List Models

curl --request GET \
  --url https://api.venice.ai/api/v1/models \
  --header 'Authorization: Bearer <token>'

import requests

url = "https://api.venice.ai/api/v1/models"

headers = {"Authorization": "Bearer <token>"}

response = requests.get(url, headers=headers)

print(response.text)

const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};

fetch('https://api.venice.ai/api/v1/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.venice.ai/api/v1/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 => [
    "Authorization: Bearer <token>"
  ],
]);

$response = curl_exec($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.venice.ai/api/v1/models"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("Authorization", "Bearer <token>")

	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.venice.ai/api/v1/models")
  .header("Authorization", "Bearer <token>")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.venice.ai/api/v1/models")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer <token>'

response = http.request(request)
puts response.read_body

{
  "data": [
    {
      "created": 1727966436,
      "id": "llama-3.2-3b",
      "model_spec": {
        "availableContextTokens": 131072,
        "capabilities": {
          "optimizedForCode": false,
          "quantization": "fp16",
          "supportsAudioInput": false,
          "supportsFunctionCalling": true,
          "supportsLogProbs": true,
          "supportsMultipleImages": false,
          "supportsReasoning": false,
          "supportsReasoningEffort": false,
          "supportsResponseSchema": true,
          "supportsTeeAttestation": false,
          "supportsE2EE": false,
          "supportsVision": false,
          "supportsVideoInput": false,
          "supportsWebSearch": true,
          "supportsXSearch": false
        },
        "constraints": {
          "temperature": {
            "default": 0.8
          },
          "top_p": {
            "default": 0.9
          }
        },
        "description": "Compact and efficient model for quick responses and lighter workloads.",
        "name": "Llama 3.2 3B",
        "modelSource": "https://huggingface.co/meta-llama/Llama-3.2-3B",
        "offline": false,
        "privacy": "private",
        "pricing": {
          "input": {
            "usd": 0.15,
            "diem": 0.15
          },
          "output": {
            "usd": 0.6,
            "diem": 0.6
          }
        },
        "traits": [
          "fastest"
        ]
      },
      "object": "model",
      "owned_by": "venice.ai",
      "type": "text"
    }
  ],
  "object": "list",
  "type": "text"
}

{
  "error": "<string>"
}