DeepSeek V4 Pro vs GLM 5.3 Flash
Pricing, context window and real answers (August 2026)
DeepSeek V4 Pro (DeepSeek) and GLM 5.3 Flash (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 Pro |  GLM 5.3 Flash | |
|---|---|---|
| Provider | DeepSeek | Z.ai |
| Input (per 1M tokens) | ¥341.32 | ¥13.19 |
| Output (per 1M tokens) | ¥684.42 | ¥43.98 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥684 | ¥35 |
| Context window | 1,048,576 tokens | 1,310,720 tokens |
| Release date | 4/24/2026 | 8/26/2026 |
| Input modalities | text | text, image, video |
| Arena · overall | #54 · ELO 1,458 | #38 · ELO 1,469 |
| Arena · Japanese | #22 · ELO 1,463 | Unranked |
| Arena · coding | #59 · ELO 1,502 | #11 · ELO 1,531 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GLM 5.3 Flash: ¥43.98 per 1M output tokens, 94% less than DeepSeek V4 Pro.
- On the Overall arena board, GLM 5.3 Flash ranks higher (#38; DeepSeek V4 Pro is #54).
- On the Coding arena board, GLM 5.3 Flash ranks higher (#11; DeepSeek V4 Pro is #59).
- For long documents, GLM 5.3 Flash: a 1,310,720-token context window against 1,048,576 for DeepSeek V4 Pro.
- 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 Pro
The word is "strawberry". Let's count the occurrences of the letter 'r' step by step:
1. Write the word: s t r a w b e r r y
2. Examine each character:
- s: not an 'r'
- t: not an 'r'
- r: is an 'r' → count 1
- a: not an 'r'
- w: not an 'r'
- b: not an 'r'
- e: not an 'r'
- r: is an 'r' → count 2
- r: is an 'r' → count 3
- y: not an 'r'
3. Total number of 'r's = 3.
Therefore, there are **3** 'r's in "strawberry".
7.3s1136 output tokens
GLM 5.3 Flash
# Counting 'r's in 'strawberry'
**Step 1: Write out the word letter by letter**
s - t - r - a - w - b - e - r - r - y
**Step 2: Check each letter one at a time**
| Position | Letter | Is it 'r'? |
|----------|--------|-----------|
| 1 | s | No |
| 2 | t | No |
| 3 | r | **Yes! (1)** |
| 4 | a | No |
| 5 | w | No |
| 6 | b | No |
| 7 | e | No |
| 8 | r | **Yes! (2)** |
| 9 | r | **Yes! (3)** |
| 10 | y | No |
**Step 3: Add up the matches**
The 'r's appear at positions 3, 8, and 9.
## Answer: There are **3** 'r's in "strawberry" 🍓
7.2s449 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 Pro
The error is occurring because `users` is `undefined` when the component renders, and you're trying to call `.map()` on it. This typically happens when the data hasn't been loaded yet or wasn't passed correctly to the component.
## Here are several ways to fix this:
### 1. **Add a default value with empty array (Simplest fix)**
```javascript
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
### 2. **Add a conditional check**
```javascript
function UserList({ users }) {
if (!users) {
return <div>No users found</div>;
}
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}<…
6.9s442 output tokens
GLM 5.3 Flash
## What's happening
The error means the `users` prop is `undefined` at the time `UserList` renders. Since you can't call `.map()` on `undefined`, JavaScript throws the TypeError.
This usually happens for one of these reasons:
1. **The parent isn't passing the prop** — rendering `<UserList />` without `users`, or with a typo'd prop name like `user={users}`.
2. **Data hasn't loaded yet** — the parent fetches data asynchronously and its state starts as `undefined`:
```jsx
const [users, setUsers] = useState(); // undefined until fetch resolves!
return <UserList users={users} />;
```
3. **API response shape mismatch** — the array is nested, e.g., you need `response.data.users` inst…
31.3s1639 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 Pro
Here’s a review of your `get_data` function, highlighting issues and suggesting improvements.
## Overall Observations
- The function works but has several readability, robustness, and maintainability issues.
- Imports are inside the function, bare `except` hides errors, and the filtering logic is not Pythonic.
- No type hints or docstring, making it harder to use and understand.
## Specific Improvements
### 1. Move Imports to the Top of the Module
**Why:** Imports inside a function are executed every time the function is called, which is slightly slower and violates PEP 8 style guidelines.
**Before:**
```python
def get_data(url, retries=3):
import requests
import time
# ...
`…
40.5s2277 output tokens
GLM 5.3 Flash
Solid foundation — you're already passing an explicit `timeout` and implementing retries, which many people skip. Here's a breakdown by category:
## Correctness & robustness (most important)
- **Bare `except:`** catches *everything*, including `KeyboardInterrupt` and `SystemExit`, and silently discards the error. Catch specific exceptions: `requests.RequestException` for network issues, `ValueError` for invalid JSON.
- **Retrying non-retryable failures**: a 401/403/404 will never succeed on retry, so you're sleeping 6 seconds for nothing. Only retry transient errors (5xx, 429, timeouts/connection errors).
- **`item["active"]` raises `KeyError`** on malformed data. Use `item.get("active")`…
116.1s6185 output tokens
Frequently asked questions
- Which is cheaper, DeepSeek V4 Pro or GLM 5.3 Flash?
- Per 1M output tokens, DeepSeek V4 Pro is ¥684.42 and GLM 5.3 Flash is ¥43.98 on FastMetal (yen, before tax), so GLM 5.3 Flash is cheaper.
- How do the context windows of DeepSeek V4 Pro and GLM 5.3 Flash compare?
- DeepSeek V4 Pro takes 1,048,576 tokens; GLM 5.3 Flash takes 1,310,720.
- Which ranks higher, DeepSeek V4 Pro or GLM 5.3 Flash?
- DeepSeek V4 Pro ranks higher on the public arena (DeepSeek V4 Pro #22, GLM 5.3 Flash #38). Ranks move as the leaderboard updates.
- Can I use DeepSeek V4 Pro and GLM 5.3 Flash with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4-pro" or "glm-5.3-flash" 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 Pro and GLM 5.3 Flash from the browser chat and the API. No monthly fee.