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Documentation Index

Fetch the complete documentation index at: https://docs.gmicloud.ai/llms.txt

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Model ID 
google/gemma-4-31b

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API Usage

You can interact with the Gemma 4 31B model through our OpenAI-compatible APIs. Below are examples showing how to use the model’s API.

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API Examples

Generate a model response using the chat endpoint of Gemma 4 31B.

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Shell

curl --request POST \
  --url https://api.gmi-serving.com/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer *************' \
  --data '{
    "model": "google/gemma-4-31b",
    "messages": [
      {"role": "system", "content": "You are a helpful AI assistant"},
      {"role": "user", "content": "List 3 countries and their capitals."}
    ],
    "temperature": 0,
    "max_tokens": 500
  }'

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example for function call

# 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 '{
    "temperature": 0,
    "max_tokens": 200,
    "model": "google/gemma-4-31b",
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get weather in a location",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {
                            "type": "string",
                            "description": "The city, e.g. San Francisco"
                        }
                    },
                    "required": [
                        "location"
                    ]
                }
            }
        }
    ],
    "messages": [
        {
            "role": "user",
            "content": "What is the weather in San Francisco?"
        }
    ]
}'

​
Python

import requests
import json

url = "https://api.gmi-serving.com/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer *************"
}

payload = {
    "model": "google/gemma-4-31b",
    "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))