Create Transcription

POST /v1/audio/transcriptions Models: Transcription View .md

Transcribe audio. The request can be OpenRouter's JSON form, with the audio base64-encoded in input_audio, or OpenAI's multipart/form-data upload with the audio in file. Both return the same response, so the OpenAI and OpenRouter SDKs work unchanged.

Audio: Up to 25 MB after decoding and 4 hours long. Audio URLs are not accepted.

Formats: response_format is json (the default) or text, which returns the bare transcript as text/plain. verbose_json, timestamp_granularities, srt and vtt are not supported and return 400.

Streaming: With stream: true the response is OpenAI's server-sent events: transcript.text.delta events with each piece of the transcript as it is decoded, then one transcript.text.done with the whole text and the same usage as the JSON response. A failure after the stream began ends it with a transcript.text.error event in the error envelope. The upload still completes before decoding starts; this is not live audio.

Billing: Per second of audio, rounded up, as reported in usage.seconds.

Body

application/json

OpenRouter's transcription request. OpenRouter's provider is accepted and ignored.

model string required

The speech-to-text model to use, e.g. whisper-large-v3-turbo.
input_audio object required
2 fields
- data string required
  
  The audio, base64-encoded. Raw base64, not a data URI. Up to 25 MB decoded.
- format string required
  
  wavmp3flacm4aoggwebmaac
language string

ISO-639-1 code of the spoken language. Detected when omitted.
prompt string

Text to guide spelling and style, such as names and terms in the audio.
temperature number

range 0–1
response_format string

default jsonjsontext
stream boolean

Stream the transcript as OpenAI's transcript.text.* server-sent events.

default false

Body

multipart/form-data

Fields as multipart/form-data

model string required

The speech-to-text model to use, e.g. whisper-large-v3-turbo.
file string (binary) required

The audio file, up to 25 MB.
language string

ISO-639-1 code of the spoken language. Detected when omitted.
prompt string

Text to guide spelling and style, such as names and terms in the audio.
temperature number

range 0–1
response_format string

default jsonjsontext
stream boolean

Stream the transcript as OpenAI's transcript.text.* server-sent events.

default false

Responses

application/json, text/plain, text/event-stream · transcription-response-payload

2 fields

text string required

The transcript.
usage object required
2 fields
- type string
  
  Always duration.
- seconds integer
  
  Seconds of audio, rounded up. This is the billed amount.

curl https://api.vultrinference.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $VULTR_INFERENCE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "whisper-large-v3-turbo",
    "input_audio": {
      "data": "UklGRiQAAABXQVZFZm10IBAAAAABAAEAgD4AAAB9AAACABAAZGF0YQAAAAA=",
      "format": "wav"
    },
    "language": "en"
  }'

import os
import requests

response = requests.post(
    "https://api.vultrinference.com/v1/audio/transcriptions",
    headers={"Authorization": f"Bearer {os.environ['VULTR_INFERENCE_API_KEY']}"},
    json={
        "model": "whisper-large-v3-turbo",
        "input_audio": {
            "data": "UklGRiQAAABXQVZFZm10IBAAAAABAAEAgD4AAAB9AAACABAAZGF0YQAAAAA=",
            "format": "wav",
        },
        "language": "en",
    },
)
print(response.json())

const response = await fetch("https://api.vultrinference.com/v1/audio/transcriptions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.VULTR_INFERENCE_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "whisper-large-v3-turbo",
    "input_audio": {
      "data": "UklGRiQAAABXQVZFZm10IBAAAAABAAEAgD4AAAB9AAACABAAZGF0YQAAAAA=",
      "format": "wav"
    },
    "language": "en"
  }),
});
console.log(await response.json());

Response · 200

{
    "text": "string",
    "usage": {
        "type": "string",
        "seconds": 0
    }
}