Model comparison

Muse Glimmer 30B vs Muse Spark 1.3

Pricing, context window and real answers (September 2026)

Muse Glimmer 30B (Meta) and Muse Spark 1.3 (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

meta logoMuse Glimmer 30Bmeta logoMuse Spark 1.3
ProviderMetaMeta
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 window131,072 tokens1,048,576 tokens
Release date8/10/20269/2/2026
Input modalitiestext, imagetext, image, video, file, audio
Arena · overallUnrankedUnranked
Arena · JapaneseUnrankedUnranked
Arena · codingUnrankedUnranked

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 1.3.
  • For long documents, Muse Spark 1.3: 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 1.3

The word is **strawberry** — there are **3** 'r's in it. Here's my reasoning step by step: 1. **Write out the word:** strawberry 2. **Break it into individual letters:** s - t - r - a - w - b - e - r - r - y 3. **Go through each letter one by one and check if it is 'r':** 1. s → not r, count = 0 2. t → not r, count = 0 3. r → is r, count = 1 4. a → not r, count = 1 5. w → not r, count = 1 6. b → not r, count = 1 7. e → not r, count = 1 8. r → is r, count = 2 9. r → is r, count = 3 10. y → not r, count = 3 4. **Total up the matches:** The 'r' appears at position 3, 8, and 9. **Final answer: 3**
10.5s1063 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 1.3

This error means `users` is `undefined` when your component tries to render. `users.map(...)` only works if `users` is an array. On the first render, if you haven't passed the prop yet, or your data hasn't loaded from an API yet, `users` is `undefined`, so JavaScript throws: > Cannot read properties of undefined (reading 'map') This almost always happens in one of these 2 cases: 1. You forgot to pass the prop: ```js <UserList /> // users is undefined! ``` vs. ```js <UserList users={myUsers} /> ``` 2. Your data is async and is `undefined` on the first render: ```js const [users, setUsers] = useState(); // undefined at first! // ... <UserList users={users} /> ``` ### How to fix it **1.…
16.7s1242 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 1.3

Here's a friendly review of your `get_data` function — it works, but there are a few readability, robustness, and performance issues worth fixing: ### 1. Readability Issues **a) Imports inside the function** ```python import requests import time ``` This runs on every call (though Python caches it). Move to the top of the file per PEP 8. **b) Poor variable names & magic numbers** `r`, `i`, `data`, `2`, `10`, `200` don't tell the reader much. **c) `== True` anti-pattern** ```python if item["active"] == True: ``` Just use `if item.get("active"):` or `is True`. The current version will also crash with `KeyError` if `active` is missing. **d) No docstring / type hints** No one knows what `ur…
26.9s2141 output tokens

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Frequently asked questions

Which is cheaper, Muse Glimmer 30B or Muse Spark 1.3?
Per 1M output tokens, Muse Glimmer 30B is ¥268.05 and Muse Spark 1.3 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 1.3 compare?
Muse Glimmer 30B takes 131,072 tokens; Muse Spark 1.3 takes 1,048,576.
Can I use Muse Glimmer 30B and Muse Spark 1.3 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "muse-glimmer-30b" or "muse-spark-1.3" 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 1.3 from the browser chat and the API. No monthly fee.

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