Documentation Index
Fetch the complete documentation index at: https://docs.gmicloud.ai/llms.txt
Use this file to discover all available pages before exploring further.
Model ID
API Usage
You can interact with the Qwen3-32B-FP8 model through various programming languages and methods. Below are examples showing how to use the model’s API.
API Examples
Generate a model response using the chat endpoint of Qwen3-32B-FP8.
Shell
curl --request POST \
--url https://api.gmi-serving.com/v1/chat/completions \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer *************' \
--data '{
"model": "Qwen/Qwen3-32B-FP8",
"messages": [
{"role": "system", "content": "You are a helpful AI assistant"},
{"role": "user", "content": "List 3 countries and their capitals."}
],
"temperature": 0,
"max_tokens": 500
}'
# example for function call
curl --request POST \
--url https://api.gmi-serving.com/v1/chat/completions \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer *************' \
--data '{
"model": "Qwen/Qwen3-235B-A22B-FP8",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "What is the weather like in San Francisco?"
}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g., San Francisco, CA"
},
"unit": {
"type": "string",
"enum": [
"celsius",
"fahrenheit"
],
"description": "The temperature unit to use"
}
},
"required": [
"location"
]
}
}
}
],
"tool_choice": "auto"
}'
Python
import requests
import json
url = "https://api.gmi-serving.com/v1/chat/completions"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer *************"
}
payload = {
"model": "Qwen/Qwen3-32B-FP8",
"messages": [
{"role": "system", "content": "You are a helpful AI assistant"},
{"role": "user", "content": "List 3 countries and their capitals."}
],
"temperature": 0,
"max_tokens": 500
}
response = requests.post(url, headers=headers, json=payload)
print(json.dumps(response.json(), indent=2))