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Model ID 
Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8
Significant Performance among open models on Agentic Coding, Agentic Browser-Use, and other foundational coding tasks. Long-context Capabilities with native support for 256K tokens, extendable up to 1M tokens using Yarn, optimized for repository-scale understanding. Agentic Coding supporting for most platform such as Qwen Code, CLINE, featuring a specially designed function call format.

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API Usage

You can interact with the Qwen3-Coder-480B-A35B-Instruct-FP8 model through various programming languages and methods. 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 Qwen3-Coder-480B-A35B-Instruct-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": "Qwen/Qwen3-Coder-480B-A35B-Instruct-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
  }'

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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-Coder-480B-A35B-Instruct-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))