Model comparison

Fugu Max vs Llama 3.1 8B Instruct

Pricing, context window and real answers (September 2026)

Fugu Max (Sakana AI) and Llama 3.1 8B Instruct (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 Maxmeta-llama logoLlama 3.1 8B Instruct
ProviderSakana AIMeta
Input (per 1M tokens)¥357.4¥8.94
Output (per 1M tokens)¥1,072.2¥14.3
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥894¥16
Context window1,000,000 tokens131,072 tokens
Release date9/11/20267/23/2024
Input modalitiestext, image, filetext
Throughput (p50)
Arena · overallUnranked#329 · ELO 1,211
Arena · JapaneseUnranked#243 · ELO 1,087
Arena · codingUnranked#323 · ELO 1,260

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

Which should you pick?

  • On price, Llama 3.1 8B Instruct: ¥14.3 per 1M output tokens, 99% less than Fugu Max.
  • For long documents, Fugu Max: a 1,000,000-token context window against 131,072 for Llama 3.1 8B Instruct.
  • 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 Max

The word **“strawberry”** has **3** letters **“r”**. Step by step: 1. Write the word: **s t r a w b e r r y** 2. Check each letter: - s — no - t — no - **r** — yes, 1st - a — no - w — no - b — no - e — no - **r** — yes, 2nd - **r** — yes, 3rd - y — no So, the total number of **‘r’s** in **“strawberry”** is **3**.
3.7s261 output tokens

Llama 3.1 8B Instruct

To count the number of 'r's in 'strawberry', I will break down the word into its individual letters and examine each one. Here's the step-by-step process: 1. The word 'strawberry' consists of the following letters: s-t-r-a-w-b-e-r-r-y. 2. I will start by counting the letters that are not 'r'. The word has 1 's', 1 't', 1 'a', 1 'w', 1 'b', 1 'e', 1 'y'. 3. Next, I will count the number of 'r's. The word has 2 'r's, one of which is part of the letter combination 'rr'. Therefore, there are 2 'r's in the word 'strawberry'.
9.7s169 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 Max

The error means `users` is `undefined` when `UserList` renders, so `users.map(...)` throws: ```js function UserList({ users }) { // if `users` is not passed, this is undefined return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` Common causes: 1. Parent renders `<UserList />` without the `users` prop. 2. State is initialized as `undefined`: ```js const [users, setUsers] = useState(); ``` 3. Async data hasn’t loaded yet, but the component already renders. 4. The API returned something unexpected, e.g. `undefined`, an object, or an error response. ## Fixes ### 1. Default the prop to an empty array ```jsx function UserList({ use…
10.6s1293 output tokens

Llama 3.1 8B Instruct

The error `TypeError: Cannot read properties of undefined (reading 'map')` typically occurs when you're trying to access a property (in this case, `map`) on an object that is `undefined`. In your case, the `users` prop passed to the `UserList` component is `undefined`. This is likely because the parent component that renders `UserList` is not passing the `users` prop, or the prop is not being properly initialized. To fix this error, you can add a simple check to ensure that `users` is not `undefined` before trying to call `map` on it: ```javascript function UserList({ users }) { if (!users) return null; // or return a default message, e.g. "No users found" return ( <ul> {us…
7.9s292 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 Max

Here’s a review with concrete improvements. ## Main issues 1. **Bare `except:`** - Catches everything, including `KeyboardInterrupt`, `SystemExit`, and programming errors. - Catch `requests.RequestException` instead, plus `ValueError` for JSON parsing if needed. 2. **Retries everything, including non-retryable errors** - A `404` or `401` will be retried even though retrying will not help. - Retry only transient failures: network errors, `429`, and `5xx`. 3. **Fixed 2-second sleep** - No exponential backoff. Repeated retries can hammer the server. - Use exponential backoff, optionally with jitter. 4. **Silent failure** - Returning `[]` after all retries makes it hard…
24.7s3795 output tokens

Llama 3.1 8B Instruct

Here are some suggestions for improving the function's readability, performance, and best practices: **Readability Improvements** 1. **Function name**: Consider renaming `get_data` to `fetch_active_items` to better reflect its purpose. 2. **Variable naming**: Use more descriptive variable names, such as `response` instead of `r`, and `active_items` instead of `result`. 3. **Code organization**: Break up the function into smaller, more focused sections. This will improve readability and make it easier to understand the logic. 4. **Type hints**: Add type hints for function parameters and return types to make the code more self-documenting. **Performance Improvements** 1. **Use a more effic…
29.7s533 output tokens

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Frequently asked questions

Which is cheaper, Fugu Max or Llama 3.1 8B Instruct?
Per 1M output tokens, Fugu Max is ¥1,072.2 and Llama 3.1 8B Instruct is ¥14.3 on FastMetal (yen, before tax), so Llama 3.1 8B Instruct is cheaper.
How do the context windows of Fugu Max and Llama 3.1 8B Instruct compare?
Fugu Max takes 1,000,000 tokens; Llama 3.1 8B Instruct takes 131,072.
Can I use Fugu Max and Llama 3.1 8B Instruct with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "fugu-max" or "llama-3.1-8b-instruct" 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 Max and Llama 3.1 8B Instruct from the browser chat and the API. No monthly fee.

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