Pruna P-Video-2 Image-to-Video generates videos from input images with explicit controls for duration, resolution, draft mode, and audio output, making it suitable for image animation, creative videos, social content, ads, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.025per run·~40 / $1
The knight slowly lowers her sword completely. The white wolf approaches cautiously, stops in front of her, and places the broken golden chain at her feet. She kneels and picks it up, recognizing the symbol engraved on it. The wolf turns toward a distant mountain path and begins walking away. She hesitates, then follows. The camera gently circles during their first approach, then follows from behind into the snowy forest. Epic but intimate fantasy storytelling.
Pruna P-Video-2 Image-to-Video generates videos from an input image and a motion prompt. Upload a reference image, describe the motion or scene direction, choose a duration from 1 to 20 seconds, and generate either a full-quality video or a lower-cost draft preview.
Image-to-video generation
Turn a still image into a video using a motion prompt.
Image-based aspect ratio
The output aspect ratio follows the input image automatically.
Flexible duration control
Choose an explicit duration from 1 to 20 seconds.
Draft and Full modes
Use Draft mode for faster, lower-cost previews, or Full mode for higher-quality output.
720p and 1080p output
Generate at 720p for lower cost or 1080p for higher-resolution results.
Prompt upsampling
Use prompt_upsampling to expand and refine the generation prompt.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Non-empty generation prompt describing the desired motion, scene, camera movement, and visual direction. |
| image | Yes | Input image used as the visual source. Upload JPEG, PNG, or WebP, or provide a public image URL. The output aspect ratio follows this image. |
| duration | Yes | Requested video duration in seconds. Range: 1–20. No default is supplied. |
| resolution | No | Output resolution: 720p or 1080p. Default: 720p. |
| draft | No | Enable lower-quality Draft mode for faster, lower-cost previews. Default: false. |
| save_audio | No | Save audio in the generated result when supported. Default: true. |
| prompt_upsampling | No | Expand and optimize the generation prompt. Default: true. |
| seed | No | Optional non-negative integer seed for reproducible results. Omit for random generation. |
1 to 20 seconds.720p for lower-cost generation or 1080p for higher-resolution output.draft for preview generation or leave it disabled for full output.prompt_upsampling enabled when you want the prompt refined automatically.Pricing is based on the explicitly requested duration, selected resolution, and draft mode.
| Resolution | Full / second | Draft / second |
|---|---|---|
| 720p | $0.025 | $0.015 |
| 1080p | $0.05 | $0.03 |
| Duration | 720p Full | 720p Draft | 1080p Full | 1080p Draft |
|---|---|---|---|---|
| 5s | $0.125 | $0.075 | $0.25 | $0.15 |
| 10s | $0.25 | $0.15 | $0.50 | $0.30 |
| 20s | $0.50 | $0.30 | $1.00 | $0.60 |
Billing uses the requested duration, not the measured duration of the generated output. save_audio, prompt_upsampling, and seed do not add separate charges.
720p for lower-cost tests and 1080p for higher-resolution output.seed when comparing prompt or parameter changes.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/pruna-ai/p-video-2/image-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for P Video 2 Image To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"duration": 5,
"resolution": "720p",
"draft": false,
"save_audio": true,
"prompt_upsampling": true
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/pruna-ai/p-video-2/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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(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' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/pruna-ai/p-video-2/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"duration": 5,
"resolution": "720p",
"draft": false,
"save_audio": true,
"prompt_upsampling": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}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",
"duration": 5,
"resolution": "720p",
"draft": False,
"save_audio": True,
"prompt_upsampling": True
}
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-2/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 = 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", "deleted"}:
raise RuntimeError(result)
time.sleep(2)P Video 2 Image To Video is a Pruna Ai model for video generation from images, exposed as a REST API on WaveSpeedAI. Pruna P-Video-2 Image-to-Video generates videos from input images with explicit controls for duration, resolution, draft mode, and audio output, making it suitable for image animation, creative 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.
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-2-image-to-video.
P Video 2 Image To Video starts at $0.025 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.
Key inputs: `prompt`, `image`, `resolution`, `duration`, `seed`, `draft`. 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-2-image-to-video.
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.
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.