GLM 4.7 vs Qwen3.8 Max
Pricing, context window and real answers (August 2026)
GLM 4.7 (Z.ai) and Qwen3.8 Max (Qwen), 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 |  Qwen3.8 Max | |
|---|---|---|
| Provider | Z.ai | Qwen |
| Input (per 1M tokens) | ¥107.22 | ¥357.4 |
| Output (per 1M tokens) | ¥393.14 | ¥1,072.2 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥304 | ¥894 |
| Context window | 202,752 tokens | 1,000,000 tokens |
| Release date | 12/22/2025 | 8/3/2026 |
| Input modalities | text | text, image |
| Arena · overall | #79 · ELO 1,442 | #20 · ELO 1,479 |
| Arena · Japanese | Unranked | #14 · ELO 1,485 |
| Arena · coding | #87 · ELO 1,485 | #26 · ELO 1,520 |
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, 63% less than Qwen3.8 Max.
- On the Overall arena board, Qwen3.8 Max ranks higher (#20; GLM 4.7 is #79).
- On the Coding arena board, Qwen3.8 Max ranks higher (#26; GLM 4.7 is #87).
- For long documents, Qwen3.8 Max: a 1,000,000-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
Qwen3.8 Max
The word **strawberry** is spelled:
**s t r a w b e r r y**
Now count the letter **r**:
1. s
2. t
3. **r** ← first r
4. a
5. w
6. b
7. e
8. **r** ← second r
9. **r** ← third r
10. y
There are **3** letters **r** in **strawberry**.
3.5s156 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
Qwen3.8 Max
The error means `users` is `undefined` when `UserList` tries to render:
```js
{users.map(user => ...)}
```
JavaScript cannot call `.map()` on `undefined`, so React throws:
```text
Cannot read properties of undefined (reading 'map')
```
## Most likely cause
The parent component is rendering `UserList` without passing a valid `users` array, or it is passing `users` before the data has loaded.
For example:
```jsx
<UserList />
```
or:
```jsx
<UserList users={undefined} />
```
or:
```jsx
const [users, setUsers] = useState(); // undefined initially
```
Then later:
```jsx
<UserList users={users} />
```
On the first render, `users` is still `undefined`.
---
## Fix 1: Give `users` a d…
17.7s1020 output tokens
Professional Email
Write a professional email to a client explaining that the project delivery will be delayed by two weeks due to unexpected technical challenges discovered during integration testing. The tone should be apologetic but con…
GLM 4.7
Subject: Important Update: Revised Timeline for [Project Name]
Dear [Client Name],
I am writing to provide you with an update on the status of [Project Name].
During our final phase of integration testing, our team encountered some unexpected technical challenges that require immediate attention. While the individual components performed well during unit testing, specific complexities arose when connecting [mention specific systems/modules, e.g., the database migration and the API layer].
After a thorough review, we have determined that in order to deliver a stable and secure product, we need to adjust the project timeline by two weeks.
I sincerely apologize for this delay. I understand…
57.1s1744 output tokens
Qwen3.8 Max
Subject: Revised Project Delivery Timeline – Updated Schedule and Next Steps
Dear [Client Name],
I hope this message finds you well.
I am writing to provide an update on the current status of the project and to inform you that, during our recent integration testing phase, we encountered several unexpected technical challenges that will impact the original delivery timeline. After careful review with the technical team, we now anticipate the revised delivery date will be [insert date – two weeks from original delivery date].
Please accept my sincere apologies for this delay. We understand the importance of this project and the expectations tied to the original schedule. While this situati…
11.9s547 output tokens
Frequently asked questions
- Which is cheaper, GLM 4.7 or Qwen3.8 Max?
- Per 1M output tokens, GLM 4.7 is ¥393.14 and Qwen3.8 Max is ¥1,072.2 on FastMetal (yen, before tax), so GLM 4.7 is cheaper.
- How do the context windows of GLM 4.7 and Qwen3.8 Max compare?
- GLM 4.7 takes 202,752 tokens; Qwen3.8 Max takes 1,000,000.
- Which ranks higher, GLM 4.7 or Qwen3.8 Max?
- Qwen3.8 Max ranks higher on the public arena (GLM 4.7 #79, Qwen3.8 Max #14). Ranks move as the leaderboard updates.
- Can I use GLM 4.7 and Qwen3.8 Max with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-4.7" or "qwen3.8-max" 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 Qwen3.8 Max from the browser chat and the API. No monthly fee.