DeepSeek V4.1 Flash vs GLM 4.7
Pricing, context window and real answers (October 2026)
DeepSeek V4.1 Flash (DeepSeek) and GLM 4.7 (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 4.7 | |
|---|---|---|
| Provider | DeepSeek | Z.ai |
| Input (per 1M tokens) | $0.211 | $0.422 |
| Output (per 1M tokens) | $0.633 | $1.85 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $0.5275 | $1.35 |
| Context window | 1,048,576 tokens | 202,752 tokens |
| Release date | 9/10/2026 | 12/22/2025 |
| Input modalities | text, image | text |
| Throughput (p50) | 194 tokens/s (n=27) | — |
| Arena · overall | #34 · ELO 1,476 | #95 · ELO 1,441 |
| Arena · Japanese | #37 · ELO 1,453 | #50 · ELO 1,440 |
| Arena · coding | #30 · ELO 1,523 | #107 · ELO 1,484 |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-22; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, DeepSeek V4.1 Flash: $0.633 per 1M output tokens, 66% less than GLM 4.7.
- On the Overall arena board, DeepSeek V4.1 Flash ranks higher (#34; GLM 4.7 is #95).
- On the Japanese arena board, DeepSeek V4.1 Flash ranks higher (#37; GLM 4.7 is #50).
- On the Coding arena board, DeepSeek V4.1 Flash ranks higher (#30; GLM 4.7 is #107).
- For long documents, DeepSeek V4.1 Flash: a 1,048,576-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.
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 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
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 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
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 4.7
Here is a review of your function with suggestions for improving readability, performance, and best practices, followed by a refactored version of the code.
### Code Review
1. **Import Placement:** You import `requests` and `time` inside the function. Imports should generally be placed at the top of the file so they are loaded once when the module starts, rather than every time the function is called.
2. **Bare `except:`:** You used `except:` without specifying an exception type. This is dangerous because it catches *everything*, including `KeyboardInterrupt` (Ctrl+C) and `SystemExit`, preventing your program from terminating when needed. You should specifically catch `requests.exception…
24.5s2951 output tokens
Frequently asked questions
- Which is cheaper, DeepSeek V4.1 Flash or GLM 4.7?
- Per 1M output tokens, DeepSeek V4.1 Flash is $0.633 and GLM 4.7 is $1.85 on FastMetal (US dollars, before tax), so DeepSeek V4.1 Flash is cheaper.
- How do the context windows of DeepSeek V4.1 Flash and GLM 4.7 compare?
- DeepSeek V4.1 Flash takes 1,048,576 tokens; GLM 4.7 takes 202,752.
- Which ranks higher, DeepSeek V4.1 Flash or GLM 4.7?
- DeepSeek V4.1 Flash ranks higher on the public arena (DeepSeek V4.1 Flash #37, GLM 4.7 #50). Ranks move as the leaderboard updates.
- Can I use DeepSeek V4.1 Flash and GLM 4.7 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4.1-flash" or "glm-4.7" 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 4.7 from the browser chat and the API. No monthly fee.