PixVerse V6 generates high-quality videos from text prompts with flexible duration (1-15s), multiple resolutions up to 1080p, and optional audio generation. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
निष्क्रिय
$0.1प्रति रन·~10 / $1
A flamenco dancer stands completely still at center stage, spotlight on. For three seconds: nothing. Then her fingers begin — just the fingers — curling outward like smoke. The movement travels up her arms, into her shoulders, her chest expanding. By the time her foot stamps, the camera has already pulled back to reveal the full stage. One continuous breath becoming fury.
A macro lens slowly pushes through a single drop of water suspended mid-air, refracting an entire burning cityscape upside down within it. The drop trembles at 240fps, surface tension visibly pulsing. Background bokeh shifts from amber to deep violet as the camera breaches the droplet's edge.
PixVerse V6 is PixVerse's latest text-to-video model, delivering high-fidelity cinematic video from natural language prompts. With resolution options from 360p to 1080p, flexible aspect ratios, optional synchronized audio generation, and a thinking mode for complex scenes, it supports a wide range of creative and production workflows.
High-fidelity 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.
Optional audio generation Enable generate_audio_switch to produce synchronized ambient sound and atmosphere alongside the video.
Thinking mode The thinking_type parameter lets the model apply extended reasoning for complex or nuanced scene descriptions.
Flexible aspect ratios Supports multiple orientations to fit social, cinematic, and broadcast formats.
Prompt Enhancer Built-in tool to automatically improve your scene descriptions for richer output.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the scene, motion, camera style, and atmosphere. |
| aspect_ratio | No | Output aspect ratio. Default: 16:9. |
| resolution | No | Output resolution: 360p, 540p, 720p (default), or 1080p. |
| duration | No | Clip length in seconds. Default: 5. |
| generate_audio_switch | No | Whether to generate synchronized audio for the video. Default: off. |
| thinking_type | No | Reasoning mode for scene generation. Default: auto. |
| Resolution | Without Audio | With Audio |
|---|---|---|
| 360p | $0.025/s | $0.035/s |
| 540p | $0.035/s | $0.045/s |
| 720p | $0.045/s | $0.060/s |
| 1080p | $0.090/s | $0.115/s |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/pixverse/pixverse-v6/text-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Pixverse v6 Text To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"generate_audio_switch": false,
"thinking_type": "auto"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/pixverse/pixverse-v6/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-v6/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5,
"generate_audio_switch": false,
"thinking_type": "auto"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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,
"thinking_type": "auto"
}
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-v6/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 v6 Text To Video is a Pixverse model for video generation, exposed as a REST API on WaveSpeedAI. PixVerse V6 generates high-quality videos from text prompts with flexible duration (1-15s), multiple resolutions up to 1080p, and optional 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-v6-text-to-video.
Pixverse v6 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`, `thinking_type`. 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-v6-text-to-video.
Median end-to-end generation time on WaveSpeedAI is around 168 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.