> ## Documentation Index > Fetch the complete documentation index at: https://docs.together.ai/llms.txt > Use this file to discover all available pages before exploring further. # Transcribe audio > Transcribe and translate audio into text. Using a coding agent? Install the [together-audio](https://github.com/togethercomputer/skills/tree/main/skills/together-audio) skill to let your agent write correct speech-to-text code automatically. See [agent skills](/docs/agent-skills) for details. Together AI hosts speech recognition models including OpenAI's Whisper and NVIDIA Parakeet for batch transcription and real-time streaming. Read the [end-to-end guide](/docs/how-to-build-phone-voice-agent) to build a live voice agent powered by Together AI's real-time STT and TTS pipeline. ## Quickstart Basic transcription and translation: ```python Python theme={null} from pathlib import Path from together import Together client = Together() ## Basic transcription response = client.audio.transcriptions.create( file=Path("audio.mp3"), model="openai/whisper-large-v3", language="en", ) print(response.text) ## Basic translation response = client.audio.translations.create( file=Path("foreign_audio.mp3"), model="openai/whisper-large-v3", ) print(response.text) ``` ```typescript TypeScript theme={null} import { createReadStream } from 'fs'; import Together from 'together-ai'; const together = new Together(); // Basic transcription const transcription = await together.audio.transcriptions.create({ file: createReadStream('audio.mp3'), model: 'openai/whisper-large-v3', language: 'en', }); console.log(transcription.text); // Basic translation const translation = await together.audio.translations.create({ file: createReadStream('foreign_audio.mp3'), model: 'openai/whisper-large-v3', }); console.log(translation.text); ``` ```bash cURL theme={null} # Use -F for each field. Append ;type= to the file field so the # server knows the audio format. Common values: # audio/mpeg → .mp3 # audio/wav → .wav # audio/mp4 → .m4a # audio/webm → .webm # audio/flac → .flac # Transcription (MP3) curl -X POST "https://api.together.ai/v1/audio/transcriptions" \ -H "Authorization: Bearer $TOGETHER_API_KEY" \ -F "file=@audio.mp3;type=audio/mpeg" \ -F "model=openai/whisper-large-v3" \ -F "language=en" \ -F "response_format=json" # Translation (MP3) curl -X POST "https://api.together.ai/v1/audio/translations" \ -H "Authorization: Bearer $TOGETHER_API_KEY" \ -F "file=@foreign_audio.mp3;type=audio/mpeg" \ -F "model=openai/whisper-large-v3" # Transcription (WAV) curl -X POST "https://api.together.ai/v1/audio/transcriptions" \ -H "Authorization: Bearer $TOGETHER_API_KEY" \ -F "file=@audio.wav;type=audio/wav" \ -F "model=openai/whisper-large-v3" ``` ## Available models The following speech-to-text models are available: | Organization | Model | Model string for API | Serverless | Dedicated | | :----------- | :------------------------------ | :--------------------------------------- | :--------: | :-------: | | OpenAI | Whisper Large v3 | `openai/whisper-large-v3` | ✅ | ✅ | | NVIDIA | Parakeet TDT 0.6B v3 | `nvidia/parakeet-tdt-0.6b-v3` | ✅ | ✅ | | NVIDIA | Nemotron 3 ASR Streaming 0.6B | `nvidia/nemotron-3-asr-streaming-0.6b` | ✅ | ✅ | | NVIDIA | Nemotron 3.5 ASR Streaming 0.6B | `nvidia/nemotron-3.5-asr-streaming-0.6b` | ✅ | ✅ | | Deepgram | Nova-3 (English) | `deepgram/nova-3-en` | ❌ | ✅ | | Deepgram | Nova-3 Multilingual | `deepgram/nova-3-multi` | ❌ | ✅ | | Deepgram | Flux | `deepgram/flux` | ❌ | ✅ | See the [serverless catalog](/docs/serverless/models) and the [dedicated endpoint model catalog](/docs/dedicated-endpoints/models) for pricing and additional deployment options. ## Limits | Limit | Value | Notes | | -------------------------------- | ----------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Max request size (direct upload) | **500 MB** | Requests above this are rejected at the edge with `HTTP 413 Payload Too Large`. For anything larger, host the audio at a public HTTPS URL and pass that URL as the `file` field instead. | | Max file size (URL fetch) | **1 GB** | When you submit an HTTPS URL instead of binary, the server downloads up to 1 GB. Larger downloads fail with `400 file_too_large`. | | Max audio duration | **4 hours** per request | Longer audio is rejected with `400 audio_too_long`. Split into ≤ 4 h segments and submit separately. | | Supported formats | `.wav`, `.mp3`, `.m4a`, `.webm`, `.flac`, `.ogg`, `.opus`, `.aac` | | For payloads above 500 MB, host the file at a public HTTPS URL and pass that URL as the `file` field instead of a binary upload. The 500 MB edge cap only applies to direct uploads. See [Errors and troubleshooting](/docs/inference/transcription/features#errors-and-troubleshooting) for the full list of error codes. ## Audio transcription Audio transcription is speech-to-text in the same language as the source audio. ```python Python theme={null} from pathlib import Path from together import Together client = Together() response = client.audio.transcriptions.create( file=Path("meeting_recording.mp3"), model="openai/whisper-large-v3", language="en", response_format="json", ) print(f"Transcription: {response.text}") ``` ```typescript TypeScript theme={null} import { createReadStream } from 'fs'; import Together from 'together-ai'; const together = new Together(); const response = await together.audio.transcriptions.create({ file: createReadStream('meeting_recording.mp3'), model: 'openai/whisper-large-v3', language: 'en', response_format: 'json', }); console.log(`Transcription: ${response.text}`); ``` The API supports the following audio formats: * `.wav` (audio/wav) * `.mp3` (audio/mpeg) * `.m4a` (audio/mp4) * `.webm` (audio/webm) * `.flac` (audio/flac) * `.ogg` (audio/ogg) * `.opus` (audio/opus) * `.aac` (audio/aac) ### Audio limits The same limits apply to both `/v1/audio/transcriptions` and `/v1/audio/translations`: * **Maximum duration:** 4 hours. Longer audio is rejected with an `audio_too_long` error. * **Binary uploads:** Capped at 500 MB. Larger uploads return HTTP 413. Submit the audio via an HTTPS URL on the `file` field instead. * **URL-fetched audio:** Capped at 1 GB and 4 hours when you pass a public HTTPS URL as `file`. For longer recordings, chunk the audio into ≤ 4 h segments and submit each chunk as a separate URL request. When sending a binary upload, put the `model` form field **before** the `file` field in the multipart body so the server can dispatch the request without buffering the full audio payload. ### Input methods #### Path object ```python Python theme={null} from pathlib import Path response = client.audio.transcriptions.create( file=Path("recordings/interview.wav"), model="openai/whisper-large-v3", ) ``` #### File-like object ```python Python theme={null} with open("audio.mp3", "rb") as audio_file: response = client.audio.transcriptions.create( file=audio_file, model="openai/whisper-large-v3", ) ``` #### Remote URL The Python SDK doesn't accept a string URL on `file=`. To transcribe a remote file, download it first. ### Language support Specify the audio language using ISO 639-1 language codes: ```python Python theme={null} from pathlib import Path response = client.audio.transcriptions.create( file=Path("spanish_audio.mp3"), model="openai/whisper-large-v3", language="es", # Spanish ) ``` Common language codes: * `"en"`: English. * `"es"`: Spanish. * `"fr"`: French. * `"de"`: German. * `"ja"`: Japanese. * `"zh"`: Chinese. * `"auto"`: Auto-detect (default). ### Custom prompts Use prompts to improve transcription accuracy for specific contexts. Prompts are supported only on Whisper-family models (for example, `openai/whisper-large-v3`). Other STT models (for example, `nvidia/parakeet-tdt-0.6b-v3`) accept the field for API compatibility but ignore it. ```python Python theme={null} from pathlib import Path response = client.audio.transcriptions.create( file=Path("medical_consultation.mp3"), model="openai/whisper-large-v3", language="en", prompt="This is a medical consultation discussing patient symptoms, diagnosis, and treatment options.", ) ``` ## Next steps * [Streaming transcription](/docs/inference/transcription/streaming): real-time WebSocket transcription for low-latency applications. * [Audio translation](/docs/inference/transcription/translation): translate speech in any language to English text. * [Transcription features](/docs/inference/transcription/features): speaker diarization, word-level timestamps, response formats, async support, and best practices.