MiniMax M2.7 vs Muse Spark 1.3
Pricing, context window and real answers (September 2026)
MiniMax M2.7 (MiniMax) and Muse Spark 1.3 (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
 MiniMax M2.7 |  Muse Spark 1.3 | |
|---|---|---|
| Provider | MiniMax | Meta |
| Input (per 1M tokens) | ¥53.61 | ¥219.9 |
| Output (per 1M tokens) | ¥214.44 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥161 | ¥594 |
| Context window | 204,800 tokens | 1,048,576 tokens |
| Release date | 3/18/2026 | 9/2/2026 |
| Input modalities | text | text, image, video, file, audio |
| Arena · overall | #124 · ELO 1,415 | Unranked |
| Arena · Japanese | #166 · ELO 1,278 | Unranked |
| Arena · coding | #97 · ELO 1,480 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, MiniMax M2.7: ¥214.44 per 1M output tokens, 71% less than Muse Spark 1.3.
- For long documents, Muse Spark 1.3: a 1,048,576-token context window against 204,800 for MiniMax M2.7.
- 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.
MiniMax M2.7
**Step‑by‑step counting**
1. Write the word **strawberry** as a sequence of its letters:
`s‑t‑r‑a‑w‑b‑e‑r‑r‑y`
2. Go through each letter and check whether it is the letter **r** (case‑insensitive).
| Position | Letter | Is it “r”? |
|----------|--------|------------|
| 1 | s | No |
| 2 | t | No |
| 3 | **r** | Yes → count = 1 |
| 4 | a | No |
| 5 | w | No |
| 6 | b | No |
| 7 | e | No |
| 8 | **r** | Yes → count = 2 |
| 9 | **r** | Yes → count = 3 |
| 10 | y | No |
3. After checking all ten positions, the total number of times the letter **…
11.1s475 output tokens
Muse Spark 1.3
The word is **strawberry** — there are **3** 'r's in it.
Here's my reasoning step by step:
1. **Write out the word:**
strawberry
2. **Break it into individual letters:**
s - t - r - a - w - b - e - r - r - y
3. **Go through each letter one by one and check if it is 'r':**
1. s → not r, count = 0
2. t → not r, count = 0
3. r → is r, count = 1
4. a → not r, count = 1
5. w → not r, count = 1
6. b → not r, count = 1
7. e → not r, count = 1
8. r → is r, count = 2
9. r → is r, count = 3
10. y → not r, count = 3
4. **Total up the matches:**
The 'r' appears at position 3, 8, and 9.
**Final answer: 3**
10.5s1063 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…
MiniMax M2.7
# Fixing the "Cannot read properties of undefined" Error
## The Problem
The error occurs because `users` is `undefined` when the component renders. The `.map()` method can't be called on `undefined`.
This typically happens when:
- The parent component doesn't pass the `users` prop
- The data is still loading/fetching
- The initial state is `undefined` instead of an empty array
---
## Solutions
### 1. Add a Default Parameter (Recommended)
```javascript
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
### 2. Use Optional Chaining
```javascript
function UserList({ users }) {
return (
<ul>…
14.2s695 output tokens
Muse Spark 1.3
This error means `users` is `undefined` when your component tries to render.
`users.map(...)` only works if `users` is an array. On the first render, if you haven't passed the prop yet, or your data hasn't loaded from an API yet, `users` is `undefined`, so JavaScript throws:
> Cannot read properties of undefined (reading 'map')
This almost always happens in one of these 2 cases:
1. You forgot to pass the prop:
```js
<UserList /> // users is undefined!
```
vs.
```js
<UserList users={myUsers} />
```
2. Your data is async and is `undefined` on the first render:
```js
const [users, setUsers] = useState(); // undefined at first!
// ...
<UserList users={users} />
```
### How to fix it
**1.…
16.7s1242 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):…
MiniMax M2.7
# Code Review: `get_data` Function
## Issues Identified
### 1. **Critical Issues**
```python
# ❌ Bare except clause - catches everything including KeyboardInterrupt
except:
time.sleep(2)
```
```python
# ❌ Comparing to True - redundant comparison
if item["active"] == True:
```
```python
# ❌ No JSON error handling - r.json() can raise ValueError
data = r.json()
```
### 2. **Code Quality Issues**
| Issue | Location | Problem |
|-------|----------|---------|
| Imports inside function | Line 2-3 | Should be at module level |
| Magic numbers | `timeout=10`, `sleep(2)` | Not descriptive |
| No docstring | Function | No documentation |
| No type hints | Function signature | Missing type safet…
31.7s1690 output tokens
Muse Spark 1.3
Here's a friendly review of your `get_data` function — it works, but there are a few readability, robustness, and performance issues worth fixing:
### 1. Readability Issues
**a) Imports inside the function**
```python
import requests
import time
```
This runs on every call (though Python caches it). Move to the top of the file per PEP 8.
**b) Poor variable names & magic numbers**
`r`, `i`, `data`, `2`, `10`, `200` don't tell the reader much.
**c) `== True` anti-pattern**
```python
if item["active"] == True:
```
Just use `if item.get("active"):` or `is True`. The current version will also crash with `KeyError` if `active` is missing.
**d) No docstring / type hints**
No one knows what `ur…
26.9s2141 output tokens
Frequently asked questions
- Which is cheaper, MiniMax M2.7 or Muse Spark 1.3?
- Per 1M output tokens, MiniMax M2.7 is ¥214.44 and Muse Spark 1.3 is ¥747.65 on FastMetal (yen, before tax), so MiniMax M2.7 is cheaper.
- How do the context windows of MiniMax M2.7 and Muse Spark 1.3 compare?
- MiniMax M2.7 takes 204,800 tokens; Muse Spark 1.3 takes 1,048,576.
- Can I use MiniMax M2.7 and Muse Spark 1.3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "minimax-m2.7" or "muse-spark-1.3" 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 MiniMax M2.7 and Muse Spark 1.3 from the browser chat and the API. No monthly fee.