If you are looking for a GLM-5 tutorial for absolute beginners 2026, you are in the right place. We're going to show you how to get flagship-level AI performance without opening your wallet.

1. Why GLM-5 Matters Right Now

Let's skip the corporate talk. AI is getting incredibly expensive, and if you're a developer or a student, those monthly subscriptions add up fast. But what if I told you that one of the most powerful models on the planet—rivaling GPT-4 and Claude 3.5—is actually accessible for free?

Zhipu AI recently dropped GLM-5, and it’s a beast. It’s built on a Mixture-of-Experts (MoE) architecture, meaning it’s fast, smart, and handles massive codebases without breaking a sweat. If you want a free ai model for coding that actually works, this is where you start.

2. What exactly is GLM-5?

GLM stands for "General Language Model." GLM-5 is the latest iteration from Zhipu AI, and it’s specifically designed to handle "long-horizon" tasks. That's just a fancy way of saying it’s really good at following a complex plan over many steps without getting distracted or making things up.

Key details you should know:

Architecture: MoE with 40 billion active parameters (744B total).
Specialty: Systems engineering, math, and deep coding.
License: Open-source under MIT (unrestricted commercial use).

3. Ways to Access GLM-5 for Free

There are a few ways to get your hands on this model without touching your credit card:

z.ai Chat: Immediate access via a web interface.
BigModel API: 20 million free tokens for new developer accounts.
Local Run: Download quantized weights and run it on your own hardware.

4. Method 1: Using GLM-5 Online (The Easiest Way)

This is where I suggest everyone starts. It’s the closest experience to ChatGPT but with the GLM engine underneath.

1 Sign up on the Z.ai Platform

Go to z.ai or chat.zai. Registration usually takes less than a minute. You just need an email and a password. No phone number or credit card is required for the initial trial.

2 Choose the GLM-5 Model

In the chat window, look for the model selector (usually at the top). Make sure "GLM-5" is active. As of Feb 2026, it is prominently featured as their flagship experience.

Pro Tip: Use the "System Command" feature to set a role. For example: "You are a technical document writer. Use clear headings and avoid filler words."

5. Method 2: Using the GLM-5 API for Free

This is where it gets exciting for devs. If you want to know how to use GLM-5 for coding projects in 2026, the API is your best friend. Zhipu AI currently gives 20,000,000 free tokens to new users on their BigModel.cn platform.

1 Get your API Key

Log into your dashboard, navigate to "API Keys," and click "Create New."

2 Python Integration Example

For a basic automation script, Python is the way to go. Install the library first: pip install requests.

import requests

# Your free API key from BigModel.cn
API_KEY = "YOUR_KEY_HERE"
URL = "https://open.bigmodel.cn/api/paas/v4/chat/completions"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

data = {
    "model": "glm-5",
    "messages": [{"role": "user", "content": "Refactor this JS code to use async/await."}]
}

response = requests.post(URL, headers=headers, json=data)
print(response.json()['choices'][0]['message']['content'])

3 Node.js Integration Example

If you're building a web app, you'll probably want to use axios in Node.js.

const axios = require('axios');

const getAIResponse = async () => {
  const result = await axios.post('https://open.bigmodel.cn/api/paas/v4/chat/completions', {
    model: "glm-5",
    messages: [{ role: "user", content: "Explain React hooks simply." }]
  }, {
    headers: { 'Authorization': 'Bearer YOUR_KEY_HERE' }
  });
  
  console.log(result.data.choices[0].message.content);
};

getAIResponse();

6. Method 3: Running GLM-5 Locally

If you have the hardware, this is the ultimate glm 5 setup guide. Since GLM-5 is MIT-licensed, you can download it and keep it forever.

! Using Ollama

The easiest local method is Ollama. If you have it installed, just run:

ollama run glm5:8b-q4_K_M

Note: For the full flagship experience, you'll need multiple GPUs or a very high-end Mac Studio.

7. GLM-5 vs GPT-4 latency and cost comparison 2026

Why choose GLM-5? Here is the cold, hard data on how it compares to the industry standard.

Metric	GLM-5	GPT-4o
Input Cost (per 1M)	$1.00 (Often free trial)	~$30.00
Comparison	30x Cheaper	Expensive baseline
Max Context	200,000 Tokens	128,000 Tokens
Latency	~50 tokens/sec (MoE)	Highly variable

As you can see, if you want a cost-effective ai agents solution, GLM-5 is the winner. For a deeper look at the rivals, check out our comparison of Qwen 3.5 vs GPT-4 vs Claude 4.5.

8. Best Use Cases for GLM-5

From our testing at Cloudvyn, we've found it excels at:

Repository-Scale Refactoring: Throwing 50 files at it and asking for a structural change.
Native Multimodal Tasks: Showing it a UI screenshot and getting back the CSS.
Building Private Agents: If you don't want your data leaving your server, local GLM-5 is perfect. See our guide on how to Build Your Own AI Agent for more.

Also, don't miss our breakdown of GLM-5 vs Kimi k2.5 if you're comparing regional leaders.

9. Things to Remember

While the use glm 5 api free credits are generous, they aren't infinite. Once you hit 20 million tokens, you'll need to pay or wait for new promotions. Also, setting it up locally still requires a solid understanding of Python and CUDA drivers.

Ready to Start?

Jump into the DeepSeek V4 vs Qwen 3.5 debate with some firsthand experience. Go to DeepSeek V4 vs Qwen 3.5 to see where GLM-5 fits in the bigger picture.

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