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POST
/
v1
/
embeddings
Create Embeddings
curl --request POST \
  --url https://api.perplexity.ai/v1/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": "<string>"
}
'
{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 123,
      "embedding": "<string>"
    }
  ],
  "model": "<string>",
  "usage": {
    "prompt_tokens": 123,
    "total_tokens": 123,
    "cost": {
      "input_cost": 123,
      "total_cost": 123
    }
  }
}

Documentation Index

Fetch the complete documentation index at: https://docs.perplexity.ai/llms.txt

Use this file to discover all available pages before exploring further.

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

Request body for creating embeddings

​
input
required

Input text to embed, encoded as a string or array of strings. Maximum 512 texts per request. Each input must not exceed 32K tokens. All inputs in a single request must not exceed 120,000 tokens combined. Empty strings are not allowed.

Minimum string length: 1
​
model
enum<string>
required

The embedding model to use

Available options:
pplx-embed-v1-0.6b,
pplx-embed-v1-4b
​
dimensions
integer

Number of dimensions for output embeddings (Matryoshka). Range: 128-1024 for pplx-embed-v1-0.6b, 128-2560 for pplx-embed-v1-4b. Defaults to full dimensions (1024 or 2560).

Required range: 128 <= x <= 2560
​
encoding_format
enum<string>
default:base64_int8

Output encoding format for embeddings. base64_int8 returns base64-encoded signed int8 values. base64_binary returns base64-encoded packed binary (1 bit per dimension).

Available options:
base64_int8,
base64_binary

Response

Successful Response

Response body for embeddings request

​
object
string

The object type

Example:

"list"

​
data
Embedding Object · object[]

List of embedding objects

​
model
string

The model used to generate embeddings

​
usage
Embeddings Usage · object

Token usage for the embeddings request