GLM 5.1 vs Mercury 2.5
Pricing, context window and real answers (September 2026)
GLM 5.1 (Z.ai) and Mercury 2.5 (Inception), 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 | Mercury 2.5 | |
|---|---|---|
| Provider | Z.ai | Inception |
| Input (per 1M tokens) | ¥250.18 | ¥6.77 |
| Output (per 1M tokens) | ¥786.28 | ¥25.38 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥643 | ¥19 |
| Context window | 204,800 tokens | 260,000 tokens |
| Release date | 4/7/2026 | 9/8/2026 |
| Input modalities | text | text |
| Arena · overall | #44 · ELO 1,466 | Unranked |
| Arena · Japanese | #45 · ELO 1,434 | Unranked |
| Arena · coding | #37 · ELO 1,514 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Mercury 2.5: ¥25.38 per 1M output tokens, 97% less than GLM 5.1.
- For long documents, Mercury 2.5: a 260,000-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
Mercury 2.5
To determine the number of 'r's in the word "strawberry", we can examine each letter in sequence:
1. **s** - Not 'r'
2. **t** - Not 'r'
3. **r** - First 'r' found
4. **a** - Not 'r'
5. **w** - Not 'r'
6. **b** - Not 'r'
7. **e** - Not 'r'
8. **r** - Second 'r' found
9. **r** - Third 'r' found
10. **y** - Not 'r'
Counting these occurrences, there are **3** 'r's in "strawberry".
1.8s968 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
Mercury 2.5
This error occurs because the `users` prop is `undefined` when the component renders. Since the code calls `.map()` on `users`, JavaScript throws a TypeError when `users` is not an array.
Here is how to fix it:
1. **Set a Default Value**
Update the function signature to default `users` to an empty array if it is not provided:
```javascript
function UserList({ users = [] }) {
// ...
}
```
2. **Add a Conditional Check**
If `users` might be null or undefined during data loading, guard the map operation:
```javascript
{users && users.map(user => <li key={user.id}>{user.name}</li>)}
```
3. **Verify Parent Props**
Ensure the parent component pas…
2.4s1028 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
Mercury 2.5
Here is a review of the function with suggestions for improvement.
### Key Observations
1. **Imports:** Libraries should be imported at the module level, not inside functions.
2. **Exception Handling:** Bare `except:` clauses catch system exits and interrupts. Use specific exceptions like `requests.exceptions.RequestException`.
3. **Logic & Pythonicity:**
* Avoid `== True`; rely on truthiness or `item.get("active")`.
* List comprehensions are more concise and efficient than manual appending.
4. **Retry Strategy:** Implement exponential backoff instead of fixed sleeps, and avoid sleeping after the final failed attempt.
5. **Documentation:** Add type hints and a docstring fo…
4.6s1999 output tokens
Frequently asked questions
- Which is cheaper, GLM 5.1 or Mercury 2.5?
- Per 1M output tokens, GLM 5.1 is ¥786.28 and Mercury 2.5 is ¥25.38 on FastMetal (yen, before tax), so Mercury 2.5 is cheaper.
- How do the context windows of GLM 5.1 and Mercury 2.5 compare?
- GLM 5.1 takes 204,800 tokens; Mercury 2.5 takes 260,000.
- Can I use GLM 5.1 and Mercury 2.5 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.1" or "mercury-2.5" 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 Mercury 2.5 from the browser chat and the API. No monthly fee.