GPT-4o-mini vs GPT-5 Mini
Pricing, context window and real answers (September 2026)
GPT-4o-mini (OpenAI) and GPT-5 Mini (OpenAI), 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 | GPT-5 Mini | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input (per 1M tokens) | ¥26.81 | ¥44.68 |
| Output (per 1M tokens) | ¥107.22 | ¥357.4 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥80 | ¥223 |
| Context window | 128,000 tokens | 400,000 tokens |
| Release date | 7/18/2024 | 8/7/2025 |
| Input modalities | text, image, file | text, image, file |
| Throughput (p50) | — | — |
| Arena · overall | #251 · ELO 1,318 | #163 · ELO 1,390 |
| Arena · Japanese | #187 · ELO 1,250 | #109 · ELO 1,365 |
| Arena · coding | #259 · ELO 1,348 | #172 · ELO 1,431 |
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, 70% less than GPT-5 Mini.
- On the Overall arena board, GPT-5 Mini ranks higher (#163; GPT-4o-mini is #251).
- On the Japanese arena board, GPT-5 Mini ranks higher (#109; GPT-4o-mini is #187).
- On the Coding arena board, GPT-5 Mini ranks higher (#172; GPT-4o-mini is #259).
- For long documents, GPT-5 Mini: a 400,000-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
GPT-5 Mini
We examine the word "strawberry" letter by letter:
1. s — not an r (count = 0)
2. t — not an r (count = 0)
3. r — 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 — an r (count = 2)
9. r — an r (count = 3)
10. y — not an r (count = 3)
Total number of 'r's = 3.
5.2s382 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
GPT-5 Mini
That error means users is undefined when you call users.map(...). map is an Array method, so calling it on undefined throws "Cannot read properties of undefined (reading 'map')".
Common causes
- The parent component didn't pass a users prop.
- users is still loading (e.g. fetched asynchronously) and is null/undefined until the fetch completes.
- The parent initialized users to null instead of an empty array.
How to fix
Choose one or more of these approaches depending on your app:
1) Initialize the parent state as an array
If users is state in the parent, initialize it to [] so the child always receives an array:
const [users, setUsers] = useState([]);
// fetch and setUsers(data)
2) Give…
8.0s966 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
GPT-5 Mini
Thanks — this is a nice simple function, but it can be improved in several ways: move imports to module scope, avoid broad except:, use connection pooling (Session) for performance, use specific exception types, add logging and docstring, avoid comparing to True, use list comprehensions, validate JSON shape, and implement backoff (or use urllib3 Retry).
Below are two improved alternatives and a short rationale for the changes.
1) A simple, clear improvement (small changes, explicit errors, backoff + jitter)
- Moves imports to top-level
- Uses requests.Session for connection pooling
- Catches specific exceptions (requests.RequestException, ValueError)
- Uses list comprehension and item.get(…
13.6s1702 output tokens
Frequently asked questions
- Which is cheaper, GPT-4o-mini or GPT-5 Mini?
- Per 1M output tokens, GPT-4o-mini is ¥107.22 and GPT-5 Mini is ¥357.4 on FastMetal (yen, before tax), so GPT-4o-mini is cheaper.
- How do the context windows of GPT-4o-mini and GPT-5 Mini compare?
- GPT-4o-mini takes 128,000 tokens; GPT-5 Mini takes 400,000.
- Which ranks higher, GPT-4o-mini or GPT-5 Mini?
- GPT-5 Mini ranks higher on the public arena (GPT-4o-mini #187, GPT-5 Mini #109). Ranks move as the leaderboard updates.
- Can I use GPT-4o-mini and GPT-5 Mini with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4o-mini" or "gpt-5-mini" 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 GPT-5 Mini from the browser chat and the API. No monthly fee.