> ## Documentation Index
> Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview of Whisper

> OpenAI’s Whisper is a model for audio-to-text tasks, providing transcription and translation APIs for various languages.

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:

## Key Audio APIs

<Callout icon="lightbulb" color="#1CB2FE">
  Whisper supports transcription and translation for multiple source languages. However, its accuracy peaks when the output language is set to English.
</Callout>

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  ![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.](https://kodekloud.com/kk-media/image/upload/v1752881497/notes-assets/images/Mastering-Generative-AI-with-OpenAI-Overview-of-Whisper/audio-transcription-translation-apis.jpg)
</Frame>

| Endpoint             | Description                                                               |
| -------------------- | ------------------------------------------------------------------------- |
| audio.transcriptions | Transcribes spoken content from an uploaded audio file into English text. |
| audio.translations   | Translates audio in various languages into English text.                  |

## Audio File Size Limit

<Callout icon="triangle-alert" color="#FF6B6B">
  Each audio file uploaded to Whisper must not exceed 25 MB. Exceeding this limit will result in an error response from the API.
</Callout>

<Frame>
  ![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."](https://kodekloud.com/kk-media/image/upload/v1752881498/notes-assets/images/Mastering-Generative-AI-with-OpenAI-Overview-of-Whisper/document-icon-sound-wave-25mb.jpg)
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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.

## Next Steps

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

***

## Links and References

* [OpenAI Whisper API Reference](https://platform.openai.com/docs/api-reference/audio)
* [Whisper GitHub Repository](https://github.com/openai/whisper)
* [OpenAI API Documentation](https://platform.openai.com/docs/)

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