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.
Idle
$0.4per run·~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; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for v2.2 Pikaframes below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/pika/v2.2-pikaframes" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"seed": -1
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("pika/v2.2-pikaframes", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"seed": -1
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"pika/v2.2-pikaframes",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"seed": -1
}
)
print(output["outputs"][0]) # → URL of the generated outputv2.2 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 prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. 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 1075 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.