Seedance 2.0 Fast Text to Video Turbo | Powerful Text-to-Video API on WaveSpeedAI

Seedance 2.0 Fast Text-to-Video Turbo

Seedance 2.0 Fast Text-to-Video Turbo is the fastest and most affordable Seedance option — combining speed-optimized inference to deliver 720p and 1080p cinematic videos with native audio-visual synchronization.

Key Features

Fastest Seedance option Speed-optimized inference for maximum throughput.
Affordable HD output Starting at $0.60 per 5 seconds at 720p.
Unified multimodal architecture Same Seedance 2.0 foundation handling text, image, audio, and video inputs.
Native audio-visual synchronization Generates video with synchronized audio in a single pass.
Director-level control Camera movement, lighting, shadows, and character performance controlled through prompts.

Parameters

Parameter	Required	Description
prompt	Yes	Detailed description of the cinematic scene
aspect_ratio	No	Output format: 16:9 (default), 9:16, 4:3, 3:4, 1:1, 21:9
duration	No	Video length in seconds: 4-15 (default: 5)
resolution	No	Output resolution: 720p (default) or 1080p
enable_web_search	No	Enable web search for real-time information (default: false)
generate_audio	No	Generate synchronized audio for the output video (default: true)
reference_images	No	Reference image URLs to guide style, characters, or composition
reference_videos	No	Reference video URLs (up to 3). Each reference video is normalized to at least 2 seconds, each clip and the combined input are capped at 15 seconds, and the normalized combined input duration is rounded up to a whole second for billing.
reference_audios	No	Reference audio URLs (total length must not exceed 15 seconds)

Writing Effective Prompts

Most weak results come from thin prompts. Seedance reads a prompt like a shot list — the more you direct it, the more it delivers. Structure your prompt in three layers.

1. One-sentence summary

Open with a single line that fixes the essentials:

subject + setting + action + style + camera

A lone astronaut walks across a red desert at dusk, cinematic sci-fi, slow low-angle tracking shot.

2. Shot-by-shot timeline

For anything with a beginning, middle, and end, break the duration into timed segments (1-second granularity). Keep the timeline continuous — no gaps.

0-3s: The astronaut crests a dune, silhouetted against the setting sun. Slow push-in. 3-7s: They stop, turn to face the camera, and raise a hand to shield their eyes. Wind lifts red dust across the frame. 7-10s: Wide pull-back reveals a half-buried spaceship behind them. Warm rim light, long shadows.

Give each range enough to do but not too much — cramming a dozen actions into three seconds causes cuts or dropped beats.

3. Consistency notes

End with anything that should hold across the whole clip: camera style, lighting, color palette, atmosphere, audio.

Handheld feel throughout, shallow depth of field, warm golden-hour palette. Ambient wind and footsteps only — no music.

Camera language

Write these directly; the model understands them:

Shot size — extreme wide, wide, medium, medium close-up, close-up
Movement — push in, pull out, pan, track, follow, orbit, tilt up, handheld shake
Angle — low angle, overhead, eye-level, first-person
Techniques — one-shot / long take, dolly zoom, bullet time, speed ramp

For a niche term, add a plain-language gloss: "rack focus: the sharp foreground softens as the background comes into focus."

Referencing uploaded assets

When you attach images, videos, or audio, bind each one explicitly in the prompt by its upload order — @image1, @video1, @audio1 — and say what it's for. Don't rely on labels drawn inside the image itself.

"The knight in @image1 walks through the castle in @image2."
"Refer to @video1 for the camera movement only; keep its shot order."
"@image1 and @image2 are Character 1, voiced by @audio1."

When a reference is already accurate, just point to it — no need to re-describe it in detail.

Negative control

Positive descriptions work best, but you can suppress subtitles and audio:

"No subtitles."
"No BGM — ambient and action sounds only."
"No audio."

Weak vs. strong

	prompt
weak	`a cat playing`
strong	`A ginger cat pounces on a ball of yarn on a sunlit wooden floor. 0-2s: it crouches, tail flicking, eyes locked on the yarn. 2-5s: it springs forward and bats the yarn across the floor, then chases it out of frame. Low eye-level shot, slight handheld follow, warm afternoon light, shallow depth of field. Playful mood, soft ambient room tone, no music.`

Pricing

Without reference videos, output is $0.60 per 5 seconds at 720p and $0.65 per 5 seconds at 1080p.

With reference videos, pricing has two parts:

Normalized reference-video duration + output duration: $0.065 per second.
Output upscale: $0.02 per second at 720p or $0.03 per second at 1080p.

Each reference video is normalized to at least 2 seconds, each clip and the combined input are capped at 15 seconds, and the normalized combined input duration is rounded up to a whole second for billing.

Reference input	Output	720p	1080p
none	5s	$0.60	$0.65
2s	5s	$0.555	$0.605
5s	5s	$0.75	$0.80
15s	5s	$1.40	$1.45

Best Use Cases

Maximum Speed — Fastest possible Seedance generation at HD resolution.
High-Volume Production — Most cost-effective HD generation for large content libraries.
Rapid Prototyping — Quick iteration on HD concepts before upgrading to standard quality.
A/B Testing — Generate many variations efficiently.

Pro Tips

Use this for maximum speed and lowest cost at HD resolution.
Switch to standard Seedance 2.0 for final production quality.
Write prompts like a film director — include lighting, camera angles, and mood.
Start with 5s to iterate, then extend once the look is right.

Notes

Native audio generation included.
Resolution options: 720p and 1080p only (turbo mode with speed-optimized inference).
Duration range: 4-15 seconds (continuous).

Related Models

Seedance 2.0 Fast Text-to-Video — Speed-optimized generation.
Seedance 2.0 Text-to-Video Turbo — Standard inference turbo mode.
Seedance 2.0 Text-to-Video — Highest quality generation.

Notice: Use @image1, @image2, @audio1, etc. to reference your uploaded assets. The references will stay as plain text—don't worry.

Seedance 2.0 Fast Text To Video Turbo API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bytedance/seedance-2.0-fast/text-to-video-turbo 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 Seedance 2.0 Fast Text To Video Turbo below.

HTTP example

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,
    "enable_web_search": false,
    "generate_audio": true
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/bytedance/seedance-2.0-fast/text-to-video-turbo" \
  -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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 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' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Node.js example

const submitUrl = "https://api.wavespeed.ai/api/v3/bytedance/seedance-2.0-fast/text-to-video-turbo";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "16:9",
        "resolution": "720p",
        "duration": 5,
        "enable_web_search": false,
        "generate_audio": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  await new Promise(resolve => setTimeout(resolve, 2000));
}

Python example

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,
    "enable_web_search": False,
    "generate_audio": True
}

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/bytedance/seedance-2.0-fast/text-to-video-turbo", 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 = 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", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Seedance 2.0 Fast Text To Video Turbo API — Frequently asked questions

What is the Seedance 2.0 Fast Text To Video Turbo API?

Seedance 2.0 Fast Text To Video Turbo is a ByteDance model for video generation, exposed as a REST API on WaveSpeedAI. Seedance 2.0 Fast (Text-to-Video Turbo) generates cinematic 720p/1080p videos from text prompts using speed-optimized inference —the fastest and most affordable Seedance option with native audio-visual synchronization and director-level control. You can call it programmatically or try it from the playground above.

How do I call the Seedance 2.0 Fast Text To Video Turbo API?

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/bytedance/bytedance-seedance-2.0-fast-text-to-video-turbo.

How much does Seedance 2.0 Fast Text To Video Turbo cost per run?

Seedance 2.0 Fast Text To Video Turbo starts at $0.60 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.

What inputs does Seedance 2.0 Fast Text To Video Turbo accept?

Key inputs: `prompt`, `aspect_ratio`, `resolution`, `duration`, `reference_images`, `enable_web_search`. 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/bytedance/bytedance-seedance-2.0-fast-text-to-video-turbo.

How long does Seedance 2.0 Fast Text To Video Turbo take to generate?

Median end-to-end generation time on WaveSpeedAI is around 179 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Seedance 2.0 Fast Text To Video Turbo outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (ByteDance). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

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README

Seedance 2.0 Fast Text-to-Video Turbo

Key Features

Parameters

Writing Effective Prompts

1. One-sentence summary

2. Shot-by-shot timeline

3. Consistency notes

Camera language

Referencing uploaded assets

Negative control

Weak vs. strong

Pricing

Best Use Cases

Pro Tips

Notes

Related Models

Seedance 2.0 Fast Text To Video Turbo API — Quick start

Seedance 2.0 Fast Text To Video Turbo API — Frequently asked questions

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