glm-5.3-flash

Name: glm-5.3-flash API (AlphaTech Relay)
Brand: AlphaTech

Price verified

API model parameter

glm-5.3-flash

Input price (¥/1M)

¥0.4800

Output price (¥/1M)

¥1.68

Output/input ratio

×3.5

Pricing source: https://alphatech.net.cn/api/pricing, fetched at 2026-10-11T08:10:39.293Z. Group cn (group_ratio ×0.6); input USD/1M = 0.057143 × 2 × 0.6 = $0.0686; CNY converted at ¥7/USD.

Python SDK Quickstart

from openai import OpenAI

# Initialize the client against the AlphaTech relay endpoint
client = OpenAI(
    api_key="your_alphatech_api_key",
    base_url="https://alphatech.net.cn/v1"
)

# Send a streaming chat completion request
response = client.chat.completions.create(
    model="glm-5.3-flash",
    messages=[
        {"role": "system", "content": "You are an AI assistant routed via AlphaTech."},
        {"role": "user", "content": "Briefly describe your key characteristics."}
    ],
    temperature=0.7,
    stream=True
)

for chunk in response:
    content = chunk.choices[0].delta.content or ""
    print(content, end="", flush=True)

cURL Request

curl https://alphatech.net.cn/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your_alphatech_api_key" \
  -d '{
    "model": "glm-5.3-flash",
    "messages": [{"role": "user", "content": "Hello via AlphaTech"}]
  }'

Node.js / TypeScript SDK Integration

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.ALPHATECH_API_KEY,
  baseURL: 'https://alphatech.net.cn/v1'
});

async function main() {
  const stream = await client.chat.completions.create({
    model: 'glm-5.3-flash',
    messages: [{ role: 'user', content: 'Explain distributed consensus algorithms.' }],
    stream: true,
  });

  for await (const chunk of stream) {
    process.stdout.write(chunk.choices[0]?.delta?.content || '');
  }
}

main();

Get a glm-5.3-flash API key

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