Openai Whisper Turbo

Openai Whisper Turbo

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Try it on WaveSpeedAI!

Accurate speech-to-text with OpenAI Whisper Large v3 Turbo: multilingual transcripts with auto language detection and punctuation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

OpenAI Whisper Turbo is a fast, accurate speech-to-text transcription model powered by OpenAI’s Whisper architecture. It converts audio into clean, readable text with support for multiple languages — ideal for transcription, subtitling, and voice-driven workflows.


Why It Stands Out

  • High-speed transcription: Optimized for fast processing without sacrificing accuracy.
  • Multilingual support: Transcribe audio in dozens of languages with automatic language detection.
  • Prompt-guided transcription: Steer output formatting, terminology, or punctuation with custom prompts.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better transcription guidance.
  • Flexible input: Supports direct audio upload or public URL.

Parameters

ParameterRequiredDescription
audioYesUpload or link to an audio file (MP3 / WAV / M4A, etc.).
languageNoLanguage code for transcription; leave empty for auto-detection.
promptNoShort guidance text to steer transcription style or terminology.
enable_sync_modeNoWait for result before returning response (API only).

How to Use

  1. Upload your audio — drag and drop a file or paste a public URL.
  2. Select language (optional) — choose a specific language or let the model auto-detect.
  3. Add a prompt (optional) — guide formatting, punctuation, or specific terminology.
  4. Click Run and wait for transcription to complete.
  5. Copy or download the transcribed text.

Best Use Cases

  • Meeting Transcription — Convert recorded meetings, interviews, and calls into searchable text.
  • Subtitle Generation — Create accurate transcripts for video subtitling workflows.
  • Content Repurposing — Turn podcasts, webinars, and lectures into written content.
  • Voice Notes — Quickly transcribe voice memos and audio notes.
  • Accessibility — Generate transcripts to make audio content accessible.

Pricing

MetricPrice
Per second of audio$0.0007 / s

Total cost = duration of audio (in seconds) × $0.0007

Examples

  • 60s audio → 60 × $0.0007 = $0.042
  • 5 min (300s) audio → 300 × $0.0007 = $0.21
  • 30 min (1800s) audio → 1800 × $0.0007 = $1.26

Pro Tips for Best Quality

  • Use clear audio with minimal background noise for optimal accuracy.
  • Specify the language if auto-detection is inconsistent.
  • Add a prompt to guide transcription — include names, jargon, or formatting preferences.
  • For long recordings, consider splitting into smaller segments for faster processing.

Notes

  • Ensure uploaded audio URLs are publicly accessible.
  • Processing time varies based on audio duration and current queue load.

Duration limit

The maximum supported audio duration is 10 minutes. Longer audio is automatically trimmed to 10 minutes before processing.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
  "language": "auto"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/openai-whisper-turbo" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  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
done

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
audiostringYes--Audio file to transcribe. Provide an HTTPS URL or upload a file (MP3, WAV, FLAC up to 60 minutes).
languagestringNoautoauto, af, am, ar, as, az, ba, be, bg, bn, bo, br, bs, ca, cs, cy, da, de, el, en, es, et, eu, fa, fi, fo, fr, gl, gu, ha, haw, he, hi, hr, ht, hu, hy, id, is, it, ja, jw, ka, kk, km, kn, ko, la, lb, ln, lo, lt, lv, mg, mi, mk, ml, mn, mr, ms, mt, my, ne, nl, nn, no, oc, pa, pl, ps, pt, ro, ru, sa, sd, si, sk, sl, sn, so, sq, sr, su, sv, sw, ta, te, tg, th, tk, tl, tr, tt, uk, ur, uz, vi, yi, yo, zh, yueLanguage spoken in the audio. Set to 'auto' for automatic language detection (default).
promptstringNo-An optional text to provide as a prompt to guide the model's style or continue a previous audio segment. The prompt should be in the same language as the audio.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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