GPT-6.1 Sol vs Muse Spark 1.2
Pricing, context window and real answers (September 2026)
GPT-6.1 Sol (OpenAI) 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
 GPT-6.1 Sol |  Muse Spark 1.2 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Input (per 1M tokens) | ¥357.4 | ¥219.9 |
| Output (per 1M tokens) | ¥1,787 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,251 | ¥594 |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Release date | 9/29/2026 | 8/5/2026 |
| Input modalities | file, image, text | text, image, video, file, audio |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #7 · ELO 1,496 |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | #11 · ELO 1,535 |
Prices are FastMetal's yen rates before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-09-25; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, Muse Spark 1.2: ¥747.65 per 1M output tokens, 58% less than GPT-6.1 Sol.
- For long documents, GPT-6.1 Sol: a 1,050,000-token context window against 1,048,576 for Muse Spark 1.2.
- 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-6.1 Sol
“strawberry” is spelled **s-t-r-a-w-b-e-r-r-y**.
The letter **r** appears at positions **3, 8, and 9**.
So, there are **3 r’s** in “strawberry.”
2.8s88 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…
GPT-6.1 Sol
The error means **`users` is `undefined` when `UserList` renders**. Calling `.map()` on `undefined` throws this error.
This commonly happens when the parent doesn’t pass the `users` prop, or when data hasn’t finished loading yet.
### Fix: provide a default empty array
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
This renders an empty list if `users` is omitted or `undefined`. It does **not** handle `null`.
### Check the parent component too
Make sure it passes an array:
```jsx
<UserList users={users} />
```
If you’re fetching users asynchronously, initialize the stat…
5.8s306 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):…
GPT-6.1 Sol
The function is short, but its main weakness is that it hides failures: a network error, invalid JSON, and a genuinely empty result all return `[]`.
### Suggested improvements
- **Move imports to module scope.** This is conventional and makes dependencies visible. Repeated imports are cached, so the performance benefit is minor.
- **Avoid bare `except:`.** It catches everything, including `KeyboardInterrupt` and `SystemExit`, and can hide programming errors.
- **Handle HTTP errors explicitly.** `raise_for_status()` provides useful exceptions. Retry transient failures such as timeouts, connection errors, HTTP 429, and HTTP 5xx—not permanent errors such as HTTP 404.
- **Don’t sleep after the…
19.0s1094 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, GPT-6.1 Sol or Muse Spark 1.2?
- Per 1M output tokens, GPT-6.1 Sol is ¥1,787 and Muse Spark 1.2 is ¥747.65 on FastMetal (yen, before tax), so Muse Spark 1.2 is cheaper.
- How do the context windows of GPT-6.1 Sol and Muse Spark 1.2 compare?
- GPT-6.1 Sol takes 1,050,000 tokens; Muse Spark 1.2 takes 1,048,576.
- Can I use GPT-6.1 Sol and Muse Spark 1.2 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-6.1-sol" 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 GPT-6.1 Sol and Muse Spark 1.2 from the browser chat and the API. No monthly fee.