The file field accepts the following formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, webm.The maximum upload size per request is 32 MB. For longer recordings, split the audio into chunks and concatenate the resulting transcripts on your side.
Use response_format=verbose_json together with timestamp_granularities[] to get word-level and/or segment-level timestamps. This is especially useful for subtitle generation, audio alignment, and video localization.timestamp_granularities[] accepts word, segment, or both (OpenAI whisper-1 supports both simultaneously).
mistral/voxtral-mini-latest only supports a single timestamp_granularities value per request. If you need both word and segment timestamps with Mistral, make two separate requests.
The verbose_json response format with timestamp_granularities is supported for openai/whisper-1 and mistral/voxtral-mini-latest. The newer gpt-4o-transcribe models return timestamps through their own response schema.
Transcription models are priced either per token of input audio (for gpt-4o-transcribe and gpt-4o-mini-transcribe) or per second of input audio (for whisper-1). The exact rate per model is on the Transcription model library. Charges appear in your usage dashboard immediately after the request completes.
400 Bad Request (missing file or model, unsupported audio format)
401 Unauthorized (invalid API key)
404 Model not found or not approved for your organization
413 Payload Too Large (audio file exceeds 32 MB)
429 Rate limited
500 Internal Server Error
This endpoint is fully compatible with the OpenAI Audio Transcriptions API. You can use the OpenAI SDK’s client.audio.transcriptions.create() method directly.
The language of the input audio in ISO 639-1 format (for example, en, fr, ja). Supplying the language improves accuracy and latency. Auto-detected when omitted.
Usage stats for the transcription. The shape depends on how the model is billed: token-based (gpt-4o-transcribe, gpt-4o-mini-transcribe) or duration-based (whisper-1).
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Last modified on June 8, 2026
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