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

# Migrating From OpenAI Speech to Text

This guide covers migrating from OpenAI Speech to Text, which is for **batch audio transcription**.

Cartesia's Batch Speech-to-Text API is compatible with OpenAI's API, making migration simply a matter of changing a few parameters.

<Card horizontal title="Back to migration guides" icon="arrow-left-from-arc" href="/use-the-api/stt/migrations">
  Migrating from OpenAI realtime transcription and others
</Card>

## Endpoints

**Cartesia Native:** `/stt` - Full feature support\
**OpenAI Compatible:** `/audio/transcriptions` - Drop-in replacement for OpenAI

## Using the OpenAI SDK

Replace your OpenAI base URL with `https://api.cartesia.ai` to use the compatibility layer for Cartesia:

### Supported parameters

* `file` - The audio file to transcribe
* `model` - Use `ink-whisper`
* `language` - Input audio language (ISO-639-1 format)
* `timestamp_granularities` - Include `["word"]` to get word-level timestamps

**Response Format**: Always returns JSON with transcribed text, duration, language, and optionally word timestamps.

For the complete parameter reference, see the [Batch STT API documentation](/api-reference/stt/transcribe).

Point the OpenAI SDK at Cartesia's base URL and switch the model to `ink-whisper`:

<CodeGroup>
  ```python theme={null}
  from openai import OpenAI

  client = OpenAI(
      api_key="your-cartesia-api-key",
      base_url="https://api.cartesia.ai"
  )

  with open("audio.wav", "rb") as audio_file:
      transcript = client.audio.transcriptions.create(
          file=audio_file,
          model="ink-whisper",
          language="en",
          timestamp_granularities=["word"]
      )
      
  print(transcript.text)
  ```

  ```typescript theme={null}
  import OpenAI from 'openai';
  import fs from 'fs';

  const client = new OpenAI({
    apiKey: 'your-cartesia-api-key',
    baseURL: 'https://api.cartesia.ai'
  });

  const transcription = await client.audio.transcriptions.create({
    file: fs.createReadStream('audio.wav'),
    model: 'ink-whisper',
    language: 'en',
    timestamp_granularities: ['word']
  });

  console.log(transcription.text);
  ```
</CodeGroup>

## Direct API Usage

Both endpoints accept identical parameters and return the same JSON response format:

### Cartesia Native Endpoint

```bash theme={null}
curl -X POST https://api.cartesia.ai/stt \
  -H "X-API-Key: your-cartesia-api-key" \
  -F "file=@audio.wav" \
  -F "model=ink-whisper" \
  -F "language=en" \
  -F "timestamp_granularities[]=word"
```

### OpenAI-Compatible Endpoint

```bash theme={null}
curl -X POST https://api.cartesia.ai/audio/transcriptions \
  -H "X-API-Key: your-cartesia-api-key" \
  -F "file=@audio.wav" \
  -F "model=ink-whisper" \
  -F "language=en" \
  -F "timestamp_granularities[]=word"
```

## Summary

To migrate from OpenAI Speech to Text to Cartesia:

1. **Update the base URL**: Change from `https://api.openai.com/v1` to `https://api.cartesia.ai`
2. **Update authentication**: Replace your OpenAI API key with your Cartesia API key
3. **Update model names**: Use `ink-whisper` instead of OpenAI's model names
4. **Keep the same endpoint**: Continue using `/audio/transcriptions`
5. **Avoid unsupported parameters**: Remove `prompt`, `temperature`, and `response_format` parameters
6. **Use timestamp\_granularities (Optional)**: Add `timestamp_granularities: ["word"]` to get word-level timestamps

The core functionality remains the same, with JSON responses containing transcribed text and optional word timestamps.