Model comparison

Claude Sonnet 5 vs Muse Spark 1.2

Pricing, context window and real answers (August 2026)

Claude Sonnet 5 (Anthropic) and Muse Spark 1.2 (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 Sonnet 5meta logoMuse Spark 1.2
ProviderAnthropicMeta
Input (per 1M tokens)¥357.4¥219.9
Output (per 1M tokens)¥1,787¥747.65
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥1,251¥594
Context window1,000,000 tokens1,048,576 tokens
Release date6/30/20268/5/2026
Input modalitiestext, image, filetext, image, video, file, audio
Arena · overall#47 · ELO 1,461#4 · ELO 1,498
Arena · Japanese#33 · ELO 1,447Unranked
Arena · coding#22 · ELO 1,522#7 · ELO 1,533

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 1.2: ¥747.65 per 1M output tokens, 58% less than Claude Sonnet 5.
  • On the Overall arena board, Muse Spark 1.2 ranks higher (#4; Claude Sonnet 5 is #47).
  • On the Coding arena board, Muse Spark 1.2 ranks higher (#7; Claude Sonnet 5 is #22).
  • For long documents, Muse Spark 1.2: a 1,048,576-token context window against 1,000,000 for Claude Sonnet 5.
  • 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 Sonnet 5

# Counting 'r's in "strawberry" **Step 1: Spell out the word letter by letter** s - t - r - a - w - b - e - r - r - y **Step 2: Number each letter position** | Position | Letter | |----------|--------| | 1 | s | | 2 | t | | 3 | **r** | | 4 | a | | 5 | w | | 6 | b | | 7 | e | | 8 | **r** | | 9 | **r** | | 10 | y | **Step 3: Identify and count the 'r's** - Position 3: **r** ✓ (1st r) - Position 8: **r** ✓ (2nd r) - Position 9: **r** ✓ (3rd r) **Answer: There are 3 r's in "strawberry"**
5.9s405 output tokens

Muse Spark 1.2

There are **3** 'r's in "strawberry". Here is my reasoning step by step: 1. Write out the word and its spelling: **s-t-r-a-w-b-e-r-r-y** 2. Go through each letter one by one and check if it is an 'r': * 1. s - not an 'r' -> count = 0 * 2. t - not an 'r' -> count = 0 * 3. **r** - yes, it's an 'r' -> count = 1 * 4. a - not an 'r' -> count = 1 * 5. w - not an 'r' -> count = 1 * 6. b - not an 'r' -> count = 1 * 7. e - not an 'r' -> count = 1 * 8. **r** - yes, it's an 'r' -> count = 2 * 9. **r** - yes, it's an 'r' -> count = 3 * 10. y - not an 'r' -> count = 3 3. Final total = **3**.
13.3s1123 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 Sonnet 5

# Root Cause The `UserList` component receives `users` as a prop, but at the time it's rendered, `users` is `undefined` — not an empty array, but literally missing. When your code tries to call `.map()` on `undefined`, JavaScript throws that `TypeError`. This typically happens when: - The parent component hasn't fetched the data yet (e.g., an API call is still in progress) - The prop name doesn't match what's being passed down (typo) - The data source (API/state) genuinely returns `undefined` in some case # Fixes **1. Add a default prop value (quick fix)** ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </u…
8.8s750 output tokens

Muse Spark 1.2

This error means `users` is `undefined` when the component tries to render. You are calling `.map()` on `users` at line 12, but `.map()` only exists on arrays. If `users` is `undefined` or `null`, JavaScript throws: `Cannot read properties of undefined (reading 'map')`. This usually happens for 2 reasons: 1. You didn't pass the `users` prop to the component: `<UserList />` 2. Your data is async and `users` is `undefined` on the first render. For example: `const [users, setUsers] = useState()` without an initial value, and the data hasn't been fetched yet. ### Fix it You need to guarantee `users` is always an array before you call `.map()`. #### 1. Best Fix: Give it a default value U…
7.6s1142 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 Sonnet 5

## Review of `get_data` Function Here's an improved version followed by an explanation of the changes: ```python import logging import time from typing import Any import requests logger = logging.getLogger(__name__) def get_data( url: str, retries: int = 3, timeout: float = 10.0, backoff_factor: float = 2.0, ) -> list[dict[str, Any]]: """ Fetch active items from the given URL. Args: url: The endpoint to fetch data from. retries: Number of attempts before giving up. timeout: Request timeout in seconds. backoff_factor: Multiplier for exponential backoff between retries. Returns: A list of dicts with "name" and "id"…
14.0s1299 output tokens

Muse Spark 1.2

Here is a review of your function with a refactored, production-ready version: ### Issues in the Current Version #### 1. Readability 1. **Generic name:** `get_data` tells nothing about what it does. `get_active_items` is better. 2. **Imports inside function:** `import requests, time` should be at the top of the file. It's slower and violates PEP 8. 3. **Magic numbers:** `200`, `10`, `2` have no context. 4. **Verbose loop:** Manual `for` loop + `append` can be replaced with a list comprehension. 5. **No documentation/typing:** No docstring, no type hints, so callers don't know what it expects or returns. 6. **`== True` is redundant:** `if item["active"] == True:` should be `if item["a…
11.8s2278 output tokens

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Frequently asked questions

Which is cheaper, Claude Sonnet 5 or Muse Spark 1.2?
Per 1M output tokens, Claude Sonnet 5 is ¥1,787 and Muse Spark 1.2 is ¥747.65 on FastMetal (yen, before tax), so Muse Spark 1.2 is cheaper.
How do the context windows of Claude Sonnet 5 and Muse Spark 1.2 compare?
Claude Sonnet 5 takes 1,000,000 tokens; Muse Spark 1.2 takes 1,048,576.
Which ranks higher, Claude Sonnet 5 or Muse Spark 1.2?
Muse Spark 1.2 ranks higher on the public arena (Claude Sonnet 5 #33, Muse Spark 1.2 #4). Ranks move as the leaderboard updates.
Can I use Claude Sonnet 5 and Muse Spark 1.2 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-sonnet-5" or "muse-spark-1.2" 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 Sonnet 5 and Muse Spark 1.2 from the browser chat and the API. No monthly fee.

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