GPT-4.1 Nano vs Muse Spark 1.3
Pricing, context window and real answers (September 2026)
GPT-4.1 Nano (OpenAI) 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
 GPT-4.1 Nano |  Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Input (per 1M tokens) | ¥17.87 | ¥219.9 |
| Output (per 1M tokens) | ¥71.48 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥54 | ¥594 |
| Context window | 1,047,576 tokens | 1,048,576 tokens |
| Release date | 4/14/2025 | 9/2/2026 |
| Input modalities | image, text, file | text, image, video, file, audio |
| Throughput (p50) | — | — |
| Arena · overall | #243 · ELO 1,322 | #8 · ELO 1,493 |
| Arena · Japanese | #195 · ELO 1,234 | Unranked |
| Arena · coding | #226 · ELO 1,374 | #8 · ELO 1,537 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-4.1 Nano: ¥71.48 per 1M output tokens, 90% less than Muse Spark 1.3.
- On the Overall arena board, Muse Spark 1.3 ranks higher (#8; GPT-4.1 Nano is #243).
- On the Coding arena board, Muse Spark 1.3 ranks higher (#8; GPT-4.1 Nano is #226).
- For long documents, Muse Spark 1.3: a 1,048,576-token context window against 1,047,576 for GPT-4.1 Nano.
- 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.
GPT-4.1 Nano
Let's analyze the word "strawberry" step by step to count the number of 'r's.
1. Write down the word: **strawberry**
2. Examine each letter one by one:
- s: no
- t: no
- r: yes (first 'r')
- a: no
- w: no
- b: no
- e: no
- r: yes (second 'r')
- r: yes (third 'r')
- y: no
3. Counting the 'r's found:
- First 'r' (at position 3)
- Second 'r' (at position 8)
- Third 'r' (at position 9)
So, there are **3** 'r's in "strawberry."
**Final answer: 3**
2.0s183 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…
GPT-4.1 Nano
The error:
```
TypeError: Cannot read properties of undefined (reading 'map')
```
indicates that `users` is `undefined` at the time your `UserList` component is rendering, and you're trying to call `map` on it.
### Why is this happening?
In React, if a prop (`users` in this case) is not provided or is undefined, trying to do `users.map(...)` causes this error. This can happen if:
- The parent component does not pass `users`.
- `users` might be `null` or `undefined` initially, especially if data fetching is involved.
### How to fix it
**Option 1: Provide a default value for `users`**
Ensure that `users` defaults to an empty array if it is not provided:
```jsx
function UserList({ users…
4.3s514 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):…
GPT-4.1 Nano
Here's a review and an improved version of your function:
### Key improvements:
1. **Move imports to the top**: Imports should generally be at the top of the file, not inside functions.
2. **Specify exception types**: Catch specific exceptions rather than a generic `except`.
3. **Use context managers if needed**: Not necessary here, but good to consider.
4. **Avoid repeated code**: The sleep statement is the same whether there is a request exception or a non-200 status.
5. **Simplify filtering**: Use list comprehensions for clarity.
6. **Improve variable names**: For readability.
7. **Add optional headers or parameters** if needed (not required here).
8. **Optional:** Add more descriptive e…
3.4s391 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, GPT-4.1 Nano or Muse Spark 1.3?
- Per 1M output tokens, GPT-4.1 Nano is ¥71.48 and Muse Spark 1.3 is ¥747.65 on FastMetal (yen, before tax), so GPT-4.1 Nano is cheaper.
- How do the context windows of GPT-4.1 Nano and Muse Spark 1.3 compare?
- GPT-4.1 Nano takes 1,047,576 tokens; Muse Spark 1.3 takes 1,048,576.
- Which ranks higher, GPT-4.1 Nano or Muse Spark 1.3?
- Muse Spark 1.3 ranks higher on the public arena (GPT-4.1 Nano #195, Muse Spark 1.3 #8). Ranks move as the leaderboard updates.
- Can I use GPT-4.1 Nano and Muse Spark 1.3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4.1-nano" 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 GPT-4.1 Nano and Muse Spark 1.3 from the browser chat and the API. No monthly fee.