MiniMax M3.1 Flash vs Muse Spark 1.3
Pricing, context window and real answers (October 2026)
MiniMax M3.1 Flash (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 M3.1 Flash |  Muse Spark 1.3 | |
|---|---|---|
| Provider | MiniMax | Meta |
| Input (per 1M tokens) | $0.1583 | $1.38 |
| Output (per 1M tokens) | $0.633 | $4.68 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $0.4748 | $3.72 |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Release date | 10/19/2026 | 9/2/2026 |
| Input modalities | text, image | text, image, video, file, audio |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #10 · ELO 1,494 |
| Arena · Japanese | Unranked | #13 · ELO 1,492 |
| Arena · coding | Unranked | #15 · ELO 1,535 |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-15; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, MiniMax M3.1 Flash: $0.633 per 1M output tokens, 86% less than Muse Spark 1.3.
- 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 M3.1 Flash
1. Spell **strawberry**:
**s – t – r – a – w – b – e – r – r – y**
2. Count the letter **r**: it appears at positions **3, 8, and 9**.
**Total: 3 “r”s.**
3.0s193 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 M3.1 Flash
The error occurs because `users` is `undefined` when `UserList` renders. Calling `.map()` on `undefined` causes the `TypeError`.
This commonly happens when:
- `<UserList />` is rendered without passing the `users` prop.
- The prop has a different name, such as `user`.
- Data is still loading and the parent initializes its state as `undefined`.
- An API response is accessed before it exists.
### Immediate fix
Provide a default empty array:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
Then pass the actual data from the parent:
```jsx
const [users, setUsers] = useState([…
7.3s744 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 M3.1 Flash
The function is understandable, but it has a few important issues:
- `except:` catches programming errors such as `KeyError`, `TypeError`, and even `KeyboardInterrupt`.
- Every non-200 response is retried, including permanent failures such as 400, 401, and 404.
- It sleeps after the final failed attempt.
- Returning `[]` makes a failed request indistinguishable from a successful response containing no active records.
- A fixed delay can cause clients to retry simultaneously; exponential backoff and `Retry-After` are preferable.
- `item["active"] == True` should be `item.get("active") is True` if the API contract says it is a JSON boolean.
- A `Session` can reuse connections, while `requests…
146.5s
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 M3.1 Flash or Muse Spark 1.3?
- Per 1M output tokens, MiniMax M3.1 Flash is $0.633 and Muse Spark 1.3 is $4.68 on FastMetal (US dollars, before tax), so MiniMax M3.1 Flash is cheaper.
- How do the context windows of MiniMax M3.1 Flash and Muse Spark 1.3 compare?
- MiniMax M3.1 Flash takes 1,048,576 tokens; Muse Spark 1.3 takes 1,048,576.
- Can I use MiniMax M3.1 Flash and Muse Spark 1.3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "minimax-m3.1-flash" 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 M3.1 Flash and Muse Spark 1.3 from the browser chat and the API. No monthly fee.