Llama 3.3 70B Instruct vs Muse Glimmer 30B
Pricing, context window and real answers (September 2026)
Llama 3.3 70B Instruct (Meta) 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
 Llama 3.3 70B Instruct | Muse Glimmer 30B | |
|---|---|---|
| Provider | Meta | Meta |
| Input (per 1M tokens) | ¥17.87 | ¥58.8 |
| Output (per 1M tokens) | ¥57.18 | ¥252 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥46 | ¥185 |
| Context window | 131,072 tokens | 131,072 tokens |
| Release date | 12/6/2024 | 8/10/2026 |
| Input modalities | text | text, image |
| Throughput (p50) | — | — |
| Arena · overall | #250 · ELO 1,318 | Unranked |
| Arena · Japanese | #210 · ELO 1,212 | Unranked |
| Arena · coding | #263 · ELO 1,346 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Llama 3.3 70B Instruct: ¥57.18 per 1M output tokens, 77% less than 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.
Llama 3.3 70B Instruct
To count the number of 'r's in 'strawberry', I'll break down the word into its individual letters and then examine each one to identify the 'r's. Here are the steps:
1. **Write down the word 'strawberry' with its individual letters separated**: s-t-r-a-w-b-e-r-r-y
2. **Examine each letter to find the 'r's**: Going through the word letter by letter, I identify the 'r's.
- The first 'r' appears after 't', so that's one 'r'.
- Continuing through the word, I find another 'r' after 'e', which gives me a second 'r'.
- Then, immediately after this second 'r', I find a third 'r'.
3. **Count the total number of 'r's identified**: From the step above, I've identified a total of 3 'r's in th…
12.6s217 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…
Llama 3.3 70B Instruct
# Step-by-step analysis of the problem:
1. **The error is occurring because the `map()` function is being called on `undefined`**: This means that the `users` prop is not being passed to the `UserList` component, or its value is `undefined`.
2. **The `map()` function is a method of arrays**: It is used to iterate over the elements of an array and apply a transformation to each element. If `users` is not an array (i.e., it's `undefined`), this method will not be available, hence the error.
3. **To fix this error, you need to ensure that `users` is always an array**: You can achieve this by adding a conditional statement to check if `users` is an array before calling `map()` on it.
# Fixed so…
28.4s560 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):…
Llama 3.3 70B Instruct
### Review and Suggestions
The provided Python function `get_data` appears to be designed to fetch data from a given URL, filter active items, and return the filtered results. Here's a review of the function focusing on readability, performance, and best practices, along with suggestions for improvement.
#### Issues and Improvements:
1. **Import Statements**: Import statements should be placed at the top of the file, not inside the function. This adheres to PEP 8, the official Python style guide.
2. **Exception Handling**: The `except` block is too broad. It's better to catch specific exceptions that you anticipate might occur. For example, `requests.get` might raise `requests.RequestExc…
40.3s815 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, Llama 3.3 70B Instruct or Muse Glimmer 30B?
- Per 1M output tokens, Llama 3.3 70B Instruct is ¥57.18 and Muse Glimmer 30B is ¥252 on FastMetal (yen, before tax), so Llama 3.3 70B Instruct is cheaper.
- How do the context windows of Llama 3.3 70B Instruct and Muse Glimmer 30B compare?
- Llama 3.3 70B Instruct takes 131,072 tokens; Muse Glimmer 30B takes 131,072.
- Can I use Llama 3.3 70B Instruct and Muse Glimmer 30B with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "llama-3.3-70b-instruct" 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 Llama 3.3 70B Instruct and Muse Glimmer 30B from the browser chat and the API. No monthly fee.