OpenAI's Whisper large-v3 speech recognition (144M+ runs) — the standard for transcription. Automatic language detection across ~100 languages, English translation, and plain text / SRT / VTT output formats.
Test this model instantly in the Console Playground — no code required
Copy usage instructions for Claude, ChatGPT, or other AI
curl -X POST "https://api.core.today/v1/predictions" \
-H "Content-Type: application/json" \
-H "X-API-Key: cdt_your_api_key" \
-d '{
"model": "openai/whisper",
"input": {
"audio": "https://example.com/meeting.mp3",
"language": "auto",
"transcription": "plain text"
}
}'| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
audio | string | Yes | - | Audio file to transcribe (mp3, wav, m4a, ...), up to 1 hour |
transcription | string | No | plain text | Format for the transcription output plain textsrtvtt |
translate | boolean | No | false | Translate the transcription to English |
language | string | No | auto | Language spoken in the audio. 'auto' detects automatically ('ko' for Korean) autoafamarasazbabebgbnbobrbscacscydadeeleneseteufafifofrglguhahawhehihrhthuhyidisitjajwkakkkmknkolalblnloltlvmgmimkmlmnmrmsmtmynenlnnnoocpaplpsptrorusasdsiskslsnsosqsrsusvswtatetgthtktltrttukuruzviyiyoyuezhAfrikaansAlbanianAmharicArabicArmenianAssameseAzerbaijaniBashkirBasqueBelarusianBengaliBosnianBretonBulgarianBurmeseCantoneseCastilianCatalanChineseCroatianCzechDanishDutchEnglishEstonianFaroeseFinnishFlemishFrenchGalicianGeorgianGermanGreekGujaratiHaitianHaitian CreoleHausaHawaiianHebrewHindiHungarianIcelandicIndonesianItalianJapaneseJavaneseKannadaKazakhKhmerKoreanLaoLatinLatvianLetzeburgeschLingalaLithuanianLuxembourgishMacedonianMalagasyMalayMalayalamMalteseMandarinMaoriMarathiMoldavianMoldovanMongolianMyanmarNepaliNorwegianNynorskOccitanPanjabiPashtoPersianPolishPortuguesePunjabiPushtoRomanianRussianSanskritSerbianShonaSindhiSinhalaSinhaleseSlovakSlovenianSomaliSpanishSundaneseSwahiliSwedishTagalogTajikTamilTatarTeluguThaiTibetanTurkishTurkmenUkrainianUrduUzbekValencianVietnameseWelshYiddishYoruba |
temperature | number | No | 0 | Sampling temperature. 0 is deterministic |
patience | number | No | - | optional patience value to use in beam decoding, as in https://arxiv.org/abs/2204.05424, the default (1.0) is equivalent to conventional beam search |
suppress_tokens | string | No | -1 | comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations |
initial_prompt | string | No | - | Optional vocabulary hint for the first window (names, jargon) |
condition_on_previous_text | boolean | No | true | if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop |
temperature_increment_on_fallback | number | No | 0.2 | temperature to increase when falling back when the decoding fails to meet either of the thresholds below |
compression_ratio_threshold | number | No | 2.4 | if the gzip compression ratio is higher than this value, treat the decoding as failed |
logprob_threshold | number | No | -1 | if the average log probability is lower than this value, treat the decoding as failed |
no_speech_threshold | number | No | 0.6 | if the probability of the <|nospeech|> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence |
There are 3 ways to provide files for the audio parameter:
Pass a publicly accessible URL directly. With the Storage API (POST /v1/files/upload-url) the file uploads straight to S3 (50MB per file) and you pass the returned file_url.
{
"model": "openai/whisper",
"input": {
"prompt": "your prompt here",
"audio": "https://example.com/image.jpg"
}
}Attach files directly to POST /v1/predictions/upload. No separate upload step, but the bytes pass through the API server so the whole request is capped at 10MB.
curl -X POST "https://api.core.today/v1/predictions/upload" \
-H "X-API-Key: cdt_your_api_key" \
-F "model=openai/whisper" \
-F 'input={"prompt":"your prompt here"}' \
-F "file:audio=@your_file.png"Common parameters used when calling POST /v1/predictions.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
model | string | Yes | - | Model identifier |
input | object | Yes | - | Object containing the model-specific parameters from the table above |
output_folder | string | No | - | Folder path for output files (max 256 chars, '..' not allowed) |
webhook_url | string | No | - | Webhook URL to call on completion |
is_public | boolean | No | false | If true, output files are also available via permanent public URLs |
Transcribe a Korean recording with auto detection
curl -X POST "https://api.core.today/v1/predictions" \
-H "Content-Type: application/json" \
-H "X-API-Key: cdt_your_api_key" \
-d '{
"model": "openai/whisper",
"input": {
"audio": "https://example.com/meeting.mp3",
"language": "auto",
"transcription": "plain text"
}
}'Generate subtitle file content directly
curl -X POST "https://api.core.today/v1/predictions" \
-H "Content-Type: application/json" \
-H "X-API-Key: cdt_your_api_key" \
-d '{
"model": "openai/whisper",
"input": {
"audio": "https://example.com/video-audio.mp3",
"transcription": "srt"
}
}'POST /v1/predictions