GLM 4.7 (FP8) - GMI Cloud Documentation

Model ID

zai-org/GLM-4.7-FP8

API Usage

You can interact with the DeepSeek R1 0528 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 DeepSeek-V3.2.

Shell

curl --request POST \
  --url https://api.gmi-serving.com/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer *************' \
  --data '{
    "model": "deepseek-ai/DeepSeek-V3.2",
    "messages": [
      {"role": "system", "content": "You are a helpful AI assistant"},
      {"role": "user", "content": "List 3 countries and their capitals."}
    ],
    "temperature": 0,
    "max_tokens": 500
  }'

Python

import requests
import json

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

payload = {
    "model": "deepseek-ai/DeepSeek-V3.2",
    "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))