DeepSeek V4.1 Flash vs GLM 5.1
Pricing, context window and real answers (September 2026)
DeepSeek V4.1 Flash (DeepSeek) and GLM 5.1 (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 V4.1 Flash |  GLM 5.1 | |
|---|---|---|
| Provider | DeepSeek | Z.ai |
| Input (per 1M tokens) | ¥50.69 | ¥250.18 |
| Output (per 1M tokens) | ¥202.74 | ¥786.28 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥152 | ¥643 |
| Context window | 1,048,576 tokens | 204,800 tokens |
| Release date | 9/10/2026 | 4/7/2026 |
| Input modalities | text, image | text |
| Arena · overall | Unranked | #44 · ELO 1,466 |
| Arena · Japanese | Unranked | #45 · ELO 1,434 |
| Arena · coding | Unranked | #37 · ELO 1,514 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, DeepSeek V4.1 Flash: ¥202.74 per 1M output tokens, 74% less than GLM 5.1.
- For long documents, DeepSeek V4.1 Flash: a 1,048,576-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.
DeepSeek V4.1 Flash
The word **“strawberry”** has **3** letter **“r”**s.
Step-by-step:
1. Spell it out: **s t r a w b e r r y**
2. Find each **r**:
- Position 3: **r** in “str”
- Position 8: first **r** in “berry”
- Position 9: second **r** in “berry”
3. Total: **3**
**Answer: 3**
7.5s226 output tokens
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
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 V4.1 Flash
The error means that `users` is `undefined` when `UserList` renders, so JavaScript cannot call `.map()` on it.
Your component expects a `users` prop:
```jsx
function UserList({ users }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
But it is being rendered without `users`, or `users` has not loaded yet.
Common causes:
1. Parent renders it without the prop:
```jsx
<UserList />
```
instead of:
```jsx
<UserList users={users} />
```
2. The prop name is different:
```jsx
<UserList userList={users} />
```
3. The data is fetched asynchronously and is initially `undefined`:
```jsx
const [users, setUsers] = useState();
useEffect(…
16.0s945 output tokens
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
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 V4.1 Flash
Here are the main improvements:
- Move imports to module level.
- Avoid bare `except`; catch specific exceptions.
- Use a `requests.Session` for connection reuse.
- Retry only transient network/HTTP failures, not all errors.
- Use exponential backoff and don’t sleep after the final attempt.
- Use a list comprehension for readability/performance.
- Add type hints, logging, constants, and basic JSON validation.
- Avoid `== True`; use `is True` or a truthy check depending on API contract.
Example refactor:
```python
from __future__ import annotations
import logging
import time
from typing import Any
import requests
logger = logging.getLogger(__name__)
TIMEOUT = (3.05, 10) # connect time…
31.5s5142 output tokens
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
Frequently asked questions
- Which is cheaper, DeepSeek V4.1 Flash or GLM 5.1?
- Per 1M output tokens, DeepSeek V4.1 Flash is ¥202.74 and GLM 5.1 is ¥786.28 on FastMetal (yen, before tax), so DeepSeek V4.1 Flash is cheaper.
- How do the context windows of DeepSeek V4.1 Flash and GLM 5.1 compare?
- DeepSeek V4.1 Flash takes 1,048,576 tokens; GLM 5.1 takes 204,800.
- Can I use DeepSeek V4.1 Flash and GLM 5.1 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4.1-flash" or "glm-5.1" 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 V4.1 Flash and GLM 5.1 from the browser chat and the API. No monthly fee.