Grok 4.7 vs Muse Spark 1.2
Pricing, context window and real answers (September 2026)
Grok 4.7 (xAI) 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
 Grok 4.7 |  Muse Spark 1.2 | |
|---|---|---|
| Provider | xAI | Meta |
| Input (per 1M tokens) | ¥276.2 | ¥219.9 |
| Output (per 1M tokens) | ¥828.6 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥691 | ¥594 |
| Context window | 500,000 tokens | 1,048,576 tokens |
| Release date | 9/21/2026 | 8/5/2026 |
| Input modalities | text, image, file | text, image, video, file, audio |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #4 · ELO 1,500 |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | #9 · ELO 1,536 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Muse Spark 1.2: ¥747.65 per 1M output tokens, 10% less than Grok 4.7.
- For long documents, Muse Spark 1.2: a 1,048,576-token context window against 500,000 for Grok 4.7.
- 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.
Grok 4.7
The word "strawberry" consists of the letters S-T-R-A-W-B-E-R-R-Y.
- The 3rd letter is R.
- The 8th letter is R.
- The 9th letter is R.
This gives a total of 3 R's.
4.7s299 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…
Grok 4.7
The error happens because `users` is `undefined` when `UserList` renders, so calling `.map` on it fails.
That usually means the parent rendered `<UserList />` (or `<UserList users={undefined} />`) before data was loaded, or the prop name doesn’t match.
**Fix it in the component** so it tolerates a missing list:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
Or guard the call:
```jsx
function UserList({ users }) {
return (
<ul>
{(users ?? []).map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
**Also check the parent** so you pass an array once data exists:
`…
12.8s393 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):…
Grok 4.7
## Review
The function works for the happy path, but it hides failures, retries the wrong errors, and is harder to read and debug than it needs to be.
### Issues
1. **Imports inside the function** — move them to module level unless you have a strong reason (circular imports, optional dependency).
2. **Bare `except`** — swallows `KeyboardInterrupt`, `SystemExit`, and programming bugs. Catch specific exceptions.
3. **Retries non-retryable failures** — 4xx (except maybe 429) will not succeed on retry. Network errors and 5xx are the usual candidates.
4. **Sleeps after the last attempt** — wastes up to 2 seconds before returning `[]`.
5. **Unused loop variable** and vague names (`r`, `i`).
6.…
22.3s1525 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, Grok 4.7 or Muse Spark 1.2?
- Per 1M output tokens, Grok 4.7 is ¥828.6 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 Grok 4.7 and Muse Spark 1.2 compare?
- Grok 4.7 takes 500,000 tokens; Muse Spark 1.2 takes 1,048,576.
- Can I use Grok 4.7 and Muse Spark 1.2 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "grok-4.7" 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 Grok 4.7 and Muse Spark 1.2 from the browser chat and the API. No monthly fee.