> ## 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. |


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