Create precise keyframe-to-video sequences with Pika V2.2 Pikaframes. Upload up to 5 keyframes, set per-transition prompts and durations, and interpolate smooth motion for storyboards, camera moves, and style-consistent animation. Supports total runtimes up to 25 seconds. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
En attente
$0.4par exécution·~25 / $10
TV screen flickering
Pika V2.2 Pickaframes turns one or more still images into a short, animated video. You provide keyframe images plus a global description, optionally set per-segment transitions, and the model fills in motion, camera moves, and in-between frames for social videos, ads, and simple storyboard clips.
images (required)
Upload one or more images or paste URLs.
Single image: the model animates around that scene (camera moves, small changes).
Multiple images: they act as keyframes; the video evolves from the first to the last in order.
prompt (required) Global description of the clip: content, motion, and style. Example: TV screen flickering in a cozy kitchen, soft camera shake, warm cinematic lighting.
transitions (optional) A list of segments; each item has:
duration – segment length in seconds
prompt (optional) – local override or refinement for this segment only
If transitions are provided, total video length is roughly the sum of all durations. If no transitions are set, a 5-second clip is generated by default.
resolution Output quality tier, for example 720p or 1080p.
seed
−1: random each run (exploration).
Any fixed integer: reproducible layout and motion.
Output format: MP4 video at the chosen resolution.
Billing depends on effective duration and resolution. Each run is charged for at least 5 seconds.
billed_duration
If transitions are set: max(sum of all transition durations, 5)
If no transitions: 5
resolution_factor
0.5 for resolutions up to and including 720p
0.75 for 1080p
| Resolution | Billed length | Total price | Approx. per-second |
|---|---|---|---|
| ≤ 720p | 5 s | 0.20 USD | 0.040 USD / s |
| ≤ 720p | 10 s | 0.40 USD | 0.040 USD / s |
| ≤ 720p | 15 s | 0.60 USD | 0.040 USD / s |
| 1080p | 5 s | 0.30 USD | 0.060 USD / s |
| 1080p | 10 s | 0.60 USD | 0.060 USD / s |
| 1080p | 15 s | 0.90 USD | 0.060 USD / s |
Any clip shorter than 5 seconds is still billed as 5 seconds.
Write the global prompt In the prompt field, describe the overall scene and motion in one or two sentences (for example: TV screen flickering, reflections on the counter, slight handheld camera feel).
Add images
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/pika/v2.2-pikaframes 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 v2.2 Pikaframes below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"resolution": "720p",
"seed": -1
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/pika/v2.2-pikaframes" \
-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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/pika/v2.2-pikaframes";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"resolution": "720p",
"seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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));
}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 = {
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"resolution": "720p",
"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/pika/v2.2-pikaframes", 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)v2.2 Pikaframes is a Pika model for video generation from images, exposed as a REST API on WaveSpeedAI. Create precise keyframe-to-video sequences with Pika V2.2 Pikaframes. Upload up to 5 keyframes, set per-transition prompts and durations, and interpolate smooth motion for storyboards, camera moves, and style-consistent animation. Supports total runtimes up to 25 seconds. 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/pika/pika-v2.2-pikaframes.
v2.2 Pikaframes starts at $0.40 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`, `images`, `resolution`, `seed`, `transitions`. 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/pika/pika-v2.2-pikaframes.
Average end-to-end generation time on WaveSpeedAI is around 668 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Pika). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.