GLM 5.1 vs GPT-5 Mini
Pricing, context window and real answers (September 2026)
GLM 5.1 (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 5.1 |  GPT-5 Mini | |
|---|---|---|
| Provider | Z.ai | OpenAI |
| Input (per 1M tokens) | ¥250.18 | ¥44.68 |
| Output (per 1M tokens) | ¥786.28 | ¥357.4 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥643 | ¥223 |
| Context window | 204,800 tokens | 400,000 tokens |
| Release date | 4/7/2026 | 8/7/2025 |
| Input modalities | text | text, image, file |
| Throughput (p50) | — | — |
| Arena · overall | #47 · ELO 1,466 | #163 · ELO 1,390 |
| Arena · Japanese | #46 · ELO 1,434 | #109 · ELO 1,365 |
| Arena · coding | #45 · ELO 1,513 | #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, 55% less than GLM 5.1.
- On the Overall arena board, GLM 5.1 ranks higher (#47; GPT-5 Mini is #163).
- On the Japanese arena board, GLM 5.1 ranks higher (#46; GPT-5 Mini is #109).
- On the Coding arena board, GLM 5.1 ranks higher (#45; GPT-5 Mini is #172).
- For long documents, GPT-5 Mini: a 400,000-token context window against 204,800 for GLM 5.1.
- 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 5.1
There are **3** 'r's in the word "strawberry".
Here is the step-by-step reasoning:
1. Let's break down the word "strawberry" letter by letter: s - t - r - a - w - b - e - r - r - y
2. Now, let's check each letter one by one to see if it is an 'r':
- **s**: not an 'r'
- **t**: not an 'r'
- **r**: this is the 1st 'r'
- **a**: not an 'r'
- **w**: not an 'r'
- **b**: not an 'r'
- **e**: not an 'r'
- **r**: this is the 2nd 'r'
- **r**: this is the 3rd 'r'
- **y**: not an 'r'
3. Counting them up, there are three 'r's in total (in the 3rd, 8th, and 9th positions).
7.3s565 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 5.1
### What is causing the error?
The error `TypeError: Cannot read properties of undefined (reading 'map')` means you are trying to call the `.map()` method on a variable that is `undefined`.
In your code, the variable is `users`. When the `UserList` component renders, the `users` prop is `undefined`, so `undefined.map()` throws an error.
### Why is `users` undefined?
This usually happens for one of two reasons:
1. **You forgot to pass the prop:** The parent component rendering `<UserList />` is not passing the `users` attribute (e.g., `<UserList />` instead of `<UserList users={myUsers} />`).
2. **Async Data Fetching:** You are fetching the users from an API. On the initial render, befor…
45.0s1680 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 5.1
Here is a review of your function, broken down by areas for improvement, followed by a refactored version of the code.
### Key Areas for Improvement
1. **Imports Inside the Function:**
Placing `import` statements inside a function is generally discouraged in Python. It slows down the function execution every time it is called, and it violates PEP 8 (the Python style guide). Imports should always be at the top of the module.
2. **Bare `except` Clause:**
Using a bare `except:` catches *everything*, including `KeyboardInterrupt` and `SystemExit`, which makes it hard to terminate a hanging program. You should catch specific exceptions (like `requests.exceptions.RequestException`).
3. *…
70.3s2854 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 5.1 or GPT-5 Mini?
- Per 1M output tokens, GLM 5.1 is ¥786.28 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 5.1 and GPT-5 Mini compare?
- GLM 5.1 takes 204,800 tokens; GPT-5 Mini takes 400,000.
- Which ranks higher, GLM 5.1 or GPT-5 Mini?
- GLM 5.1 ranks higher on the public arena (GLM 5.1 #46, GPT-5 Mini #109). Ranks move as the leaderboard updates.
- Can I use GLM 5.1 and GPT-5 Mini with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.1" 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 5.1 and GPT-5 Mini from the browser chat and the API. No monthly fee.