GPT-4.1 Nano vs Pareto
Pricing, context window and real answers (September 2026)
GPT-4.1 Nano (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-4.1 Nano | Pareto | |
|---|---|---|
| Provider | OpenAI | Unbiased |
| Input (per 1M tokens) | ¥17.87 | ¥446.75 |
| Output (per 1M tokens) | ¥71.48 | ¥1,340.25 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥54 | ¥1,117 |
| Context window | 1,047,576 tokens | 262,144 tokens |
| Release date | 4/14/2025 | 9/17/2026 |
| Input modalities | image, text, file | text, image |
| Throughput (p50) | — | — |
| Arena · overall | #243 · ELO 1,322 | Unranked |
| Arena · Japanese | #195 · ELO 1,234 | Unranked |
| Arena · coding | #226 · ELO 1,374 | 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-4.1 Nano: ¥71.48 per 1M output tokens, 95% less than Pareto.
- For long documents, GPT-4.1 Nano: a 1,047,576-token context window against 262,144 for Pareto.
- 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-4.1 Nano
Let's analyze the word "strawberry" step by step to count the number of 'r's.
1. Write down the word: **strawberry**
2. Examine each letter one by one:
- s: no
- t: no
- r: yes (first 'r')
- a: no
- w: no
- b: no
- e: no
- r: yes (second 'r')
- r: yes (third 'r')
- y: no
3. Counting the 'r's found:
- First 'r' (at position 3)
- Second 'r' (at position 8)
- Third 'r' (at position 9)
So, there are **3** 'r's in "strawberry."
**Final answer: 3**
2.0s183 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-4.1 Nano
The error:
```
TypeError: Cannot read properties of undefined (reading 'map')
```
indicates that `users` is `undefined` at the time your `UserList` component is rendering, and you're trying to call `map` on it.
### Why is this happening?
In React, if a prop (`users` in this case) is not provided or is undefined, trying to do `users.map(...)` causes this error. This can happen if:
- The parent component does not pass `users`.
- `users` might be `null` or `undefined` initially, especially if data fetching is involved.
### How to fix it
**Option 1: Provide a default value for `users`**
Ensure that `users` defaults to an empty array if it is not provided:
```jsx
function UserList({ users…
4.3s514 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-4.1 Nano
Here's a review and an improved version of your function:
### Key improvements:
1. **Move imports to the top**: Imports should generally be at the top of the file, not inside functions.
2. **Specify exception types**: Catch specific exceptions rather than a generic `except`.
3. **Use context managers if needed**: Not necessary here, but good to consider.
4. **Avoid repeated code**: The sleep statement is the same whether there is a request exception or a non-200 status.
5. **Simplify filtering**: Use list comprehensions for clarity.
6. **Improve variable names**: For readability.
7. **Add optional headers or parameters** if needed (not required here).
8. **Optional:** Add more descriptive e…
3.4s391 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-4.1 Nano or Pareto?
- Per 1M output tokens, GPT-4.1 Nano is ¥71.48 and Pareto is ¥1,340.25 on FastMetal (yen, before tax), so GPT-4.1 Nano is cheaper.
- How do the context windows of GPT-4.1 Nano and Pareto compare?
- GPT-4.1 Nano takes 1,047,576 tokens; Pareto takes 262,144.
- Can I use GPT-4.1 Nano and Pareto with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4.1-nano" 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-4.1 Nano and Pareto from the browser chat and the API. No monthly fee.