Model comparison

Fugu Ultra v2 vs Muse Spark 1.2

Pricing, context window and real answers (September 2026)

Fugu Ultra v2 (Sakana AI) 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

Fugu Ultra v2meta logoMuse Spark 1.2
ProviderSakana AIMeta
Input (per 1M tokens)¥893.5¥219.9
Output (per 1M tokens)¥5,361¥747.65
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥3,574¥594
Context window1,000,000 tokens1,048,576 tokens
Release date9/11/20268/5/2026
Input modalitiestext, image, filetext, image, video, file, audio
Throughput (p50)
Arena · overallUnranked#4 · ELO 1,500
Arena · JapaneseUnrankedUnranked
Arena · codingUnranked#9 · ELO 1,536

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, 86% less than Fugu Ultra v2.
  • For long documents, Muse Spark 1.2: a 1,048,576-token context window against 1,000,000 for Fugu Ultra v2.
  • 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.

Fugu Ultra v2

**Answer: 3** **Step-by-step reasoning:** 1. **Write out the word letter by letter**, assigning each a position: | Position | Letter | Is it 'r'? | |---|---|---| | 1 | s | no | | 2 | t | no | | 3 | **r** | ✅ yes | | 4 | a | no | | 5 | w | no | | 6 | b | no | | 7 | e | no | | 8 | **r** | ✅ yes | | 9 | **r** | ✅ yes | | 10 | y | no | 2. **Tally the matches:** positions 3, 8, and 9 are 'r'. 3. **Sanity check by chunks:** "straw" contains one 'r' (str**a**w → the r in "str"), and "berry" contains two 'r's (be**rr**y). 1 + 2 = 3. 4. **Verify length:** the letters counted total 10, which matches the length of "strawberry" — so no letter was skipped or double-counted. **Conclusion:** There a…
10.2s435 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…

Fugu Ultra v2

## What the error means `TypeError: Cannot read properties of undefined (reading 'map')` means that when `UserList` rendered, `users` was `undefined`, and JavaScript can't read the `.map` property off `undefined`. The important detail: **the bug isn't really in `UserList`** — that's just where it surfaces. Destructuring `function UserList({ users })` does *not* throw when the prop is missing; it silently gives you `undefined`. The crash is deferred to the first property access, which is `.map` on line 12. So the real question is: why is `props.users` not an array? ## Why `users` is undefined **1. Async data hasn't arrived yet — by far the most common cause.** ```jsx const [users, setUs…
70.8s5286 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):…

Fugu Ultra v2

# Final Code Review: `get_data` The function is compact and its intent is clear, but as written it will **fail silently in production**. Two defects dominate everything else: 1. The bare `except:` swallows every error — including `KeyboardInterrupt` and genuine logic bugs. 2. A total failure and a legitimately empty dataset both return `[]`, so callers cannot tell "the service is down" from "there are no active records." Together these mean an outage looks exactly like a successful empty response. Everything else below is meaningful improvement; those two are the difference between code that fails loudly and code that fails invisibly. --- ## 1. Correctness and error handling ### 1.1 `e…
281.1s23317 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, Fugu Ultra v2 or Muse Spark 1.2?
Per 1M output tokens, Fugu Ultra v2 is ¥5,361 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 Fugu Ultra v2 and Muse Spark 1.2 compare?
Fugu Ultra v2 takes 1,000,000 tokens; Muse Spark 1.2 takes 1,048,576.
Can I use Fugu Ultra v2 and Muse Spark 1.2 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "fugu-ultra-v2" 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 Fugu Ultra v2 and Muse Spark 1.2 from the browser chat and the API. No monthly fee.

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