List available models
curl --request GET \
--url https://api.pinecone.io/models \
--header 'Api-Key: <api-key>' \
--header 'X-Pinecone-Api-Version: <x-pinecone-api-version>'import requests
url = "https://api.pinecone.io/models"
headers = {
"X-Pinecone-Api-Version": "<x-pinecone-api-version>",
"Api-Key": "<api-key>"
}
response = requests.get(url, headers=headers)
print(response.text)const options = {
method: 'GET',
headers: {'X-Pinecone-Api-Version': '<x-pinecone-api-version>', 'Api-Key': '<api-key>'}
};
fetch('https://api.pinecone.io/models', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.pinecone.io/models",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "GET",
CURLOPT_HTTPHEADER => [
"Api-Key: <api-key>",
"X-Pinecone-Api-Version: <x-pinecone-api-version>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://api.pinecone.io/models"
req, _ := http.NewRequest("GET", url, nil)
req.Header.Add("X-Pinecone-Api-Version", "<x-pinecone-api-version>")
req.Header.Add("Api-Key", "<api-key>")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.get("https://api.pinecone.io/models")
.header("X-Pinecone-Api-Version", "<x-pinecone-api-version>")
.header("Api-Key", "<api-key>")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.pinecone.io/models")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
request["X-Pinecone-Api-Version"] = '<x-pinecone-api-version>'
request["Api-Key"] = '<api-key>'
response = http.request(request)
puts response.read_body{
"models": [
{
"default_dimension": 256,
"max_batch_size": 96,
"max_sequence_length": 512,
"modality": "text",
"model": "example-embedding-model",
"provider_name": "Embedding Model Provider",
"short_description": "An example embedding model.",
"supported_dimensions": [
256,
512
],
"supported_metrics": [
"cosine",
"euclidean"
],
"supported_parameters": [
{
"allowed_values": [
"value1",
"value2"
],
"parameter": "example_required_param",
"required": true,
"type": "one_of",
"value_type": "string"
},
{
"allowed_values": [
"value1",
"value2"
],
"default": "value1",
"parameter": "example_param_with_default",
"required": false,
"type": "one_of",
"value_type": "string"
},
{
"default": 5,
"max": 10,
"min": 0,
"parameter": "example_numeric_range",
"required": false,
"type": "numeric_range",
"value_type": "integer"
}
],
"type": "embed",
"vector_type": "dense"
},
{
"max_batch_size": 100,
"max_sequence_length": 1024,
"modality": "text",
"model": "example-reranking-model",
"provider_name": "Reranking Model Provider",
"short_description": "An example reranking model.",
"supported_parameters": [
{
"default": true,
"parameter": "example_any_value",
"required": false,
"type": "any",
"value_type": "boolean"
}
],
"type": "rerank"
}
]
}{
"error": {
"code": "UNAUTHENTICATED",
"message": "Invalid API key."
},
"status": 401
}{
"error": {
"code": "NOT_FOUND",
"message": "Model example-model not found."
},
"status": 404
}{
"error": {
"code": "UNKNOWN",
"message": "Internal server error"
},
"status": 500
}Inference
List available models
List the embedding and reranking models hosted by Pinecone.
You can use hosted models for integrated inference in Pinecone operations, such as integrated-embedding fields in a document index, or for standalone embedding and reranking. For more details, see Vector embedding and Rerank results.
GET
/
models
List available models
curl --request GET \
--url https://api.pinecone.io/models \
--header 'Api-Key: <api-key>' \
--header 'X-Pinecone-Api-Version: <x-pinecone-api-version>'import requests
url = "https://api.pinecone.io/models"
headers = {
"X-Pinecone-Api-Version": "<x-pinecone-api-version>",
"Api-Key": "<api-key>"
}
response = requests.get(url, headers=headers)
print(response.text)const options = {
method: 'GET',
headers: {'X-Pinecone-Api-Version': '<x-pinecone-api-version>', 'Api-Key': '<api-key>'}
};
fetch('https://api.pinecone.io/models', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.pinecone.io/models",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "GET",
CURLOPT_HTTPHEADER => [
"Api-Key: <api-key>",
"X-Pinecone-Api-Version: <x-pinecone-api-version>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://api.pinecone.io/models"
req, _ := http.NewRequest("GET", url, nil)
req.Header.Add("X-Pinecone-Api-Version", "<x-pinecone-api-version>")
req.Header.Add("Api-Key", "<api-key>")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.get("https://api.pinecone.io/models")
.header("X-Pinecone-Api-Version", "<x-pinecone-api-version>")
.header("Api-Key", "<api-key>")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.pinecone.io/models")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
request["X-Pinecone-Api-Version"] = '<x-pinecone-api-version>'
request["Api-Key"] = '<api-key>'
response = http.request(request)
puts response.read_body{
"models": [
{
"default_dimension": 256,
"max_batch_size": 96,
"max_sequence_length": 512,
"modality": "text",
"model": "example-embedding-model",
"provider_name": "Embedding Model Provider",
"short_description": "An example embedding model.",
"supported_dimensions": [
256,
512
],
"supported_metrics": [
"cosine",
"euclidean"
],
"supported_parameters": [
{
"allowed_values": [
"value1",
"value2"
],
"parameter": "example_required_param",
"required": true,
"type": "one_of",
"value_type": "string"
},
{
"allowed_values": [
"value1",
"value2"
],
"default": "value1",
"parameter": "example_param_with_default",
"required": false,
"type": "one_of",
"value_type": "string"
},
{
"default": 5,
"max": 10,
"min": 0,
"parameter": "example_numeric_range",
"required": false,
"type": "numeric_range",
"value_type": "integer"
}
],
"type": "embed",
"vector_type": "dense"
},
{
"max_batch_size": 100,
"max_sequence_length": 1024,
"modality": "text",
"model": "example-reranking-model",
"provider_name": "Reranking Model Provider",
"short_description": "An example reranking model.",
"supported_parameters": [
{
"default": true,
"parameter": "example_any_value",
"required": false,
"type": "any",
"value_type": "boolean"
}
],
"type": "rerank"
}
]
}{
"error": {
"code": "UNAUTHENTICATED",
"message": "Invalid API key."
},
"status": 401
}{
"error": {
"code": "NOT_FOUND",
"message": "Model example-model not found."
},
"status": 404
}{
"error": {
"code": "UNKNOWN",
"message": "Internal server error"
},
"status": 500
}Authorizations
Headers
Required date-based version header
Query Parameters
Filter models by type ('embed' or 'rerank'). Filter models by type.
Possible values: embed or rerank.
Filter embedding models by vector type ('dense' or 'sparse'). Only relevant when type=embed.
Filter models by vector type.
Possible values: dense or sparse.
Response
The list of available models.
The list of available models.
List of available models.
Show child attributes
Show child attributes
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