text-to-video
Input

Idle

$0.02per run·~50 / $1

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ExamplesView all

An adult man stands on a vast desert highway under warm sunlight, with distant mountains and dry air haze behind him. Dust moves subtly across the road, his clothes shift gently in the wind, and he looks toward the horizon before turning slightly toward the camera. The camera slowly pulls back to reveal the open landscape. Cinematic commercial travel film, realistic motion, stable identity, warm natural light.

Related Models

README

Pruna AI P-Video Text-to-Video

Pruna AI P-Video Text-to-Video generates videos from natural-language prompts with control over aspect ratio, duration, resolution, audio output, and seed-based reproducibility. It is suitable for cinematic scenes, commercial visuals, social content, concept videos, and other prompt-driven video generation workflows.

Why Choose This?

  • Prompt-based video generation Turn natural-language scene descriptions into motion video clips with controllable style and composition.

  • Flexible format control Choose aspect ratio, duration, and resolution to match different delivery needs.

  • Optional audio saving Enable save_audio when you want the generated output saved with audio.

  • Seed support for reproducibility Use seed to get more consistent outputs across repeated generations.

  • Simple pricing model Cost scales clearly with duration and output resolution.

Parameters

ParameterRequiredDescription
promptYesText description of the desired video scene, motion, and style.
aspect_ratioNoOutput aspect ratio, such as 16:9.
durationNoVideo duration in seconds.
resolutionNoOutput resolution: 720p or 1080p.
save_audioNoWhether to save the generated video with audio.
seedNoRandom seed for reproducibility. Use the same seed to get more consistent results.

How to Use

  1. Write your prompt — describe the subject, environment, motion, camera movement, and overall mood.
  2. Choose aspect ratio — select the format that matches your target platform or composition needs.
  3. Set duration — choose how long the video should be.
  4. Choose resolution — use 720p for lower cost or 1080p for higher quality.
  5. Enable audio saving (optional) — turn on save_audio if you want the saved result to include audio.
  6. Set a seed (optional) — use a fixed seed for more reproducible generations.
  7. Submit — run the model and download the generated video.

Example Prompt

An adult man stands on a vast desert highway under warm sunlight, with distant mountains and dry air haze behind him. Dust moves subtly across the road, his clothes shift gently in the wind, and he looks toward the horizon before turning slightly toward the camera. The camera slowly pulls back to reveal the open landscape. Cinematic commercial travel film, realistic motion, stable identity, warm natural light.

Pricing

Pricing is based on duration and resolution.

ResolutionPer Second
720p$0.02
1080p$0.04

Example Costs

Resolution5s10s15s
720p$0.10$0.20$0.30
1080p$0.20$0.40$0.60

Billing Rules

  • 720p costs $0.02 per second
  • 1080p costs the 720p rate
  • Pricing scales linearly with duration
  • aspect_ratio, save_audio, and seed do not affect pricing

Best Use Cases

  • Cinematic scene generation — Create travel, lifestyle, and atmospheric video clips from prompts.
  • Commercial content — Generate ad-like visuals for products, campaigns, and branded storytelling.
  • Social media video — Produce short-form clips tailored to different aspect ratios and durations.
  • Concept visualization — Turn written ideas into motion previews for pitching and ideation.
  • Creative prototyping — Explore multiple directions quickly with prompt and seed control.
  • Audio-enabled delivery — Save video outputs with audio when needed for downstream use.

Pro Tips

  • Be specific in your prompt about subject, movement, camera behavior, lighting, and mood.
  • Use 720p for rapid testing, then switch to 1080p for higher-quality final outputs.
  • Keep the same seed when you want to iterate on a concept with more consistent results.
  • Shorter durations are useful for fast concept validation before generating longer clips.
  • Match aspect_ratio to the final platform, such as widescreen for cinematic layouts.

Notes

  • prompt is the only required field.
  • Pricing depends on duration and resolution.
  • save_audio controls whether the saved video includes audio, but does not affect pricing.
  • seed helps with reproducibility but may not guarantee identical results in every case.

Related Models

  • Other Pruna AI video generation and image generation models may be useful when you need different quality, speed, or workflow trade-offs.
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.

P Video Text To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/pruna-ai/p-video/text-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 P Video Text 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",
    "aspect_ratio": "16:9",
    "duration": 5,
    "resolution": "720p",
    "save_audio": true,
    "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/pruna-ai/p-video/text-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/pruna-ai/p-video/text-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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "16:9",
        "duration": 5,
        "resolution": "720p",
        "save_audio": true,
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "aspect_ratio": "16:9",
    "duration": 5,
    "resolution": "720p",
    "save_audio": True,
    "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/pruna-ai/p-video/text-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)

P Video Text To Video API — Frequently asked questions

What is the P Video Text To Video API?

P Video Text To Video is a Pruna Ai model for video generation, exposed as a REST API on WaveSpeedAI. Pruna AI P-Video Text to Video is a fast AI video generation model that creates high-quality videos from text prompts. Ready-to-use REST inference API for cinematic clips, social media videos, advertising creatives, product visuals, motion design, and AI video generation workflows with simple integration, no coldstarts, and affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the P Video Text 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/pruna-ai/pruna-ai-p-video-text-to-video.

How much does P Video Text To Video cost per run?

P Video Text To Video starts at $0.020 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 P Video Text To Video accept?

Key inputs: `prompt`, `aspect_ratio`, `resolution`, `duration`, `seed`, `save_audio`. 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/pruna-ai/pruna-ai-p-video-text-to-video.

How long does P Video Text To Video take to generate?

Median end-to-end generation time on WaveSpeedAI is around 11 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 P Video Text To Video outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Pruna Ai). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

P Video Text to Video | Powerful Text-to-Video API on WaveSpeedAI