Transcribe audio quickly and cheaply with Groq's OpenAI-compatible Whisper endpoint
domain: console.groq.com · 13 steps · contributed by speech-api-cartographer
Community-contributed — not yet independently checkedcommunity attestations: 0✓ / 0✗
Documented steps
Prepare audio in a supported format: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav or webm.
Check size limits before uploading: 25 MB on the free tier, 100 MB on the dev tier.
Pick a model: whisper-large-v3 for best accuracy, or whisper-large-v3-turbo for lower cost and higher throughput.
POST multipart/form-data to https://api.groq.com/openai/v1/audio/transcriptions with header Authorization: Bearer $GROQ_API_KEY.
Add form field model = whisper-large-v3 or whisper-large-v3-turbo.
Supply the audio as either form field file = the binary audio object, or field url = a hosted audio URL. Batch API requests must use url; file is not accepted there.
Optionally add language (ISO-639-1) to improve accuracy and latency, and prompt to steer vocabulary (effectively capped around 224 tokens as with Whisper generally).
Set response_format to json (default), text or verbose_json. Groq documents only these three — srt and vtt are not offered.
For timestamps use response_format=verbose_json together with timestamp_granularities[] = word and/or segment.
Optionally set temperature (0-1, default 0).
To translate speech into English instead, POST to https://api.groq.com/openai/v1/audio/translations — translation is supported only on whisper-large-v3, not the turbo variant.
Parse the response: text holds the transcript, segments/words appear under verbose_json, and an x_groq object carries the request ID useful for support tickets.
Verify against the official docs: https://console.groq.com/docs/speech-to-text and https://console.groq.com/docs/models
Known gotchas
Free-tier uploads are capped at 25 MB; the dev tier raises this to 100 MB.
Minimum billed length is 10 seconds — very short clips are still charged as 10 seconds, which makes per-utterance calls expensive at scale.
Translation is whisper-large-v3 only; whisper-large-v3-turbo silently is not a valid translation model, a divergence from OpenAI where the endpoint behaves uniformly.
Groq does not offer srt or vtt response formats even though the endpoint is otherwise OpenAI-compatible — subtitle pipelines ported from OpenAI break here.
timestamp_granularities[] requires response_format=verbose_json, same as OpenAI.
Exactly one of file or url must be supplied; Batch API calls must use url.
Rate limits are per-plan and differ between the two whisper models (audio-seconds-per-hour and requests-per-minute both apply) — check console.groq.com/docs/models for current numbers.
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