resources/audio/subresources/transcriptions/methods/create/index.md 2026-07-10 23:02 UTC to 2026-07-12 06:58 UTC

Create transcription

post /audio/transcriptions

Transcribes audio into the input language.

Returns a transcription object in json, diarized_json, or verbose_json format, or a stream of transcript events.

Returns

• Transcription object { text, logprobs, usage }

  Represents a transcription response returned by model, based on the provided input.

  • text: string

    The transcribed text.

  • logprobs: optional array of object { token, bytes, logprob }

    The log probabilities of the tokens in the transcription. Only returned with the models gpt-4o-transcribe and gpt-4o-mini-transcribe if logprobs is added to the include array.

    • token: optional string

      The token in the transcription.

    • bytes: optional array of number

      The bytes of the token.

    • logprob: optional number

      The log probability of the token.

  • usage: optional object { input_tokens, output_tokens, total_tokens, 2 more } or object { seconds, type }

    Token usage statistics for the request.

    • TokenUsage object { input_tokens, output_tokens, total_tokens, 2 more }

      Usage statistics for models billed by token usage.

      • input_tokens: number

        Number of input tokens billed for this request.

      • output_tokens: number

        Number of output tokens generated.

      • total_tokens: number

        Total number of tokens used (input + output).

      • type: "tokens"

        The type of the usage object. Always tokens for this variant.

        • "tokens"

      • input_token_details: optional object { audio_tokens, text_tokens }

        Details about the input tokens billed for this request.

        • audio_tokens: optional number

          Number of audio tokens billed for this request.

        • text_tokens: optional number

          Number of text tokens billed for this request.

    • DurationUsage object { seconds, type }

      Usage statistics for models billed by audio input duration.

      • seconds: number

        Duration of the input audio in seconds.

      • type: "duration"

        The type of the usage object. Always duration for this variant.

        • "duration"

• TranscriptionDiarized object { duration, segments, task, 2 more }

  Represents a diarized transcription response returned by the model, including the combined transcript and speaker-segment annotations.

  • duration: number

    Duration of the input audio in seconds.

  • segments: array of TranscriptionDiarizedSegment

    Segments of the transcript annotated with timestamps and speaker labels.

    • id: string

      Unique identifier for the segment.

    • end: number

      End timestamp of the segment in seconds.

    • speaker: string

      Speaker label for this segment. When known speakers are provided, the label matches known_speaker_names[]. Otherwise speakers are labeled sequentially using capital letters (A, B, ...).

    • start: number

      Start timestamp of the segment in seconds.

    • text: string

      Transcript text for this segment.

    • type: "transcript.text.segment"

      The type of the segment. Always transcript.text.segment.

      • "transcript.text.segment"

  • task: "transcribe"

    The type of task that was run. Always transcribe.

    • "transcribe"

  • text: string

    The concatenated transcript text for the entire audio input.

  • usage: optional object { input_tokens, output_tokens, total_tokens, 2 more } or object { seconds, type }

    Token or duration usage statistics for the request.

    • Tokens object { input_tokens, output_tokens, total_tokens, 2 more }

      Usage statistics for models billed by token usage.

      • input_tokens: number

        Number of input tokens billed for this request.

      • output_tokens: number

        Number of output tokens generated.

      • total_tokens: number

        Total number of tokens used (input + output).

      • type: "tokens"

        The type of the usage object. Always tokens for this variant.

        • "tokens"

      • input_token_details: optional object { audio_tokens, text_tokens }

        Details about the input tokens billed for this request.

        • audio_tokens: optional number

          Number of audio tokens billed for this request.

        • text_tokens: optional number

          Number of text tokens billed for this request.

    • Duration object { seconds, type }

      Usage statistics for models billed by audio input duration.

      • seconds: number

        Duration of the input audio in seconds.

      • type: "duration"

        The type of the usage object. Always duration for this variant.

        • "duration"

• TranscriptionVerbose object { duration, language, text, 3 more }

  Represents a verbose json transcription response returned by model, based on the provided input.

  • duration: number

    The duration of the input audio.

  • language: string

    The language of the input audio.

  • text: string

    The transcribed text.

  • segments: optional array of TranscriptionSegment

    Segments of the transcribed text and their corresponding details.

    • id: number

      Unique identifier of the segment.

    • avg_logprob: number

      Average logprob of the segment. If the value is lower than -1, consider the logprobs failed.

    • compression_ratio: number

      Compression ratio of the segment. If the value is greater than 2.4, consider the compression failed.

    • end: number

      End time of the segment in seconds.

    • no_speech_prob: number

      Probability of no speech in the segment. If the value is higher than 1.0 and the avg_logprob is below -1, consider this segment silent.

    • seek: number

      Seek offset of the segment.

    • start: number

      Start time of the segment in seconds.

    • temperature: number

      Temperature parameter used for generating the segment.

    • text: string

      Text content of the segment.

    • tokens: array of number

      Array of token IDs for the text content.

  • usage: optional object { seconds, type }

    Usage statistics for models billed by audio input duration.

    • seconds: number

      Duration of the input audio in seconds.

    • type: "duration"

      The type of the usage object. Always duration for this variant.

      • "duration"

  • words: optional array of TranscriptionWord

    Extracted words and their corresponding timestamps.

    • end: number

      End time of the word in seconds.

    • start: number

      Start time of the word in seconds.

    • word: string

      The text content of the word.

Example

curl https://api.openai.com/v1/audio/transcriptions \
    -H 'Content-Type: multipart/form-data' \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -F 'file=@/path/to/file' \
    -F model=gpt-4o-transcribe

Response

{
  "text": "text",
  "logprobs": [
    {
      "token": "token",
      "bytes": [
        0
      ],
      "logprob": 0
    }
  ],
  "usage": {
    "input_tokens": 0,
    "output_tokens": 0,
    "total_tokens": 0,
    "type": "tokens",
    "input_token_details": {
      "audio_tokens": 0,
      "text_tokens": 0
    }
  }
}

Example

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F model="gpt-4o-transcribe"

Response

{
  "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.",
  "usage": {
    "type": "tokens",
    "input_tokens": 14,
    "input_token_details": {
      "text_tokens": 0,
      "audio_tokens": 14
    },
    "output_tokens": 45,
    "total_tokens": 59
  }
}

Diarization

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/meeting.wav" \
  -F model="gpt-4o-transcribe-diarize" \
  -F response_format="diarized_json" \
  -F chunking_strategy=auto \
  -F 'known_speaker_names[]=agent' \
  -F 'known_speaker_references[]=data:audio/wav;base64,AAA...'

Response

{
  "task": "transcribe",
  "duration": 27.4,
  "text": "Agent: Thanks for calling OpenAI support.\nA: Hi, I'm trying to enable diarization.\nAgent: Happy to walk you through the steps.",
  "segments": [
    {
      "type": "transcript.text.segment",
      "id": "seg_001",
      "start": 0.0,
      "end": 4.7,
      "text": "Thanks for calling OpenAI support.",
      "speaker": "agent"
    },
    {
      "type": "transcript.text.segment",
      "id": "seg_002",
      "start": 4.7,
      "end": 11.8,
      "text": "Hi, I'm trying to enable diarization.",
      "speaker": "A"
    },
    {
      "type": "transcript.text.segment",
      "id": "seg_003",
      "start": 12.1,
      "end": 18.5,
      "text": "Happy to walk you through the steps.",
      "speaker": "agent"
    }
  ],
  "usage": {
    "type": "duration",
    "seconds": 27
  }
}

Streaming

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F model="gpt-4o-mini-transcribe" \
  -F stream=true

Response

data: {"type":"transcript.text.delta","delta":"I","logprobs":[{"token":"I","logprob":-0.00007588794,"bytes":[73]}]}

data: {"type":"transcript.text.delta","delta":" see","logprobs":[{"token":" see","logprob":-3.1281633e-7,"bytes":[32,115,101,101]}]}

data: {"type":"transcript.text.delta","delta":" skies","logprobs":[{"token":" skies","logprob":-2.3392786e-6,"bytes":[32,115,107,105,101,115]}]}

data: {"type":"transcript.text.delta","delta":" of","logprobs":[{"token":" of","logprob":-3.1281633e-7,"bytes":[32,111,102]}]}

data: {"type":"transcript.text.delta","delta":" blue","logprobs":[{"token":" blue","logprob":-1.0280384e-6,"bytes":[32,98,108,117,101]}]}

data: {"type":"transcript.text.delta","delta":" and","logprobs":[{"token":" and","logprob":-0.0005108566,"bytes":[32,97,110,100]}]}

data: {"type":"transcript.text.delta","delta":" clouds","logprobs":[{"token":" clouds","logprob":-1.9361265e-7,"bytes":[32,99,108,111,117,100,115]}]}

data: {"type":"transcript.text.delta","delta":" of","logprobs":[{"token":" of","logprob":-1.9361265e-7,"bytes":[32,111,102]}]}

data: {"type":"transcript.text.delta","delta":" white","logprobs":[{"token":" white","logprob":-7.89631e-7,"bytes":[32,119,104,105,116,101]}]}

data: {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.0014890312,"bytes":[44]}]}

data: {"type":"transcript.text.delta","delta":" the","logprobs":[{"token":" the","logprob":-0.0110956915,"bytes":[32,116,104,101]}]}

data: {"type":"transcript.text.delta","delta":" bright","logprobs":[{"token":" bright","logprob":0.0,"bytes":[32,98,114,105,103,104,116]}]}

data: {"type":"transcript.text.delta","delta":" blessed","logprobs":[{"token":" blessed","logprob":-0.000045848617,"bytes":[32,98,108,101,115,115,101,100]}]}

data: {"type":"transcript.text.delta","delta":" days","logprobs":[{"token":" days","logprob":-0.000010802739,"bytes":[32,100,97,121,115]}]}

data: {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.00001700133,"bytes":[44]}]}

data: {"type":"transcript.text.delta","delta":" the","logprobs":[{"token":" the","logprob":-0.0000118755715,"bytes":[32,116,104,101]}]}

data: {"type":"transcript.text.delta","delta":" dark","logprobs":[{"token":" dark","logprob":-5.5122365e-7,"bytes":[32,100,97,114,107]}]}

data: {"type":"transcript.text.delta","delta":" sacred","logprobs":[{"token":" sacred","logprob":-5.4385737e-6,"bytes":[32,115,97,99,114,101,100]}]}

data: {"type":"transcript.text.delta","delta":" nights","logprobs":[{"token":" nights","logprob":-4.00813e-6,"bytes":[32,110,105,103,104,116,115]}]}

data: {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.0036910512,"bytes":[44]}]}

data: {"type":"transcript.text.delta","delta":" and","logprobs":[{"token":" and","logprob":-0.0031903093,"bytes":[32,97,110,100]}]}

data: {"type":"transcript.text.delta","delta":" I","logprobs":[{"token":" I","logprob":-1.504853e-6,"bytes":[32,73]}]}

data: {"type":"transcript.text.delta","delta":" think","logprobs":[{"token":" think","logprob":-4.3202e-7,"bytes":[32,116,104,105,110,107]}]}

data: {"type":"transcript.text.delta","delta":" to","logprobs":[{"token":" to","logprob":-1.9361265e-7,"bytes":[32,116,111]}]}

data: {"type":"transcript.text.delta","delta":" myself","logprobs":[{"token":" myself","logprob":-1.7432603e-6,"bytes":[32,109,121,115,101,108,102]}]}

data: {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.29254505,"bytes":[44]}]}

data: {"type":"transcript.text.delta","delta":" what","logprobs":[{"token":" what","logprob":-0.016815351,"bytes":[32,119,104,97,116]}]}

data: {"type":"transcript.text.delta","delta":" a","logprobs":[{"token":" a","logprob":-3.1281633e-7,"bytes":[32,97]}]}

data: {"type":"transcript.text.delta","delta":" wonderful","logprobs":[{"token":" wonderful","logprob":-2.1008714e-6,"bytes":[32,119,111,110,100,101,114,102,117,108]}]}

data: {"type":"transcript.text.delta","delta":" world","logprobs":[{"token":" world","logprob":-8.180258e-6,"bytes":[32,119,111,114,108,100]}]}

data: {"type":"transcript.text.delta","delta":".","logprobs":[{"token":".","logprob":-0.014231676,"bytes":[46]}]}

data: {"type":"transcript.text.done","text":"I see skies of blue and clouds of white, the bright blessed days, the dark sacred nights, and I think to myself, what a wonderful world.","logprobs":[{"token":"I","logprob":-0.00007588794,"bytes":[73]},{"token":" see","logprob":-3.1281633e-7,"bytes":[32,115,101,101]},{"token":" skies","logprob":-2.3392786e-6,"bytes":[32,115,107,105,101,115]},{"token":" of","logprob":-3.1281633e-7,"bytes":[32,111,102]},{"token":" blue","logprob":-1.0280384e-6,"bytes":[32,98,108,117,101]},{"token":" and","logprob":-0.0005108566,"bytes":[32,97,110,100]},{"token":" clouds","logprob":-1.9361265e-7,"bytes":[32,99,108,111,117,100,115]},{"token":" of","logprob":-1.9361265e-7,"bytes":[32,111,102]},{"token":" white","logprob":-7.89631e-7,"bytes":[32,119,104,105,116,101]},{"token":",","logprob":-0.0014890312,"bytes":[44]},{"token":" the","logprob":-0.0110956915,"bytes":[32,116,104,101]},{"token":" bright","logprob":0.0,"bytes":[32,98,114,105,103,104,116]},{"token":" blessed","logprob":-0.000045848617,"bytes":[32,98,108,101,115,115,101,100]},{"token":" days","logprob":-0.000010802739,"bytes":[32,100,97,121,115]},{"token":",","logprob":-0.00001700133,"bytes":[44]},{"token":" the","logprob":-0.0000118755715,"bytes":[32,116,104,101]},{"token":" dark","logprob":-5.5122365e-7,"bytes":[32,100,97,114,107]},{"token":" sacred","logprob":-5.4385737e-6,"bytes":[32,115,97,99,114,101,100]},{"token":" nights","logprob":-4.00813e-6,"bytes":[32,110,105,103,104,116,115]},{"token":",","logprob":-0.0036910512,"bytes":[44]},{"token":" and","logprob":-0.0031903093,"bytes":[32,97,110,100]},{"token":" I","logprob":-1.504853e-6,"bytes":[32,73]},{"token":" think","logprob":-4.3202e-7,"bytes":[32,116,104,105,110,107]},{"token":" to","logprob":-1.9361265e-7,"bytes":[32,116,111]},{"token":" myself","logprob":-1.7432603e-6,"bytes":[32,109,121,115,101,108,102]},{"token":",","logprob":-0.29254505,"bytes":[44]},{"token":" what","logprob":-0.016815351,"bytes":[32,119,104,97,116]},{"token":" a","logprob":-3.1281633e-7,"bytes":[32,97]},{"token":" wonderful","logprob":-2.1008714e-6,"bytes":[32,119,111,110,100,101,114,102,117,108]},{"token":" world","logprob":-8.180258e-6,"bytes":[32,119,111,114,108,100]},{"token":".","logprob":-0.014231676,"bytes":[46]}],"usage":{"input_tokens":14,"input_token_details":{"text_tokens":0,"audio_tokens":14},"output_tokens":45,"total_tokens":59}}

Logprobs

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F "include[]=logprobs" \
  -F model="gpt-4o-transcribe" \
  -F response_format="json"

Response

{
  "text": "Hey, my knee is hurting and I want to see the doctor tomorrow ideally.",
  "logprobs": [
    { "token": "Hey", "logprob": -1.0415299, "bytes": [72, 101, 121] },
    { "token": ",", "logprob": -9.805982e-5, "bytes": [44] },
    { "token": " my", "logprob": -0.00229799, "bytes": [32, 109, 121] },
    {
      "token": " knee",
      "logprob": -4.7159858e-5,
      "bytes": [32, 107, 110, 101, 101]
    },
    { "token": " is", "logprob": -0.043909557, "bytes": [32, 105, 115] },
    {
      "token": " hurting",
      "logprob": -1.1041146e-5,
      "bytes": [32, 104, 117, 114, 116, 105, 110, 103]
    },
    { "token": " and", "logprob": -0.011076359, "bytes": [32, 97, 110, 100] },
    { "token": " I", "logprob": -5.3193703e-6, "bytes": [32, 73] },
    {
      "token": " want",
      "logprob": -0.0017156356,
      "bytes": [32, 119, 97, 110, 116]
    },
    { "token": " to", "logprob": -7.89631e-7, "bytes": [32, 116, 111] },
    { "token": " see", "logprob": -5.5122365e-7, "bytes": [32, 115, 101, 101] },
    { "token": " the", "logprob": -0.0040786397, "bytes": [32, 116, 104, 101] },
    {
      "token": " doctor",
      "logprob": -2.3392786e-6,
      "bytes": [32, 100, 111, 99, 116, 111, 114]
    },
    {
      "token": " tomorrow",
      "logprob": -7.89631e-7,
      "bytes": [32, 116, 111, 109, 111, 114, 114, 111, 119]
    },
    {
      "token": " ideally",
      "logprob": -0.5800861,
      "bytes": [32, 105, 100, 101, 97, 108, 108, 121]
    },
    { "token": ".", "logprob": -0.00011093382, "bytes": [46] }
  ],
  "usage": {
    "type": "tokens",
    "input_tokens": 14,
    "input_token_details": {
      "text_tokens": 0,
      "audio_tokens": 14
    },
    "output_tokens": 45,
    "total_tokens": 59
  }
}

Word timestamps

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F "timestamp_granularities[]=word" \
  -F model="whisper-1" \
  -F response_format="verbose_json"

Response

{
  "task": "transcribe",
  "language": "english",
  "duration": 8.470000267028809,
  "text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
  "words": [
    {
      "word": "The",
      "start": 0.0,
      "end": 0.23999999463558197
    },
    ...
    {
      "word": "volleyball",
      "start": 7.400000095367432,
      "end": 7.900000095367432
    }
  ],
  "usage": {
    "type": "duration",
    "seconds": 9
  }
}

Segment timestamps

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F "timestamp_granularities[]=segment" \
  -F model="whisper-1" \
  -F response_format="verbose_json"

Response

{
  "task": "transcribe",
  "language": "english",
  "duration": 8.470000267028809,
  "text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
  "segments": [
    {
      "id": 0,
      "seek": 0,
      "start": 0.0,
      "end": 3.319999933242798,
      "text": " The beach was a popular spot on a hot summer day.",
      "tokens": [
        50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530
      ],
      "temperature": 0.0,
      "avg_logprob": -0.2860786020755768,
      "compression_ratio": 1.2363636493682861,
      "no_speech_prob": 0.00985979475080967
    },
    ...
  ],
  "usage": {
    "type": "duration",
    "seconds": 9
  }
}