GPT-4.1 Mini vs Muse Glimmer 30B
Pricing, context window and real answers (September 2026)
GPT-4.1 Mini (OpenAI) and Muse Glimmer 30B (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 Mini |  Muse Glimmer 30B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Input (per 1M tokens) | ¥71.48 | ¥58.8 |
| Output (per 1M tokens) | ¥285.92 | ¥252 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥214 | ¥185 |
| Context window | 1,047,576 tokens | 131,072 tokens |
| Release date | 4/14/2025 | 8/10/2026 |
| Input modalities | image, text, file | text, image |
| Throughput (p50) | — | — |
| Arena · overall | #172 · ELO 1,383 | Unranked |
| Arena · Japanese | #135 · ELO 1,330 | Unranked |
| Arena · coding | #164 · ELO 1,433 | 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, 12% less than GPT-4.1 Mini.
- For long documents, GPT-4.1 Mini: a 1,047,576-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.
GPT-4.1 Mini
Let's count the number of 'r's in the word "strawberry" step by step:
1. Write down the word: s t r a w b e r r y
2. Look at each letter and check if it is 'r':
- s → not 'r'
- t → not 'r'
- r → yes, 1st 'r'
- a → not 'r'
- w → not 'r'
- b → not 'r'
- e → not 'r'
- r → yes, 2nd 'r'
- r → yes, 3rd 'r'
- y → not 'r'
3. Total number of 'r's found: 3
**Answer:** There are 3 'r's in the word "strawberry".
2.0s176 output tokens
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
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 Mini
The error **"TypeError: Cannot read properties of undefined (reading 'map')"** means that the `users` prop passed to your `UserList` component is `undefined` at the time the component tries to render, so calling `.map()` on it throws an error.
### What's causing the error?
- Your component expects `users` to be an array, but for some reason it is `undefined` when the component renders.
- This could happen if:
- The parent component that passes the `users` prop did not pass it or passed `undefined`.
- The data is being fetched asynchronously and hasn't arrived yet.
- The default prop is missing or no default fallback is handled.
### How to fix it?
You want to ensure `users` is alway…
8.1s465 output tokens
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
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 Mini
Your function is functional but can be improved for readability, performance, and best practices. Here are some suggestions and an improved version of your function:
### Issues and improvements
1. **Imports**: Import at the top of the file rather than inside the function.
2. **Catch specific exceptions**: Avoid bare `except:` clauses. Catch specific exceptions like `requests.RequestException` or `json.decoder.JSONDecodeError`.
3. **Use list comprehension**: Instead of a loop with `append()`, use list comprehension for clarity and conciseness.
4. **Check boolean conditions directly**: Instead of `item["active"] == True`, just use `item["active"]`.
5. **Avoid sleeping after last retry**: No…
5.6s690 output tokens
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
Frequently asked questions
- Which is cheaper, GPT-4.1 Mini or Muse Glimmer 30B?
- Per 1M output tokens, GPT-4.1 Mini is ¥285.92 and Muse Glimmer 30B is ¥252 on FastMetal (yen, before tax), so Muse Glimmer 30B is cheaper.
- How do the context windows of GPT-4.1 Mini and Muse Glimmer 30B compare?
- GPT-4.1 Mini takes 1,047,576 tokens; Muse Glimmer 30B takes 131,072.
- Can I use GPT-4.1 Mini and Muse Glimmer 30B with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4.1-mini" or "muse-glimmer-30b" 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 Mini and Muse Glimmer 30B from the browser chat and the API. No monthly fee.