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

# Text Embedding 3 Small

> Text Embedding 3 Small: text embedding model. Request examples and parameters for MixRoute.

Text Embedding 3 Small is a text embedding model from OpenAI.

Call `text-embedding-3-small` through MixRoute using the endpoint shown below.

## Key capabilities

* Vector embeddings - Convert text into numeric vectors
* Batch input - Accept a string or an array of strings
* Similarity workflows - Use vectors for search and clustering

## Quick example

<Tabs>
  <Tab title="cURL">
    ```bash theme={null}
    curl "https://api.mixroute.ai/v1/embeddings" \
      -H "Authorization: Bearer YOUR_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{
      "model": "text-embedding-3-small",
      "input": "MixRoute model API"
    }'
    ```
  </Tab>

  <Tab title="Python">
    ```python theme={null}
    import requests

    response = requests.post(
        "https://api.mixroute.ai/v1/embeddings",
        headers={"Authorization": "Bearer YOUR_API_KEY"},
        json={'model': 'text-embedding-3-small', 'input': 'MixRoute model API'},
    )

    print(response.json())
    ```
  </Tab>
</Tabs>

## Parameters

| Parameter         | Type            | Required | Description                                 |
| ----------------- | --------------- | -------- | ------------------------------------------- |
| `model`           | string          | Yes      | Must be `text-embedding-3-small`.           |
| `input`           | string \| array | Yes      | Text or text array to embed.                |
| `dimensions`      | integer         | No       | Requested output dimensions when supported. |
| `encoding_format` | string          | No       | Embedding encoding format.                  |