Google Veo 3.1 Lite Text-to-Video generates high-fidelity 720p or 1080p videos with natively generated audio from text prompts. Lightweight variant optimized for cost efficiency. Supports landscape and portrait aspect ratios, dialogue with lip-sync, and customizable duration. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
निष्क्रिय
$0.3प्रति रन·~33 / $10
A tall guy in a grocery store reaches for the last box of cereal on the top shelf — just as a woman on her tiptoes stretches for the same box from the other side. They both grab it at the same time, look at each other, then burst out laughing. He gestures "go ahead." She hesitates, then splits it — hands him half. Handheld camera, fluorescent supermarket lighting, natural and candid feel.
A young woman stands alone on a rooftop at golden hour, her loose white dress billowing in the wind. She slowly turns toward the camera, eyes half-closed, a faint smile crossing her lips. Cinematic bokeh background of city skyline, warm amber light wrapping her silhouette. 35mm film grain, shallow depth of field, slow push-in. A weathered old fisherman sits at the edge of a fog-covered dock at dawn, mending a torn net with calloused hands. His face carries decades of silence. Camera slowly orbits him. Desaturated tones, gentle waves lapping below, distant foghorn.
Veo 3.1 Lite is Google's efficient text-to-video model, generating high-quality cinematic video from natural language prompts at accessible pricing. With optional synchronized audio generation, negative prompt control, multiple aspect ratios, and resolution up to 1080p, it delivers strong results for 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.
Optional audio generation Enable generate_audio to produce synchronized ambient sound and atmosphere alongside the video.
Negative prompt support Specify what you don't want in the video for more precise control over the output.
Resolution options Generate at 720p or 1080p to match your quality and budget requirements.
Flexible aspect ratios Supports multiple orientations for social, cinematic, and broadcast formats.
Reproducible results Use the seed parameter to lock in a specific output for exact reproduction.
Prompt Enhancer Built-in tool to automatically improve your scene descriptions for richer output.
| Parameter | Required | Description |
|---|---|---|
| prompt | No | Text description of the scene, motion, camera style, and atmosphere. |
| aspect_ratio | No | Output aspect ratio. Default: 16:9. |
| duration | No | Clip length in seconds. Default: 6. |
| resolution | No | Output resolution: 720p or 1080p. Default: 1080p. |
| generate_audio | No | Whether to generate synchronized audio for the video. Default: enabled. |
| negative_prompt | No | Elements to exclude from the generated video. |
| seed | No | Random seed for reproducible results. |
| Resolution | Cost per 6s |
|---|---|
| 720p | $0.30 |
| 1080p | $0.48 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/google/veo3.1-lite/text-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Veo3.1 Lite Text To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"duration": 6,
"resolution": "720p"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/google/veo3.1-lite/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/google/veo3.1-lite/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"duration": 6,
"resolution": "720p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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",
"duration": 6,
"resolution": "720p"
}
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/google/veo3.1-lite/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)Veo3.1 Lite Text To Video is a Google model for video generation, exposed as a REST API on WaveSpeedAI. Google Veo 3.1 Lite Text-to-Video generates high-fidelity 720p or 1080p videos with natively generated audio from text prompts. Lightweight variant optimized for cost efficiency. Supports landscape and portrait aspect ratios, dialogue with lip-sync, and customizable duration. 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/google/google-veo3.1-lite-text-to-video.
Veo3.1 Lite Text To Video starts at $0.30 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`, `seed`, `negative_prompt`. 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/google/google-veo3.1-lite-text-to-video.
Median end-to-end generation time on WaveSpeedAI is around 129 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 (Google). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.