gpt-oss-120b: Responses
curl --request POST \
--url https://api.zerogpu.ai/v1/responses \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"input": "Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.",
"model": "gpt-oss-120b"
}
'import requests
url = "https://api.zerogpu.ai/v1/responses"
payload = {
"input": "Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.",
"model": "gpt-oss-120b"
}
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: 'Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.',
model: 'gpt-oss-120b'
})
};
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\": \"Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.\",\n \"model\": \"gpt-oss-120b\"\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\": \"Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.\",\n \"model\": \"gpt-oss-120b\"\n}"
response = http.request(request)
puts response.read_body{
"id": "id-1784318124857",
"object": "response",
"created_at": 1784318124,
"model": "gpt-oss-120b",
"status": "completed",
"instructions": "You are a witty naming consultant. Be brief.",
"output": [
{
"id": "rs_8d4dc6f3f33d0d28",
"type": "reasoning",
"content": [
{
"type": "reasoning_text",
"text": "We need to respond with a top 3 WiFi names that will make neighbors laugh, each with a one-line reason. Be witty. Keep brief."
}
]
},
{
"id": "msg_9c3dfbf63445d80a",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "**1. “FBI Surveillance Van #42”** – Neighbors will double-check the street before they even think about streaming.\n\n**2. “Drop It Like It’s Hotspot”** – A pun that’s so cheesy it’ll have the whole block groaning and giggling.\n\n**3. “Tell My Wi-Fi I Love You”** – Because nothing says “I’m caring” like a reminder that even your router needs affection."
}
]
}
],
"usage": {
"input_tokens": 0,
"output_tokens": 0,
"total_tokens": 0
}
}{}By model
gpt-oss-120b
Model details for gpt-oss-120b. Function calling, batch tasks, and reasoning with a 131K context window.
POST
/
responses
gpt-oss-120b: Responses
curl --request POST \
--url https://api.zerogpu.ai/v1/responses \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"input": "Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.",
"model": "gpt-oss-120b"
}
'import requests
url = "https://api.zerogpu.ai/v1/responses"
payload = {
"input": "Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.",
"model": "gpt-oss-120b"
}
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: 'Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.',
model: 'gpt-oss-120b'
})
};
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\": \"Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.\",\n \"model\": \"gpt-oss-120b\"\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\": \"Name my WiFi network something that will make my neighbors laugh. Give me your top 3 with a one-line reason each.\",\n \"model\": \"gpt-oss-120b\"\n}"
response = http.request(request)
puts response.read_body{
"id": "id-1784318124857",
"object": "response",
"created_at": 1784318124,
"model": "gpt-oss-120b",
"status": "completed",
"instructions": "You are a witty naming consultant. Be brief.",
"output": [
{
"id": "rs_8d4dc6f3f33d0d28",
"type": "reasoning",
"content": [
{
"type": "reasoning_text",
"text": "We need to respond with a top 3 WiFi names that will make neighbors laugh, each with a one-line reason. Be witty. Keep brief."
}
]
},
{
"id": "msg_9c3dfbf63445d80a",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "**1. “FBI Surveillance Van #42”** – Neighbors will double-check the street before they even think about streaming.\n\n**2. “Drop It Like It’s Hotspot”** – A pun that’s so cheesy it’ll have the whole block groaning and giggling.\n\n**3. “Tell My Wi-Fi I Love You”** – Because nothing says “I’m caring” like a reminder that even your router needs affection."
}
]
}
],
"usage": {
"input_tokens": 0,
"output_tokens": 0,
"total_tokens": 0
}
}{}OpenAI’s gpt-oss-120b is an open-weight Mixture-of-Experts model with 117B total parameters (5.1B active per token), served on ZeroGPU for general text generation. It reasons through a problem before answering and returns that reasoning trace alongside the final answer, and it supports function calling, batch tasks, and a 131,072-token context window. When a task needs frontier-level reasoning or tool use beyond what the smaller edge models cover, this is the model.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:
"gpt-oss-120b"Example:
"gpt-oss-120b"
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.

