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OpenAI’s Whisper is a specialized foundation model designed for audio-to-text tasks. Unlike GPT-3.5, which processes text, or DALL·E 2, which generates images, Whisper accepts audio files as input and returns text output. It provides two main API endpoints for handling audio content:

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Key Audio APIs

Whisper supports transcription and translation for multiple source languages. However, its accuracy peaks when the output language is set to English.
The image describes two key APIs: audio transcription, which transcribes audio files into English text, and audio translation, which translates audio files into English text.
EndpointDescription
audio.transcriptionsTranscribes spoken content from an uploaded audio file into English text.
audio.translationsTranslates audio in various languages into English text.

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Audio File Size Limit

Each audio file uploaded to Whisper must not exceed 25 MB. Exceeding this limit will result in an error response from the API.
The image shows a document icon with a sound wave and "25MB" on it, indicating that audio file sizes cannot exceed 25MB. It is titled "Two Key APIs."

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Deployment Options

Whisper is offered both as an open-source model and via the OpenAI API. Depending on your needs:
  • OpenAI API: Easiest path—no infrastructure setup, automatic scaling, and straightforward billing.
  • Self-hosted Whisper: Full control over compute environment, on-premises or cloud, ideal for organizations with strict data privacy requirements.
In this guide, we’ll demonstrate how to call the Whisper API through OpenAI’s managed service.

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Next Steps

Let’s dive into a hands-on demo of audio transcription and translation using the OpenAI Whisper API.

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