Instead of ‘login’ and ‘password’ use your credentials from https://app.dataforseo.com/api-access

# Instead of 'login' and 'password' use your credentials from https://app.dataforseo.com/api-access
login="login"
password="password"
cred="$(printf ${login}:${password} | base64)"
curl --location --request GET "https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models" \
--header "Authorization: Basic ${cred}" \
--header "Content-Type: application/json" \
--data-raw ''

<?php
// You can download this file from here https://cdn.dataforseo.com/v3/examples/php/php_RestClient.zip
require('RestClient.php');
$api_url = 'https://api.dataforseo.com/';
try {
	// Instead of 'login' and 'password' use your credentials from https://app.dataforseo.com/api-access
	$client = new RestClient($api_url, null, 'login', 'password');
} catch (RestClientException $e) {
	echo "n";
	print "HTTP code: {$e->getHttpCode()}n";
	print "Error code: {$e->getCode()}n";
	print "Message: {$e->getMessage()}n";
	print  $e->getTraceAsString();
	echo "n";
	exit();
}
try {
	// using this method you can get a list of ai models
	// GET /v3/ai_optimization/chat_gpt/llm_responses/models
	// the full list of possible parameters is available in documentation
	$result = $client->get('/v3/ai_optimization/chat_gpt/llm_responses/models');
	print_r($result);
	// do something with result
} catch (RestClientException $e) {
	echo "n";
	print "HTTP code: {$e->getHttpCode()}n";
	print "Error code: {$e->getCode()}n";
	print "Message: {$e->getMessage()}n";
	print  $e->getTraceAsString();
	echo "n";
}
$client = null;
?>

"""
Method: GET
Endpoint: https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models
@see https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models
"""

import sys
import os
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../../../../../')))
from lib.client import RestClient
from lib.config import username, password
client = RestClient(username, password)

try:
    response = client.get('/v3/ai_optimization/chat_gpt/llm_responses/models')
    print(response)
    # do something with get result
except Exception as e:
    print(f'An error occurred: {e}')

const axios = require('axios');

axios({
    method: 'get',
    url: 'https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models',
    auth: {
        username: 'login',
        password: 'password'
    },
    data: [{
        version: "v3"
    }],
    headers: {
        'content-type': 'application/json'
    }
}).then(function (response) {
    var result = response['data']['tasks'][0]['result'];
    // Result data
    console.log(result);
}).catch(function (error) {
    console.log(error);
});

using System;
using System.Linq;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Text;
using System.Collections.Generic;
using System.Threading.Tasks;
using Newtonsoft.Json;
namespace DataForSeoSdk;

public class AiOptimization
{

    private static readonly HttpClient _httpClient;
    
    static AiOptimization()
    {
        _httpClient = new HttpClient
        {
            BaseAddress = new Uri("https://api.dataforseo.com/")
        };
        _httpClient.DefaultRequestHeaders.Authorization =
            new AuthenticationHeaderValue("Basic", ApiConfig.Base64Auth);
    }

    /// <summary>
    /// Method: GET
    /// Endpoint: https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models
    /// </summary>
    /// <see href="https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/models"/>
    
    public static async Task ChatGptLlmResponsesModels()
    {
        using var response = await _httpClient.GetAsync("/v3/ai_optimization/chat_gpt/llm_responses/models");
        var result = JsonConvert.DeserializeObject<dynamic>(await response.Content.ReadAsStringAsync());
        // you can find the full list of the response codes here https://docs.dataforseo.com/v3/appendix/errors
        if (result.status_code == 20000)
        {
            // do something with result
            Console.WriteLine(result);
        }
        else
            Console.WriteLine($"error. Code: {result.status_code} Message: {result.status_message}");
    }

The above command returns JSON structured like this:

{
  "version": "0.1.20250526",
  "status_code": 20000,
  "status_message": "Ok.",
  "time": "0.0857 sec.",
  "cost": 0,
  "tasks_count": 1,
  "tasks_error": 0,
  "tasks": [
    {
      "id": "07211850-1535-0616-0000-f939ddd1730c",
      "status_code": 20000,
      "status_message": "Ok.",
      "time": "0.0339 sec.",
      "cost": 0,
      "result_count": 30,
      "path": [
        "v3",
        "ai_optimization",
        "chat_gpt",
        "llm_responses",
        "models"
      ],
      "data": {
        "api": "ai_optimization",
        "function": "llm_responses",
        "se": "chat_gpt"
      },
      "result": [
        {
          "model_name": "o4-mini",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "o4-mini-2025-04-16",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "o3-mini",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "o3-mini-2025-01-31",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "o1-pro",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "o1-pro-2025-03-19",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "o1",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "o1-2024-12-17",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4o-mini",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4o-mini-2024-07-18",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4o",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4.1-nano",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4.1-mini",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4.1-mini-2025-04-14",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4.1",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4.1-2025-04-14",
          "web_search_supported": true,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4-turbo",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4-turbo-2024-04-09",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-4-0613",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-3.5-turbo",
          "web_search_supported": false,
          "task_post_supported": true
        },
        {
          "model_name": "gpt-3.5-turbo-16k",
          "web_search_supported": false,
          "task_post_supported": false
        }
      ]
    }
  ]
}