DeepSeek V4 Flash vs GLM 5.2
Pricing, context window and real answers (August 2026)
DeepSeek V4 Flash (DeepSeek) and GLM 5.2 (Z.ai), 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
 DeepSeek V4 Flash |  GLM 5.2 | |
|---|---|---|
| Provider | DeepSeek | Z.ai |
| Input (per 1M tokens) | ¥16.08 | ¥250.18 |
| Output (per 1M tokens) | ¥32.17 | ¥786.28 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥32 | ¥643 |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Release date | 4/24/2026 | 6/16/2026 |
| Input modalities | text | text |
| Arena · overall | #79 · ELO 1,436 | #31 · ELO 1,469 |
| Arena · Japanese | #67 · ELO 1,390 | #13 · ELO 1,472 |
| Arena · coding | #80 · ELO 1,484 | #46 · ELO 1,506 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, DeepSeek V4 Flash: ¥32.17 per 1M output tokens, 96% less than GLM 5.2.
- On the Overall arena board, GLM 5.2 ranks higher (#31; DeepSeek V4 Flash is #79).
- On the Japanese arena board, GLM 5.2 ranks higher (#13; DeepSeek V4 Flash is #67).
- On the Coding arena board, GLM 5.2 ranks higher (#46; DeepSeek V4 Flash is #80).
- 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.
DeepSeek V4 Flash
The word "strawberry" is spelled as s-t-r-a-w-b-e-r-r-y. I go through each letter: s (no), t (no), r (yes, first), a (no), w (no), b (no), e (no), r (yes, second), r (yes, third), y (no). Thus, there are three 'r's.
3.9s251 output tokens
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
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…
DeepSeek V4 Flash
The error occurs because `users` is `undefined` when the component tries to call `.map()` on it.
## Why this happens
Your component expects `users` to be an array, but it's receiving `undefined` as a prop. This typically happens when:
1. The parent component doesn't pass the `users` prop
2. The data fetching hasn't completed yet (async data loading)
3. The API response is missing the expected data structure
## How to fix it
### Option 1: Default prop value (Recommended for initial state)
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
### Option 2: Guard clause (More explicit)
```jsx
func…
6.3s422 output tokens
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
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):…
DeepSeek V4 Flash
Here's a comprehensive review with suggested improvements:
## Issues Identified:
1. **Import at wrong location** - Imports inside functions are inefficient and non-standard
2. **Bare `except:` clause** - Catches all exceptions including `KeyboardInterrupt`, `SystemExit`
3. **Missing error handling granularity** - Should distinguish between retryable and non-retryable errors
4. **Duplicate sleep logic** - Same sleep in `else` and `except` blocks
5. **Unnecessary variable** - `data` is only used once
6. **Inefficient list building** - Manual loop instead of list comprehension
7. **Hardcoded error message** - No logging or error context
8. **Missing type hints** - No type annotations
9. **Fun…
12.6s987 output tokens
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
Frequently asked questions
- Which is cheaper, DeepSeek V4 Flash or GLM 5.2?
- Per 1M output tokens, DeepSeek V4 Flash is ¥32.17 and GLM 5.2 is ¥786.28 on FastMetal (yen, before tax), so DeepSeek V4 Flash is cheaper.
- How do the context windows of DeepSeek V4 Flash and GLM 5.2 compare?
- DeepSeek V4 Flash takes 1,048,576 tokens; GLM 5.2 takes 1,048,576.
- Which ranks higher, DeepSeek V4 Flash or GLM 5.2?
- GLM 5.2 ranks higher on the public arena (DeepSeek V4 Flash #67, GLM 5.2 #13). Ranks move as the leaderboard updates.
- Can I use DeepSeek V4 Flash and GLM 5.2 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4-flash" or "glm-5.2" 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 DeepSeek V4 Flash and GLM 5.2 from the browser chat and the API. No monthly fee.