GPT-4o-mini vs Muse Glimmer 30B
Pricing, context window and real answers (September 2026)
GPT-4o-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-4o-mini |  Muse Glimmer 30B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Input (per 1M tokens) | ¥26.81 | ¥58.8 |
| Output (per 1M tokens) | ¥107.22 | ¥252 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥80 | ¥185 |
| Context window | 128,000 tokens | 131,072 tokens |
| Release date | 7/18/2024 | 8/10/2026 |
| Input modalities | text, image, file | text, image |
| Throughput (p50) | — | — |
| Arena · overall | #251 · ELO 1,318 | Unranked |
| Arena · Japanese | #187 · ELO 1,250 | Unranked |
| Arena · coding | #259 · ELO 1,348 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-4o-mini: ¥107.22 per 1M output tokens, 57% less than Muse Glimmer 30B.
- For long documents, Muse Glimmer 30B: a 131,072-token context window against 128,000 for GPT-4o-mini.
- 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-4o-mini
To count the number of 'r's in the word "strawberry," we can follow these steps:
1. **Identify the word**: We have the word "strawberry."
2. **Break down the letters**: Let's write out the letters in the word:
- s
- t
- r
- a
- w
- b
- e
- r
- r
- y
3. **Locate the 'r's**: Now, we need to look for the letter 'r' among these letters.
- In the list of letters, we can see:
- The first 'r' is in the 3rd position.
- The second 'r' is in the 8th position.
- The third 'r' is in the 9th position.
4. **Count the occurrences**: We check each position we identified:
- There are three occurrences of 'r' in the word "strawberry."
5. **Conclusion**:…
2.1s239 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-4o-mini
The error you're encountering, `TypeError: Cannot read properties of undefined (reading 'map')`, indicates that the `users` prop is `undefined` when you try to call the `map` method on it.
In your `UserList` component, you're attempting to use `users.map(...)`, but if the `users` prop is not provided or is `undefined`, this will throw an error.
### Fixing the Error
1. **Default Props**: You can set a default value for the `users` prop to prevent the error when it is `undefined`.
```jsx
function UserList({ users = [] }) { // Default to an empty array
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```…
5.0s511 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-4o-mini
Your Python function, `get_data`, essentially performs a GET request, handles retries on failure, and processes the response JSON to return a filtered list of dictionaries. Below, I've highlighted several improvements regarding readability, performance, and best practices:
1. **Avoid blanket exceptions**: It’s best practice to specify which exceptions you expect, allowing for better debugging and error handling.
2. **Use `requests` built-in exception handling**: Handle specific requests exceptions, such as `requests.exceptions.RequestException`.
3. **Improve condition checks**: Check for `item['active']` directly instead of comparing to `True`, which is more Pythonic.
4. **Use `time.sl…
8.8s628 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-4o-mini or Muse Glimmer 30B?
- Per 1M output tokens, GPT-4o-mini is ¥107.22 and Muse Glimmer 30B is ¥252 on FastMetal (yen, before tax), so GPT-4o-mini is cheaper.
- How do the context windows of GPT-4o-mini and Muse Glimmer 30B compare?
- GPT-4o-mini takes 128,000 tokens; Muse Glimmer 30B takes 131,072.
- Can I use GPT-4o-mini and Muse Glimmer 30B with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4o-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-4o-mini and Muse Glimmer 30B from the browser chat and the API. No monthly fee.