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Model ID 
zai-org/GLM-4.5-FP8

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API Usage

You can access GLM-4.5-FP8 through the same RESTful Chat Completions API used by other GLM models.
The following examples demonstrate text generation and function-calling usage.

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API Examples

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Generate a Chat Completion

Use the chat completion endpoint to generate responses from GLM-4.5-FP8.

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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": "zai-org/GLM-4.5-FP8",
    "messages": [
      {"role": "system", "content": "You are a knowledgeable AI assistant."},
      {"role": "user", "content": "Explain the concept of quantum entanglement in simple terms."}
    ],
    "temperature": 0.7,
    "max_tokens": 800
  }'
Function Calling
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": 100,
    "model": "zai-org/GLM-4.5-FP8",
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "get_stock_price",
                "description": "Retrieve the current stock price for a given company.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "symbol": {
                            "type": "string",
                            "description": "Ticker symbol of the company, e.g., AAPL or TSLA."
                        }
                    },
                    "required": ["symbol"]
                }
            }
        }
    ],
    "messages": [
        {
            "role": "user",
            "content": "What is the current price of Apple stock?"
        }
    ]
}'

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Python SDK Usage

import requests
import json

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

payload = {
    "model": "zai-org/GLM-4.5-FP8",
    "messages": [
        {"role": "system", "content": "You are a knowledgeable AI assistant."},
        {"role": "user", "content": "Explain the concept of quantum entanglement in simple terms."}
    ],
    "temperature": 0.7,
    "max_tokens": 800
}

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

print(json.dumps(response.json(), indent=2))