Model comparison

Claude Fable 5.1 vs Muse Spark 1.3

Pricing, context window and real answers (September 2026)

Claude Fable 5.1 (Anthropic) 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

anthropic logoClaude Fable 5.1meta logoMuse Spark 1.3
ProviderAnthropicMeta
Input (per 1M tokens)¥1,787¥219.9
Output (per 1M tokens)¥8,935¥747.65
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥6,255¥594
Context window1,000,000 tokens1,048,576 tokens
Release date9/1/20269/2/2026
Input modalitiestext, image, filetext, image, video, file, audio
Arena · overall#3 · ELO 1,504Unranked
Arena · JapaneseUnrankedUnranked
Arena · coding#34 · ELO 1,517Unranked

Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.

Which should you pick?

  • On price, Muse Spark 1.3: ¥747.65 per 1M output tokens, 92% less than Claude Fable 5.1.
  • For long documents, Muse Spark 1.3: a 1,048,576-token context window against 1,000,000 for Claude Fable 5.1.
  • 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.

Claude Fable 5.1

**Step 1: Write out the word letter by letter.** s - t - r - a - w - b - e - r - r - y **Step 2: Number each position.** 1. s 2. t 3. **r** 4. a 5. w 6. b 7. e 8. **r** 9. **r** 10. y **Step 3: Identify which positions contain 'r'.** - Position 3: r (in "str-") - Position 8: r (in "-ber-") - Position 9: r (in "-rry") **Step 4: Count them.** 3 + 1 + 1 = **3** **Answer: There are 3 'r's in "strawberry."** A helpful way to check: split the word into its parts — "straw" (1 r) + "berry" (2 r's) = 3 r's total.
7.9s259 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…

Claude Fable 5.1

The error means that when `UserList` rendered, the `users` prop was `undefined`, so calling `.map()` on it failed. This typically happens because: 1. **The parent isn't passing the prop** (or misspelled it, e.g. `<UserList user={...} />`), or 2. **The data hasn't loaded yet.** A common pattern is fetching users in a `useEffect` and storing them in state whose initial value is `undefined` (e.g. `useState()`), so the first render happens before the data arrives. **Fixes** Give the prop a default value so the component is safe to render with no data: ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); }…
10.8s564 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):…

Claude Fable 5.1

Here's a review of the function organized by category, followed by a refactored version. ## Issues ### Correctness / robustness 1. **Bare `except:`** — This catches *everything*, including `KeyboardInterrupt`, `SystemExit`, and bugs like `KeyError` from `item["active"]`. A malformed response would be silently retried three times and then swallowed. Catch `requests.RequestException` (and `ValueError` for bad JSON) specifically. 2. **Retrying non-retryable errors** — A 404 or 400 will never succeed on retry. Only retry on transient failures (timeouts, connection errors, 5xx, 429). 3. **Silent failure** — Returning `[]` after exhausting retries is indistinguishable from "the endpoint legitima…
27.7s2028 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, Claude Fable 5.1 or Muse Spark 1.3?
Per 1M output tokens, Claude Fable 5.1 is ¥8,935 and Muse Spark 1.3 is ¥747.65 on FastMetal (yen, before tax), so Muse Spark 1.3 is cheaper.
How do the context windows of Claude Fable 5.1 and Muse Spark 1.3 compare?
Claude Fable 5.1 takes 1,000,000 tokens; Muse Spark 1.3 takes 1,048,576.
Can I use Claude Fable 5.1 and Muse Spark 1.3 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-fable-5-1" 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 Claude Fable 5.1 and Muse Spark 1.3 from the browser chat and the API. No monthly fee.

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