GPT-4o-mini vs Pareto
Pricing, context window and real answers (September 2026)
GPT-4o-mini (OpenAI) and Pareto (Unbiased), 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
 GPT-4o-mini | Pareto | |
|---|---|---|
| Provider | OpenAI | Unbiased |
| Input (per 1M tokens) | ¥26.81 | ¥446.75 |
| Output (per 1M tokens) | ¥107.22 | ¥1,340.25 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥80 | ¥1,117 |
| Context window | 128,000 tokens | 262,144 tokens |
| Release date | 7/18/2024 | 9/17/2026 |
| Input modalities | text, image, file | text, image |
| Throughput (p50) | — | — |
| Arena · overall | #251 · ELO 1,318 | Unranked |
| Arena · Japanese | #187 · ELO 1,250 | Unranked |
| Arena · coding | #259 · ELO 1,348 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-4o-mini: ¥107.22 per 1M output tokens, 92% less than Pareto.
- For long documents, Pareto: a 262,144-token context window against 128,000 for GPT-4o-mini.
- 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.
GPT-4o-mini
To count the number of 'r's in the word "strawberry," we can follow these steps:
1. **Identify the word**: We have the word "strawberry."
2. **Break down the letters**: Let's write out the letters in the word:
- s
- t
- r
- a
- w
- b
- e
- r
- r
- y
3. **Locate the 'r's**: Now, we need to look for the letter 'r' among these letters.
- In the list of letters, we can see:
- The first 'r' is in the 3rd position.
- The second 'r' is in the 8th position.
- The third 'r' is in the 9th position.
4. **Count the occurrences**: We check each position we identified:
- There are three occurrences of 'r' in the word "strawberry."
5. **Conclusion**:…
2.1s239 output tokens
Pareto
To count the number of 'r's in the word "strawberry," let's break it down letter by letter:
1. **s** - not an 'r'
2. **t** - not an 'r'
3. **r** - **Yes**, this is the first 'r'.
4. **a** - not an 'r'
5. **w** - not an 'r'
6. **b** - not an 'r'
7. **e** - not an 'r'
8. **r** - **Yes**, this is the second 'r'.
9. **r** - **Yes**, this is the third 'r'.
10. **y** - not an 'r'
Counting the occurrences:
- The 3rd letter is 'r'.
- The 8th letter is 'r'.
- The 9th letter is 'r'.
There are **3** 'r's in "strawberry".
5.5s225 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…
GPT-4o-mini
The error you're encountering, `TypeError: Cannot read properties of undefined (reading 'map')`, indicates that the `users` prop is `undefined` when you try to call the `map` method on it.
In your `UserList` component, you're attempting to use `users.map(...)`, but if the `users` prop is not provided or is `undefined`, this will throw an error.
### Fixing the Error
1. **Default Props**: You can set a default value for the `users` prop to prevent the error when it is `undefined`.
```jsx
function UserList({ users = [] }) { // Default to an empty array
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```…
5.0s511 output tokens
Pareto
The error means `users` is `undefined` when `UserList` renders. Destructuring a prop does **not** protect against it:
```jsx
function UserList({ users }) { // users can still be undefined
return <ul>{users.map(...)}</ul>; // 💥
}
```
This usually happens when:
- The parent renders `<UserList />` without passing `users`
- The parent’s state starts as `undefined` before an async fetch finishes
- The API response is not an array, or `users` is passed as `undefined`
## Fix 1: Default the prop to an empty array
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
This works when…
11.6s1478 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):…
GPT-4o-mini
Your Python function, `get_data`, essentially performs a GET request, handles retries on failure, and processes the response JSON to return a filtered list of dictionaries. Below, I've highlighted several improvements regarding readability, performance, and best practices:
1. **Avoid blanket exceptions**: It’s best practice to specify which exceptions you expect, allowing for better debugging and error handling.
2. **Use `requests` built-in exception handling**: Handle specific requests exceptions, such as `requests.exceptions.RequestException`.
3. **Improve condition checks**: Check for `item['active']` directly instead of comparing to `True`, which is more Pythonic.
4. **Use `time.sl…
8.8s628 output tokens
Pareto
The function is straightforward, but its error handling hides failures and retries requests that may never succeed.
### Main improvements
- **Move imports to module scope** for readability and conventional dependency management.
- **Avoid bare `except:`.** It catches everything, including programming errors and `KeyboardInterrupt`. Catch specific request failures instead.
- **Retry selectively.** Timeouts, connection failures, rate limits, and certain server errors may be temporary; most other HTTP errors should surface immediately.
- **Use exponential backoff** and avoid sleeping after the last attempt.
- **Use a list comprehension** to express the filtering and transformation directly.
-…
30.3s1090 output tokens
Frequently asked questions
- Which is cheaper, GPT-4o-mini or Pareto?
- Per 1M output tokens, GPT-4o-mini is ¥107.22 and Pareto is ¥1,340.25 on FastMetal (yen, before tax), so GPT-4o-mini is cheaper.
- How do the context windows of GPT-4o-mini and Pareto compare?
- GPT-4o-mini takes 128,000 tokens; Pareto takes 262,144.
- Can I use GPT-4o-mini and Pareto with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4o-mini" or "pareto" 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 GPT-4o-mini and Pareto from the browser chat and the API. No monthly fee.