PixVerse C1 generates film-grade videos from text prompts with flexible duration (1-15s), multiple resolutions up to 1080p, and optional native audio generation. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Bereit
$0.1pro Durchlauf·~10 / $1
A charismatic street magician in a worn velvet coat performs on a rainy Paris sidewalk at dusk. A small crowd watches as he produces a glowing golden coin from thin air. A skeptical little girl pushes to the front, arms crossed. He crouches to her level, winks, then reaches behind her ear — pulling out not a coin, but a tiny living butterfly. The girl's expression melts from suspicion into pure awe. Shallow depth of field, warm bokeh lights, slow-motion butterfly release, cinematic.
A WWII soldier sits alone in a crumbling stone bunker lit by a single candle, writing a letter. Outside, distant explosions silently flash through the narrow window. He pauses, stares at a small photograph of a woman and child, then closes his eyes. A single tear runs down his dust-covered cheek. He folds the letter carefully and tucks it into his breast pocket, over his heart. Slow push-in camera, desaturated warm tones, cinematic.
A young woman in a soaked trench coat sprints through a rain-drenched neon-lit alley in Tokyo, glancing back in terror. Reflections of red and blue signage ripple across the puddles beneath her feet. A shadowy figure in a hood rounds the corner behind her. She skids to a stop at a dead end, turns, and pulls a small glowing device from her pocket — her expression shifting from fear to cold determination. Cinematic handheld camera, motion blur, dramatic shadows, 4K.
PixVerse C1 is PixVerse's latest text-to-video model, generating high-quality cinematic video from natural language prompts. With four resolution tiers, eight aspect ratio options, optional native audio generation, and clips up to 15 seconds, it covers a wide range of creative and production workflows.
High-quality video generation Produces detailed, visually coherent video with accurate motion, lighting, and scene composition from text descriptions.
Four resolution tiers Generate from 360p up to 1080p — balance quality and cost based on your delivery needs.
Eight aspect ratio options Supports 16:9, 9:16, 1:1, 4:3, 3:4, 3:2, 2:3, and 21:9 for any platform or format.
Optional native audio generation Enable generate_audio_switch to produce synchronized ambient sound alongside the video.
Extended duration Generate clips from 1 to 15 seconds for maximum creative flexibility.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the scene, motion, camera style, and atmosphere. |
| aspect_ratio | No | Output aspect ratio. Options: 16:9 (default), 4:3, 1:1, 3:4, 9:16, 2:3, 3:2, 21:9. |
| resolution | No | Output resolution: 360p, 540p, 720p (default), or 1080p. |
| duration | No | Clip length in seconds. Range: 1–15. Default: 5. |
| generate_audio_switch | No | Whether to generate native audio for the video. Default: off. |
| Resolution | Without Audio | With Audio |
|---|---|---|
| 360p | $0.030/s | $0.040/s |
| 540p | $0.040/s | $0.050/s |
| 720p | $0.050/s | $0.065/s |
| 1080p | $0.095/s | $0.120/s |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/pixverse/pixverse-c1/text-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Pixverse C1 Text To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"generate_audio_switch": false
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/pixverse/pixverse-c1/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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/pixverse/pixverse-c1/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"generate_audio_switch": false
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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 = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"generate_audio_switch": False
}
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/pixverse/pixverse-c1/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)Pixverse C1 Text To Video is a Pixverse model for video generation, exposed as a REST API on WaveSpeedAI. PixVerse C1 generates film-grade videos from text prompts with flexible duration (1-15s), multiple resolutions up to 1080p, and optional native audio generation. Ready-to-use REST inference API, best performance, no cold starts, 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/pixverse/pixverse-pixverse-c1-text-to-video.
Pixverse C1 Text To Video starts at $0.10 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`, `aspect_ratio`, `resolution`, `duration`, `generate_audio_switch`. 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/pixverse/pixverse-pixverse-c1-text-to-video.
Median end-to-end generation time on WaveSpeedAI is around 47 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Pixverse). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.