GLM 4.7 vs GPT-5 Mini
Pricing, context window and real answers (September 2026)
GLM 4.7 (Z.ai) and GPT-5 Mini (OpenAI), 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 |  GPT-5 Mini | |
|---|---|---|
| Provider | Z.ai | OpenAI |
| Input (per 1M tokens) | ¥107.22 | ¥44.68 |
| Output (per 1M tokens) | ¥393.14 | ¥357.4 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥304 | ¥223 |
| Context window | 202,752 tokens | 400,000 tokens |
| Release date | 12/22/2025 | 8/7/2025 |
| Input modalities | text | text, image, file |
| Throughput (p50) | — | — |
| Arena · overall | #83 · ELO 1,442 | #163 · ELO 1,390 |
| Arena · Japanese | Unranked | #109 · ELO 1,365 |
| Arena · coding | #91 · ELO 1,485 | #172 · ELO 1,431 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-5 Mini: ¥357.4 per 1M output tokens, 9% less than GLM 4.7.
- On the Overall arena board, GLM 4.7 ranks higher (#83; GPT-5 Mini is #163).
- On the Coding arena board, GLM 4.7 ranks higher (#91; GPT-5 Mini is #172).
- For long documents, GPT-5 Mini: a 400,000-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
GPT-5 Mini
We examine the word "strawberry" letter by letter:
1. s — not an r (count = 0)
2. t — not an r (count = 0)
3. r — an r (count = 1)
4. a — not an r (count = 1)
5. w — not an r (count = 1)
6. b — not an r (count = 1)
7. e — not an r (count = 1)
8. r — an r (count = 2)
9. r — an r (count = 3)
10. y — not an r (count = 3)
Total number of 'r's = 3.
5.2s382 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
GPT-5 Mini
That error means users is undefined when you call users.map(...). map is an Array method, so calling it on undefined throws "Cannot read properties of undefined (reading 'map')".
Common causes
- The parent component didn't pass a users prop.
- users is still loading (e.g. fetched asynchronously) and is null/undefined until the fetch completes.
- The parent initialized users to null instead of an empty array.
How to fix
Choose one or more of these approaches depending on your app:
1) Initialize the parent state as an array
If users is state in the parent, initialize it to [] so the child always receives an array:
const [users, setUsers] = useState([]);
// fetch and setUsers(data)
2) Give…
8.0s966 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
GPT-5 Mini
Thanks — this is a nice simple function, but it can be improved in several ways: move imports to module scope, avoid broad except:, use connection pooling (Session) for performance, use specific exception types, add logging and docstring, avoid comparing to True, use list comprehensions, validate JSON shape, and implement backoff (or use urllib3 Retry).
Below are two improved alternatives and a short rationale for the changes.
1) A simple, clear improvement (small changes, explicit errors, backoff + jitter)
- Moves imports to top-level
- Uses requests.Session for connection pooling
- Catches specific exceptions (requests.RequestException, ValueError)
- Uses list comprehension and item.get(…
13.6s1702 output tokens
Frequently asked questions
- Which is cheaper, GLM 4.7 or GPT-5 Mini?
- Per 1M output tokens, GLM 4.7 is ¥393.14 and GPT-5 Mini is ¥357.4 on FastMetal (yen, before tax), so GPT-5 Mini is cheaper.
- How do the context windows of GLM 4.7 and GPT-5 Mini compare?
- GLM 4.7 takes 202,752 tokens; GPT-5 Mini takes 400,000.
- Which ranks higher, GLM 4.7 or GPT-5 Mini?
- GLM 4.7 ranks higher on the public arena (GLM 4.7 #83, GPT-5 Mini #109). Ranks move as the leaderboard updates.
- Can I use GLM 4.7 and GPT-5 Mini with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-4.7" or "gpt-5-mini" 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 GPT-5 Mini from the browser chat and the API. No monthly fee.