GLM 4.7 vs GLM 5.2
Pricing, context window and real answers (August 2026)
GLM 4.7 (Z.ai) and GLM 5.2 (Z.ai), compared as you can actually call them on FastMetal. Both are served from the same OpenAI-compatible endpoint and API key; switching is a change to the model string.
Specs and pricing
 GLM 4.7 | GLM 5.2 | |
|---|---|---|
| Provider | Z.ai | Z.ai |
| Input (per 1M tokens) | ¥107.22 | ¥250.18 |
| Output (per 1M tokens) | ¥393.14 | ¥786.28 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥304 | ¥643 |
| Context window | 202,752 tokens | 1,048,576 tokens |
| Release date | 12/22/2025 | 6/16/2026 |
| Input modalities | text | text |
| Arena · overall | #79 · ELO 1,442 | #33 · ELO 1,472 |
| Arena · Japanese | Unranked | #26 · ELO 1,458 |
| Arena · coding | #87 · ELO 1,485 | #48 · ELO 1,508 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GLM 4.7: ¥393.14 per 1M output tokens, 50% less than GLM 5.2.
- On the Overall arena board, GLM 5.2 ranks higher (#33; GLM 4.7 is #79).
- On the Coding arena board, GLM 5.2 ranks higher (#48; GLM 4.7 is #87).
- For long documents, GLM 5.2: a 1,048,576-token context window against 202,752 for GLM 4.7.
- If in doubt, try both on the same key. Switching is a change to the model string, and each is billed at its own rate.
Real answers to the same prompts
Exactly what the FastMetal gateway returned, side by side. Not benchmark scores: actual output.
Count the number of 'r's in 'strawberry'
Count the number of 'r's in 'strawberry'. Explain your reasoning step by step.
GLM 4.7
There are **3** "r"s in "strawberry".
Here is the step-by-step reasoning:
1. **Break down the word into individual letters:**
s - t - r - a - w - b - e - r - r - y
2. **Identify the position of each 'r':**
* The 3rd letter is **r**.
* The 8th letter is **r**.
* The 9th letter is **r**.
3. **Count the total occurrences:**
1 + 1 + 1 = 3.
23.3s685 output tokens
GLM 5.2
To count the number of 'r's in the word 'strawberry', let's look at the word letter by letter:
1. **s** - no 'r'
2. **t** - no 'r'
3. **r** - this is the 1st 'r'
4. **a** - no 'r'
5. **w** - no 'r'
6. **b** - no 'r'
7. **e** - no 'r'
8. **r** - this is the 2nd 'r'
9. **r** - this is the 3rd 'r'
10. **y** - no 'r'
Total count: 3
There are **3** 'r's in the word 'strawberry'.
2.6s439 output tokens
Debug This Error
I'm getting the following error in my Node.js application: TypeError: Cannot read properties of undefined (reading 'map') at UserList (/app/components/UserList.js:12:25) at renderWithHooks (/app/node_modules/rea…
GLM 4.7
### The Cause
The error `TypeError: Cannot read properties of undefined (reading 'map')` means that the variable `users` is `undefined` when the component tries to render.
In React, this typically happens for one of two reasons:
1. The **Parent Component** is not passing the `users` prop to `UserList`.
2. The **Parent Component** passed the prop, but the data hasn't loaded yet (e.g., an API call is still pending), so the value is initially `undefined`.
Since `undefined` does not have a `.map()` method, the application crashes.
---
### How to Fix It
There are two main ways to fix this: handling it inside the `UserList` component (defensive coding) or fixing the parent component passing…
42.0s1384 output tokens
GLM 5.2
The error `TypeError: Cannot read properties of undefined (reading 'map')` happens because the `users` prop being passed to your `UserList` component is currently `undefined`. When JavaScript tries to call `.map()` on `undefined`, it throws this error.
Here are the best ways to fix this:
### Fix 1: Provide a default value (Recommended)
You can provide a default empty array `[]` when destructuring the props. This ensures that even if `users` is not passed down, the `.map()` function will still have an array to iterate over (resulting in an empty list rather than a crash).
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</…
8.3s1006 output tokens
Code Review
Please review the following Python function and suggest improvements for readability, performance, and best practices: def get_data(url, retries=3): import requests import time for i in range(retries):…
GLM 4.7
Here is a review of your function with suggestions for improving readability, performance, and best practices, followed by a refactored version of the code.
### Code Review
1. **Import Placement:** You import `requests` and `time` inside the function. Imports should generally be placed at the top of the file so they are loaded once when the module starts, rather than every time the function is called.
2. **Bare `except:`:** You used `except:` without specifying an exception type. This is dangerous because it catches *everything*, including `KeyboardInterrupt` (Ctrl+C) and `SystemExit`, preventing your program from terminating when needed. You should specifically catch `requests.exception…
24.5s2951 output tokens
GLM 5.2
Here is a review of your Python function, broken down by readability, performance, and best practices, followed by a refactored version of the code.
### 1. Best Practices
* **Move imports to the top:** Importing modules inside a function is generally discouraged. While Python caches imports, putting `import requests` and `import time` at the top of your file is the standard convention and improves readability.
* **Avoid bare `except:` blocks:** Using a bare `except:` catches everything, including `KeyboardInterrupt` and `SystemExit`. This makes it hard to interrupt your program if it gets stuck in a loop. You should catch specific exceptions, such as `requests.exceptions.RequestException` (…
10.9s2061 output tokens
Frequently asked questions
- Which is cheaper, GLM 4.7 or GLM 5.2?
- Per 1M output tokens, GLM 4.7 is ¥393.14 and GLM 5.2 is ¥786.28 on FastMetal (yen, before tax), so GLM 4.7 is cheaper.
- How do the context windows of GLM 4.7 and GLM 5.2 compare?
- GLM 4.7 takes 202,752 tokens; GLM 5.2 takes 1,048,576.
- Which ranks higher, GLM 4.7 or GLM 5.2?
- GLM 5.2 ranks higher on the public arena (GLM 4.7 #79, GLM 5.2 #26). Ranks move as the leaderboard updates.
- Can I use GLM 4.7 and GLM 5.2 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-4.7" or "glm-5.2" as the model. Each is billed at its own rate from the same prepaid balance.
Try both on one API key
Create an account and add credit to call GLM 4.7 and GLM 5.2 from the browser chat and the API. No monthly fee.