DeepSeek V4 Pro vs Muse Spark 1.2
Pricing, context window and real answers (August 2026)
DeepSeek V4 Pro (DeepSeek) and Muse Spark 1.2 (Meta), 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 |  Muse Spark 1.2 | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Input (per 1M tokens) | ¥341.32 | ¥219.9 |
| Output (per 1M tokens) | ¥684.42 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥684 | ¥594 |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Release date | 4/24/2026 | 8/5/2026 |
| Input modalities | text | text, image, video, file, audio |
| Arena · overall | #54 · ELO 1,458 | #4 · ELO 1,498 |
| Arena · Japanese | #22 · ELO 1,463 | Unranked |
| Arena · coding | #59 · ELO 1,502 | #7 · ELO 1,533 |
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 Pro: ¥684.42 per 1M output tokens, 8% less than Muse Spark 1.2.
- On the Overall arena board, Muse Spark 1.2 ranks higher (#4; DeepSeek V4 Pro is #54).
- On the Coding arena board, Muse Spark 1.2 ranks higher (#7; DeepSeek V4 Pro is #59).
- 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
Muse Spark 1.2
There are **3** 'r's in "strawberry".
Here is my reasoning step by step:
1. Write out the word and its spelling: **s-t-r-a-w-b-e-r-r-y**
2. Go through each letter one by one and check if it is an 'r':
* 1. s - not an 'r' -> count = 0
* 2. t - not an 'r' -> count = 0
* 3. **r** - yes, it's an 'r' -> count = 1
* 4. a - not an 'r' -> count = 1
* 5. w - not an 'r' -> count = 1
* 6. b - not an 'r' -> count = 1
* 7. e - not an 'r' -> count = 1
* 8. **r** - yes, it's an 'r' -> count = 2
* 9. **r** - yes, it's an 'r' -> count = 3
* 10. y - not an 'r' -> count = 3
3. Final total = **3**.
13.3s1123 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
Muse Spark 1.2
This error means `users` is `undefined` when the component tries to render.
You are calling `.map()` on `users` at line 12, but `.map()` only exists on arrays. If `users` is `undefined` or `null`, JavaScript throws: `Cannot read properties of undefined (reading 'map')`.
This usually happens for 2 reasons:
1. You didn't pass the `users` prop to the component: `<UserList />`
2. Your data is async and `users` is `undefined` on the first render. For example: `const [users, setUsers] = useState()` without an initial value, and the data hasn't been fetched yet.
### Fix it
You need to guarantee `users` is always an array before you call `.map()`.
#### 1. Best Fix: Give it a default value
U…
7.6s1142 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
Muse Spark 1.2
Here is a review of your function with a refactored, production-ready version:
### Issues in the Current Version
#### 1. Readability
1. **Generic name:** `get_data` tells nothing about what it does. `get_active_items` is better.
2. **Imports inside function:** `import requests, time` should be at the top of the file. It's slower and violates PEP 8.
3. **Magic numbers:** `200`, `10`, `2` have no context.
4. **Verbose loop:** Manual `for` loop + `append` can be replaced with a list comprehension.
5. **No documentation/typing:** No docstring, no type hints, so callers don't know what it expects or returns.
6. **`== True` is redundant:** `if item["active"] == True:` should be `if item["a…
11.8s2278 output tokens
Frequently asked questions
- Which is cheaper, DeepSeek V4 Pro or Muse Spark 1.2?
- Per 1M output tokens, DeepSeek V4 Pro is ¥684.42 and Muse Spark 1.2 is ¥747.65 on FastMetal (yen, before tax), so DeepSeek V4 Pro is cheaper.
- How do the context windows of DeepSeek V4 Pro and Muse Spark 1.2 compare?
- DeepSeek V4 Pro takes 1,048,576 tokens; Muse Spark 1.2 takes 1,048,576.
- Which ranks higher, DeepSeek V4 Pro or Muse Spark 1.2?
- Muse Spark 1.2 ranks higher on the public arena (DeepSeek V4 Pro #22, Muse Spark 1.2 #4). Ranks move as the leaderboard updates.
- Can I use DeepSeek V4 Pro and Muse Spark 1.2 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4-pro" or "muse-spark-1.2" 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 Pro and Muse Spark 1.2 from the browser chat and the API. No monthly fee.