curl --request POST \
  --url https://open.bigmodel.cn/api/paas/v4/tokenizer \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "glm-5.3",
  "messages": [
    {
      "role": "user",
      "content": "What opportunities and challenges will the Chinese large model industry face in 2025?"
    }
  ]
}
'

import requests

url = "https://open.bigmodel.cn/api/paas/v4/tokenizer"

payload = {
    "model": "glm-5.3",
    "messages": [
        {
            "role": "user",
            "content": "What opportunities and challenges will the Chinese large model industry face in 2025?"
        }
    ]
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: 'glm-5.3',
    messages: [
      {
        role: 'user',
        content: 'What opportunities and challenges will the Chinese large model industry face in 2025?'
      }
    ]
  })
};

fetch('https://open.bigmodel.cn/api/paas/v4/tokenizer', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

HttpResponse<String> response = Unirest.post("https://open.bigmodel.cn/api/paas/v4/tokenizer")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"glm-5.3\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"What opportunities and challenges will the Chinese large model industry face in 2025?\"\n    }\n  ]\n}")
  .asString();

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://open.bigmodel.cn/api/paas/v4/tokenizer"

	payload := strings.NewReader("{\n  \"model\": \"glm-5.3\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"What opportunities and challenges will the Chinese large model industry face in 2025?\"\n    }\n  ]\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

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

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

	fmt.Println(string(body))

}

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://open.bigmodel.cn/api/paas/v4/tokenizer",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'model' => 'glm-5.3',
    'messages' => [
        [
                'role' => 'user',
                'content' => 'What opportunities and challenges will the Chinese large model industry face in 2025?'
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

{
  "id": "20241120141244890ab4ee4af84acf",
  "usage": {
    "prompt_tokens": 123,
    "video_tokens": 123,
    "image_tokens": 123,
    "total_tokens": 123
  },
  "created": 1727156815,
  "request_id": "1"
}

{
  "error": {
    "code": "<string>",
    "message": "<string>"
  }
}