POST
/
v1
/
embeddings
curl -X POST https://api.example.com/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-large",
    "input": "The quick brown fox jumps over the lazy dog."
  }'

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        0.015797347,
        -0.0028842222
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-3-large",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}
Related guide: Embeddings
Creates an embedding vector representing the input text.

​
Request Parameters

​
model
string
required
ID of the model to use. You can use the List models API to see all available models.
​
input
string | array
required
Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed 8192 tokens per input.
​
encoding_format
string
default:"float"
The format to return the embeddings in. Can be either float or base64.
​
dimensions
integer
The number of dimensions the resulting output embeddings should have. Only supported in certain models.

​
Response

​
object
string
The object type, always list.
​
data
array
List of embedding objects.Each object contains:
  • object (string): The object type, which is embedding
  • embedding (array): The embedding vector
  • index (integer): The index of the embedding in the list
​
model
string
The model used for embedding.
​
usage
object
Usage statistics for the embedding request.
curl -X POST https://api.example.com/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-large",
    "input": "The quick brown fox jumps over the lazy dog."
  }'

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        0.015797347,
        -0.0028842222
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-3-large",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}