đź“– Tutorial
June 20, 2026 · 6 min read

GLM-5 API Guide: How to Use Zhipu's Best Multilingual Model

Everything you need to start building with Zhipu AI's flagship GLM-5 model — the best multilingual Chinese LLM available. Python, Node.js, and cURL examples included.

đź“‘ Table of Contents

1. What is GLM-5? 2. Getting Started 3. Code Examples 3.1 cURL Example 3.2 Python Example 3.3 Node.js Example 4. GLM Family Pricing 5. Key Features 6. Best Use Cases 7. GLM-5 vs GPT-4o

GLM-5: $0.25/M input · 128K context · Best multilingual · $0.48/M Flash

1. What is GLM-5?

GLM-5 is Zhipu AI's flagship large language model, developed by the Tsinghua-affiliated team (清华系) that has been at the forefront of Chinese AI research. As the fifth generation in the GLM (General Language Model) series, GLM-5 represents a significant leap forward in multilingual capabilities.

Unlike many Chinese LLMs that struggle with non-Chinese languages, GLM-5 delivers excellent multilingual performance across English, Chinese, Japanese, French, and more. It's particularly strong at translation, summarization, and content generation — making it the go-to choice for international teams working across language barriers.

For developers who need faster responses or have budget constraints, Zhipu also offers GLM-5 Flash — a lighter, faster variant at just $0.12 per million input tokens. Flash maintains strong quality while delivering higher throughput for production workloads.

GLM-5 excels at:

💡 GLM-5 is available through tokencnn.com's OpenAI-compatible API — drop-in replacement, no code changes needed.

2. Getting Started

Getting started with GLM-5 is quick and straightforward. No Chinese phone number required — just an email address.

  1. Sign up at tokencnn.com — only your email is required, no phone verification needed.
  2. Navigate to API Keys in your dashboard and click Generate new key.
  3. Save your key — it will look like sk-xxx.... Store it securely and never commit it to version control.
  4. Use the endpoint — point your client to https://www.tokencnn.com/v1 with the model name glm-5 or glm-5-flash.

⚠️ Keep your API key safe. Never expose it in client-side code or public repositories. Use environment variables in production.

3. Code Examples

GLM-5 uses the standard OpenAI-compatible chat completions endpoint. Simply point your client to https://www.tokencnn.com/v1 and use the model name glm-5.

3.1 cURL Example

Quick test from your terminal:

curl https://www.tokencnn.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $YOUR_API_KEY" \
  -d '{
    "model": "glm-5",
    "messages": [
      {"role": "system", "content": "You are a helpful multilingual assistant."},
      {"role": "user", "content": "Translate 'Hello, how are you?' to Chinese and Japanese."}
    ]
  }'

đź’ˇ Replace $YOUR_API_KEY with your actual API key. Expect a JSON response with the assistant's reply in choices[0].message.content.

3.2 Python Example

Using the OpenAI Python SDK (v1.0+):

# pip install openai
from openai import OpenAI

client = OpenAI(
  base_url="https://www.tokencnn.com/v1",
  api_key="sk-your-api-key"
)

response = client.chat.completions.create(
  model="glm-5",
  messages=[{"role": "user", "content": "Explain quantum computing in simple terms."}]
)

print(response.choices[0].message.content)

Streaming example:

stream = client.chat.completions.create(
  model="glm-5",
  messages=[{"role": "user", "content": "Write a short poem about AI in both English and Chinese."}],
  stream=True
)
for chunk in stream:
  if chunk.choices[0].delta.content is not None:
    print(chunk.choices[0].delta.content, end="")

3.3 Node.js Example

Using the OpenAI Node.js SDK:

// npm install openai
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: 'https://www.tokencnn.com/v1',
  apiKey: 'sk-your-api-key',
});

async function main() {
  const completion = await client.chat.completions.create({
    model: "glm-5",
    messages: [{ role: "user", content: "What are the top 3 benefits of multilingual AI?" }],
  });
  console.log(completion.choices[0].message.content);
}
main();

💡 The GLM-5 API is fully OpenAI-compatible. If you've used GPT-4o or any OpenAI model before, you already know how to use it — just change the base_url and model name.

4. GLM Family Pricing

GLM-5 and GLM-5 Flash offer exceptional value — especially for multilingual tasks. Here's how they compare:

Model Input $/1M Output $/1M Best For
GLM-5 $0.25 $1.00 Multilingual, Complex
GLM-5 Flash $0.12 $0.48 Speed, Budget
GPT-4o $2.50 $10.00 Comparison baseline

💡 GLM-5 is 10x cheaper than GPT-4o on input tokens and 10x cheaper on output tokens. GLM-5 Flash is an even better deal at just $0.12/M input — perfect for high-volume production workloads.

5. Key Features

GLM-5 packs impressive capabilities tailored for multilingual and international workloads:

6. Best Use Cases

GLM-5's multilingual strengths make it particularly valuable for international and cross-border applications:

7. GLM-5 vs GPT-4o

How does GLM-5 stack up against OpenAI's flagship model? The answer might surprise you:

💡 For teams doing significant Chinese↔multilingual work, GLM-5 is the clear winner — better cultural understanding, comparable quality, and a fraction of the cost.

🚀 Get Your API Key

Start building with GLM-5 today. Sign up at tokencnn.com and get free credits instantly — no Chinese phone number needed.

🚀 Get Your API Key →