GLM 5.1 vs GPT-6.1 Sol
Pricing, context window and real answers (September 2026)
GLM 5.1 (Z.ai) and GPT-6.1 Sol (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-6.1 Sol | |
|---|---|---|
| Provider | Z.ai | OpenAI |
| Input (per 1M tokens) | ¥250.18 | ¥357.4 |
| Output (per 1M tokens) | ¥786.28 | ¥1,787 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥643 | ¥1,251 |
| Context window | 204,800 tokens | 1,050,000 tokens |
| Release date | 4/7/2026 | 9/29/2026 |
| Input modalities | text | file, image, text |
| Throughput (p50) | — | — |
| Arena · overall | #49 · ELO 1,465 | Unranked |
| Arena · Japanese | #46 · ELO 1,438 | Unranked |
| Arena · coding | #48 · ELO 1,513 | Unranked |
Prices are FastMetal's yen rates before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-09-25; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, GLM 5.1: ¥786.28 per 1M output tokens, 56% less than GPT-6.1 Sol.
- For long documents, GPT-6.1 Sol: a 1,050,000-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-6.1 Sol
“strawberry” is spelled **s-t-r-a-w-b-e-r-r-y**.
The letter **r** appears at positions **3, 8, and 9**.
So, there are **3 r’s** in “strawberry.”
2.8s88 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-6.1 Sol
The error means **`users` is `undefined` when `UserList` renders**. Calling `.map()` on `undefined` throws this error.
This commonly happens when the parent doesn’t pass the `users` prop, or when data hasn’t finished loading yet.
### Fix: provide a default empty array
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
This renders an empty list if `users` is omitted or `undefined`. It does **not** handle `null`.
### Check the parent component too
Make sure it passes an array:
```jsx
<UserList users={users} />
```
If you’re fetching users asynchronously, initialize the stat…
5.8s306 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-6.1 Sol
The function is short, but its main weakness is that it hides failures: a network error, invalid JSON, and a genuinely empty result all return `[]`.
### Suggested improvements
- **Move imports to module scope.** This is conventional and makes dependencies visible. Repeated imports are cached, so the performance benefit is minor.
- **Avoid bare `except:`.** It catches everything, including `KeyboardInterrupt` and `SystemExit`, and can hide programming errors.
- **Handle HTTP errors explicitly.** `raise_for_status()` provides useful exceptions. Retry transient failures such as timeouts, connection errors, HTTP 429, and HTTP 5xx—not permanent errors such as HTTP 404.
- **Don’t sleep after the…
19.0s1094 output tokens
Frequently asked questions
- Which is cheaper, GLM 5.1 or GPT-6.1 Sol?
- Per 1M output tokens, GLM 5.1 is ¥786.28 and GPT-6.1 Sol is ¥1,787 on FastMetal (yen, before tax), so GLM 5.1 is cheaper.
- How do the context windows of GLM 5.1 and GPT-6.1 Sol compare?
- GLM 5.1 takes 204,800 tokens; GPT-6.1 Sol takes 1,050,000.
- Can I use GLM 5.1 and GPT-6.1 Sol with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.1" or "gpt-6.1-sol" 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-6.1 Sol from the browser chat and the API. No monthly fee.