models/OpenAI/Whisper-Large-V3-Turbo

Whisper-Large-V3-Turbo

audio-stt

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation.

slug · openai/whisper-large-v3-turboprovider · OpenAIfamily · Whisperreleased · 2024-05-22

Quickstart

curl https://api.aigateway.sh/v1/audio/transcriptions \
  -H "Authorization: Bearer $AIGATEWAY_API_KEY" \
  -F model="openai/whisper-large-v3-turbo" \
  -F file="@audio.mp3"

Capabilities

Streaming

Strengths

  • Speech-to-text transcription

Use cases

Meeting transcriptsCaptionsVoice agents

Pricing

Per minute$0.0005
You pay pass-through · 5% applied at credit top-up, not per-call.
Try in playground →CompareAPI referenceSee usage ranking →

Collections

More audio models →More from OpenAIFrontier models →Free-tier models →
API schema

Call Whisper-Large-V3-Turbo from any OpenAI SDK

POST https://api.aigateway.sh/v1/audio/transcriptions·Content-Type: multipart/form-data·Auth: Bearer sk-aig-...

Request body

json
# multipart/form-data — use curl -F or SDK file upload
model="openai/whisper-large-v3-turbo"
file=@audio.mp3
response_format=json    # or "verbose_json", "text", "srt", "vtt"
language=en             # optional

Response

json
{
  "text": "Hello from AIgateway.",
  "language": "en",
  "duration": 1.82
}

Quickstart

from openai import OpenAI
client = OpenAI(base_url="https://api.aigateway.sh/v1", api_key="sk-aig-...")

with open("audio.mp3", "rb") as f:
    r = client.audio.transcriptions.create(model="openai/whisper-large-v3-turbo", file=f)
print(r.text)

Errors

401authentication_errorInvalid or missing API key
402insufficient_creditsWallet empty (PAYG only)
404not_foundUnknown model or endpoint
429rate_limit_errorOver per-minute limit — see Retry-After header
500server_errorUpstream provider failed (retryable)
503service_unavailableUpstream saturated (retryable)
Full docs →API reference →OpenAPI spec →llms.txt →