GLM 5.2 vs Inkling
Pricing, context window and real answers (August 2026)
GLM 5.2 (Z.ai) and Inkling (Thinkingmachines), 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 5.2 | Inkling | |
|---|---|---|
| Provider | Z.ai | Thinkingmachines |
| Input (per 1M tokens) | ¥250.18 | ¥178.7 |
| Output (per 1M tokens) | ¥786.28 | ¥723.74 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥643 | ¥541 |
| Context window | 1,048,576 tokens | 524,288 tokens |
| Release date | 6/16/2026 | 7/17/2026 |
| Input modalities | text | text, image, audio |
| Arena · overall | #31 · ELO 1,469 | #71 · ELO 1,443 |
| Arena · Japanese | #13 · ELO 1,472 | Unranked |
| Arena · coding | #46 · ELO 1,506 | #64 · ELO 1,496 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Inkling: ¥723.74 per 1M output tokens, 8% less than GLM 5.2.
- On the Overall arena board, GLM 5.2 ranks higher (#31; Inkling is #71).
- On the Coding arena board, GLM 5.2 ranks higher (#46; Inkling is #64).
- For long documents, GLM 5.2: a 1,048,576-token context window against 524,288 for Inkling.
- 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 5.2
To count the number of 'r's in the word 'strawberry', let's look at the word letter by letter:
1. **s** - no 'r'
2. **t** - no 'r'
3. **r** - this is the 1st 'r'
4. **a** - no 'r'
5. **w** - no 'r'
6. **b** - no 'r'
7. **e** - no 'r'
8. **r** - this is the 2nd 'r'
9. **r** - this is the 3rd 'r'
10. **y** - no 'r'
Total count: 3
There are **3** 'r's in the word 'strawberry'.
2.6s439 output tokens
Inkling
Let's break down the word **"strawberry"** letter by letter:
1. **s**
2. **t**
3. **r** ← (1st 'r')
4. **a**
5. **w**
6. **b**
7. **e**
8. **r** ← (2nd 'r')
9. **r** ← (3rd 'r')
10. **y**
So the spelling is: s-t-**r**-a-w-b-e-**r**-**r**-y
Counting them up:
- One 'r' in "str" (the 3rd letter)
- Two 'r's in "berry" (the 8th and 9th letters)
**Total: 3 'r's** in "strawberry".**
2.4s417 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 5.2
The error `TypeError: Cannot read properties of undefined (reading 'map')` happens because the `users` prop being passed to your `UserList` component is currently `undefined`. When JavaScript tries to call `.map()` on `undefined`, it throws this error.
Here are the best ways to fix this:
### Fix 1: Provide a default value (Recommended)
You can provide a default empty array `[]` when destructuring the props. This ensures that even if `users` is not passed down, the `.map()` function will still have an array to iterate over (resulting in an empty list rather than a crash).
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</…
8.3s1006 output tokens
Inkling
The error occurs because `users` is `undefined` when `UserList` renders, so `users.map` fails.
This usually happens when:
- The parent doesn't pass the prop (`<UserList />` instead of `<UserList users={...} />`)
- Data is still loading (e.g., API hasn't returned yet)
## Quick Fix
Provide a default empty array so `.map` always has an array to work with:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
Alternatively, guard against undefined explicitly:
```jsx
function UserList({ users }) {
if (!users) return null; // or a loading state
return (
<ul>
{users.map(user => <li key={…
4.9s585 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 5.2
Here is a review of your Python function, broken down by readability, performance, and best practices, followed by a refactored version of the code.
### 1. Best Practices
* **Move imports to the top:** Importing modules inside a function is generally discouraged. While Python caches imports, putting `import requests` and `import time` at the top of your file is the standard convention and improves readability.
* **Avoid bare `except:` blocks:** Using a bare `except:` catches everything, including `KeyboardInterrupt` and `SystemExit`. This makes it hard to interrupt your program if it gets stuck in a loop. You should catch specific exceptions, such as `requests.exceptions.RequestException` (…
10.9s2061 output tokens
Inkling
Here is a review with an improved version followed by explanations.
### Issues in the original
- **Imports inside the function**: Re-importing on every call is inefficient.
- **Bare `except:`**: Catches `SystemExit`, `KeyboardInterrupt`, etc.
- **Silent failures**: No logging; errors disappear.
- **Magic numbers**: `10`, `2`, `200` are hard-coded.
- **Data validation missing**: Assumes `data` is a list and every item has `"active"`, `"name"`, and `"id"` (will crash with `KeyError`).
- **Performance**: Uses `.append()` in a loop instead of a list comprehension.
- **Ambiguous return**: `[]` means both "success with no results" and "total failure".
### Improved version
```python
import loggi…
54.1s5649 output tokens
Frequently asked questions
- Which is cheaper, GLM 5.2 or Inkling?
- Per 1M output tokens, GLM 5.2 is ¥786.28 and Inkling is ¥723.74 on FastMetal (yen, before tax), so Inkling is cheaper.
- How do the context windows of GLM 5.2 and Inkling compare?
- GLM 5.2 takes 1,048,576 tokens; Inkling takes 524,288.
- Which ranks higher, GLM 5.2 or Inkling?
- GLM 5.2 ranks higher on the public arena (GLM 5.2 #13, Inkling #71). Ranks move as the leaderboard updates.
- Can I use GLM 5.2 and Inkling with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.2" or "inkling" 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 5.2 and Inkling from the browser chat and the API. No monthly fee.