glm-5.3-flash: Responses
curl --request POST \
--url https://api.zerogpu.ai/v1/responses \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"input": "Hello!",
"model": "glm-5.3-flash"
}
'import requests
url = "https://api.zerogpu.ai/v1/responses"
payload = {
"input": "Hello!",
"model": "glm-5.3-flash"
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({input: 'Hello!', model: 'glm-5.3-flash'})
};
fetch('https://api.zerogpu.ai/v1/responses', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));falsepackage main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.zerogpu.ai/v1/responses"
payload := strings.NewReader("{\n \"input\": \"Hello!\",\n \"model\": \"glm-5.3-flash\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
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))
}require 'uri'
require 'net/http'
url = URI("https://api.zerogpu.ai/v1/responses")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"input\": \"Hello!\",\n \"model\": \"glm-5.3-flash\"\n}"
response = http.request(request)
puts response.read_body{}{}By model
glm-5.3-flash
Model details for glm-5.3-flash. Coding and long-horizon agent tasks with a 1M-token context window.
POST
/
responses
glm-5.3-flash: Responses
curl --request POST \
--url https://api.zerogpu.ai/v1/responses \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"input": "Hello!",
"model": "glm-5.3-flash"
}
'import requests
url = "https://api.zerogpu.ai/v1/responses"
payload = {
"input": "Hello!",
"model": "glm-5.3-flash"
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({input: 'Hello!', model: 'glm-5.3-flash'})
};
fetch('https://api.zerogpu.ai/v1/responses', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));falsepackage main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.zerogpu.ai/v1/responses"
payload := strings.NewReader("{\n \"input\": \"Hello!\",\n \"model\": \"glm-5.3-flash\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
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))
}require 'uri'
require 'net/http'
url = URI("https://api.zerogpu.ai/v1/responses")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"input\": \"Hello!\",\n \"model\": \"glm-5.3-flash\"\n}"
response = http.request(request)
puts response.read_body{}{}Z.ai’s GLM-5.3-Flash is an efficient open-weight model for coding and long-horizon agent tasks, served on ZeroGPU for general text generation. Its hybrid sparse and linear attention keeps long-context behaviour accurate across a 1,048,576-token (1M) window while reducing compute, and it supports function calling and adjustable reasoning effort.References: Model docs • Terms • Privacy
Authorizations
Headers
Optional project identifier. Scopes the request to a specific project when provided.
Body
application/json
Model identifier (fixed for this playground). Use request examples to change use cases.
Allowed value:
"glm-5.3-flash"Example:
"glm-5.3-flash"
Multi-line text or document content to send to the model.
Required string length:
1 - 131072Maximum number of tokens to generate in the response.
Required range:
x >= 1Example:
800
Response
Success
The response is of type object.

