curl --request GET \
  --url https://llm-gateway.assemblyai.com/v1/models

import requests

url = "https://llm-gateway.assemblyai.com/v1/models"

response = requests.get(url)

print(response.text)

const options = {method: 'GET'};

fetch('https://llm-gateway.assemblyai.com/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://llm-gateway.assemblyai.com/v1/models",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
]);

$response = curl_exec($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://llm-gateway.assemblyai.com/v1/models"

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

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://llm-gateway.assemblyai.com/v1/models")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://llm-gateway.assemblyai.com/v1/models")

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

request = Net::HTTP::Get.new(url)

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

{
  "data": [
    {
      "id": "qwen3.5-4b-32k-fast",
      "name": "Qwen3.5 4B Fast",
      "description": "",
      "creator": "Qwen",
      "context_length": 32768,
      "supported_parameters": [
        "max_tokens",
        "temperature",
        "stream"
      ],
      "default_parameters": {
        "temperature": null,
        "top_p": null,
        "frequency_penalty": null
      },
      "top_provider": {
        "is_moderated": false,
        "context_length": 32768,
        "max_completion_tokens": 8192
      },
      "pricing": {
        "global": {
          "prompt": 0.1,
          "completions": 0.5
        }
      },
      "retirement_date": 0,
      "available_regions": [
        "us",
        "eu"
      ],
      "providers": [
        {
          "id": "assemblyai",
          "name": "AssemblyAI"
        }
      ],
      "default_provider": {
        "id": "assemblyai",
        "name": "AssemblyAI"
      },
      "date_added": null,
      "performance": {
        "status": "beta",
        "data": [
          {
            "model": "qwen3.5-4b-32k-fast",
            "reasoning_effort": "default",
            "bucket": "30s",
            "quality_score": 74,
            "total_cost_usd": 0.006874,
            "cost_per_quality": 0.00009289,
            "hourly_prompt_tokens": 13717,
            "hourly_completion_tokens": 2911,
            "cost_per_hour_usd": 0.00262,
            "latency": {
              "n": 100,
              "min": 0.14,
              "max": 0.675,
              "mean": 0.33,
              "p50": 0.28,
              "p95": 0.573
            },
            "tokens_per_second": 186.145,
            "ttft": {
              "n": 50,
              "min": 0.058,
              "max": 0.325,
              "mean": 0.138,
              "p50": 0.108,
              "p95": 0.322
            },
            "task_quality": {
              "dictation": 81,
              "information_extraction": 80,
              "summarization": 76,
              "text_correction": 62
            },
            "task_cost_usd": {
              "dictation": 0.002237,
              "information_extraction": 0.001633,
              "summarization": 0.001248,
              "text_correction": 0.001756
            },
            "task_cost_per_quality": {
              "dictation": 0.00006904,
              "information_extraction": 0.0001021,
              "summarization": 0.00008211,
              "text_correction": 0.0001416
            },
            "task_cost_per_hour_usd": {
              "dictation": 0.002114,
              "information_extraction": 0.002742,
              "summarization": 0.002768,
              "text_correction": 0.003383
            }
          }
        ]
      }
    },
    {
      "id": "claude-sonnet-4-6",
      "name": "Sonnet 4.6",
      "description": "",
      "creator": "Claude",
      "context_length": 200000,
      "supported_parameters": [
        "max_tokens",
        "temperature",
        "tools",
        "tool_choice",
        "response_format",
        "stream"
      ],
      "default_parameters": {
        "temperature": null,
        "top_p": null,
        "frequency_penalty": null
      },
      "top_provider": {
        "is_moderated": false,
        "context_length": 200000,
        "max_completion_tokens": 128000
      },
      "pricing": {
        "global": {
          "prompt": 3,
          "completions": 15,
          "input_cache_read": 0.3,
          "input_cache_write": 3.75,
          "input_cache_write_1h": 6
        },
        "regional_increase_percent": 0.1
      },
      "retirement_date": 0,
      "available_regions": [
        "us",
        "eu",
        "global"
      ]
    },
    {
      "id": "gemini-2.5-flash-lite",
      "name": "Gemini 2.5 Flash Lite",
      "description": "",
      "creator": "Google",
      "context_length": 1048576,
      "supported_parameters": [
        "max_tokens",
        "response_format",
        "temperature",
        "tools",
        "tool_choice",
        "stream"
      ],
      "default_parameters": {
        "temperature": null,
        "top_p": null,
        "frequency_penalty": null
      },
      "top_provider": {
        "is_moderated": false,
        "context_length": 1048576,
        "max_completion_tokens": 65535
      },
      "pricing": {
        "global": {
          "prompt": 0.1,
          "completions": 0.4,
          "input_cache_read": 0.01
        },
        "regional_increase_percent": 0.1
      },
      "retirement_date": 0,
      "available_regions": [
        "us",
        "eu",
        "global"
      ]
    }
  ]
}

{
  "code": 123,
  "message": "<string>",
  "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "metadata": {
    "errors": [
      "<string>"
    ]
  }
}