Muse Glimmer 30B vs Pareto
Pricing, context window and real answers (September 2026)
Muse Glimmer 30B (Meta) and Pareto (Unbiased), 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 | Pareto | |
|---|---|---|
| Provider | Meta | Unbiased |
| Input (per 1M tokens) | ¥58.8 | ¥446.75 |
| Output (per 1M tokens) | ¥252 | ¥1,340.25 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥185 | ¥1,117 |
| Context window | 131,072 tokens | 262,144 tokens |
| Release date | 8/10/2026 | 9/17/2026 |
| Input modalities | text, image | text, image |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | Unranked |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | Unranked |
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: ¥252 per 1M output tokens, 81% less than Pareto.
- For long documents, Pareto: a 262,144-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
Pareto
To count the number of 'r's in the word "strawberry," let's break it down letter by letter:
1. **s** - not an 'r'
2. **t** - not an 'r'
3. **r** - **Yes**, this is the first 'r'.
4. **a** - not an 'r'
5. **w** - not an 'r'
6. **b** - not an 'r'
7. **e** - not an 'r'
8. **r** - **Yes**, this is the second 'r'.
9. **r** - **Yes**, this is the third 'r'.
10. **y** - not an 'r'
Counting the occurrences:
- The 3rd letter is 'r'.
- The 8th letter is 'r'.
- The 9th letter is 'r'.
There are **3** 'r's in "strawberry".
5.5s225 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
Pareto
The error means `users` is `undefined` when `UserList` renders. Destructuring a prop does **not** protect against it:
```jsx
function UserList({ users }) { // users can still be undefined
return <ul>{users.map(...)}</ul>; // 💥
}
```
This usually happens when:
- The parent renders `<UserList />` without passing `users`
- The parent’s state starts as `undefined` before an async fetch finishes
- The API response is not an array, or `users` is passed as `undefined`
## Fix 1: Default the prop to an empty array
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
This works when…
11.6s1478 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
Pareto
The function is straightforward, but its error handling hides failures and retries requests that may never succeed.
### Main improvements
- **Move imports to module scope** for readability and conventional dependency management.
- **Avoid bare `except:`.** It catches everything, including programming errors and `KeyboardInterrupt`. Catch specific request failures instead.
- **Retry selectively.** Timeouts, connection failures, rate limits, and certain server errors may be temporary; most other HTTP errors should surface immediately.
- **Use exponential backoff** and avoid sleeping after the last attempt.
- **Use a list comprehension** to express the filtering and transformation directly.
-…
30.3s1090 output tokens
Frequently asked questions
- Which is cheaper, Muse Glimmer 30B or Pareto?
- Per 1M output tokens, Muse Glimmer 30B is ¥252 and Pareto is ¥1,340.25 on FastMetal (yen, before tax), so Muse Glimmer 30B is cheaper.
- How do the context windows of Muse Glimmer 30B and Pareto compare?
- Muse Glimmer 30B takes 131,072 tokens; Pareto takes 262,144.
- Can I use Muse Glimmer 30B and Pareto with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "muse-glimmer-30b" or "pareto" 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 Pareto from the browser chat and the API. No monthly fee.