Muse Glimmer 30B vs Muse Spark 1.2
Pricing, context window and real answers (August 2026)
Muse Glimmer 30B (Meta) 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
 Muse Glimmer 30B | Muse Spark 1.2 | |
|---|---|---|
| Provider | Meta | Meta |
| Input (per 1M tokens) | ¥62.55 | ¥219.9 |
| Output (per 1M tokens) | ¥268.05 | ¥747.65 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥197 | ¥594 |
| Context window | 131,072 tokens | 1,048,576 tokens |
| Release date | 8/10/2026 | 8/5/2026 |
| Input modalities | text, image | text, image, video, file, audio |
| Arena · overall | Unranked | #4 · ELO 1,498 |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | #7 · ELO 1,533 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Muse Glimmer 30B: ¥268.05 per 1M output tokens, 64% less than Muse Spark 1.2.
- For long documents, Muse Spark 1.2: a 1,048,576-token context window against 131,072 for Muse Glimmer 30B.
- 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.
Muse Glimmer 30B
The word is 10 letters long. Scanning left to right:
1. **s** - not r
2. **t** - not r
3. **r** - 1st r
4. **a** - not r
5. **w** - not r
6. **b** - not r
7. **e** - not r
8. **r** - 2nd r
9. **r** - 3rd r
10. **y** - not r
`s t r a w b e r r y`
There is one r in `str-`, and a double `rr` in `-berry`.
Total = 1 + 2 = 3 r's.
8.0s614 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…
Muse Glimmer 30B
The error is exactly what it says: you're trying to call `.map` on `users`, but `users` is `undefined` at render time.
```js
{users.map(user => ...)}
^^^^^^
```
`Cannot read properties of undefined [reading 'map']` means `users` was never defined / passed in, so `users.map` throws.
This happens very commonly with React components that receive async data. The parent renders `UserList` before the data has loaded, so the prop is `undefined` / `null` on the first render.
### Fix it by guarding the prop
**1. Default parameter to an empty array - simplest**
```js
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>…
5.6s888 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):…
Muse Glimmer 30B
The function works but it mixes concerns and hides errors. Here are the main issues:
**Readability**
* Imports inside the function. `import requests` and `import time` should be at module level.
* Bare `except:` catches `KeyboardInterrupt`, `SystemExit` and masks bugs.
* Unused loop variable `i` and vague names `r`, `data`.
* No docstring / type hints, so the contract is unclear.
* `if item["active"] == True:` is redundant and will raise `KeyError` if the key is missing.
**Correctness / Best practices**
* `except:` should be `except requests.RequestException`. JSON parsing can also fail.
* Check `r.status_code == 200` is too narrow. Use `raise_for_status` / `r.ok` for any 2xx.
* Fixed 2 se…
12.0s1795 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, Muse Glimmer 30B or Muse Spark 1.2?
- Per 1M output tokens, Muse Glimmer 30B is ¥268.05 and Muse Spark 1.2 is ¥747.65 on FastMetal (yen, before tax), so Muse Glimmer 30B is cheaper.
- How do the context windows of Muse Glimmer 30B and Muse Spark 1.2 compare?
- Muse Glimmer 30B takes 131,072 tokens; Muse Spark 1.2 takes 1,048,576.
- Can I use Muse Glimmer 30B and Muse Spark 1.2 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "muse-glimmer-30b" 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 Muse Glimmer 30B and Muse Spark 1.2 from the browser chat and the API. No monthly fee.