Model comparison

GPT-4.1 Nano vs GPT-5 Mini

Pricing, context window and real answers (September 2026)

GPT-4.1 Nano (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

openai logoGPT-4.1 Nanoopenai logoGPT-5 Mini
ProviderOpenAIOpenAI
Input (per 1M tokens)¥17.87¥44.68
Output (per 1M tokens)¥71.48¥357.4
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥54¥223
Context window1,047,576 tokens400,000 tokens
Release date4/14/20258/7/2025
Input modalitiesimage, text, filetext, image, file
Throughput (p50)
Arena · overall#243 · ELO 1,322#163 · ELO 1,390
Arena · Japanese#195 · ELO 1,234#109 · ELO 1,365
Arena · coding#226 · ELO 1,374#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-4.1 Nano: ¥71.48 per 1M output tokens, 80% less than GPT-5 Mini.
  • On the Overall arena board, GPT-5 Mini ranks higher (#163; GPT-4.1 Nano is #243).
  • On the Japanese arena board, GPT-5 Mini ranks higher (#109; GPT-4.1 Nano is #195).
  • On the Coding arena board, GPT-5 Mini ranks higher (#172; GPT-4.1 Nano is #226).
  • For long documents, GPT-4.1 Nano: a 1,047,576-token context window against 400,000 for GPT-5 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-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

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-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

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-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

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

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Frequently asked questions

Which is cheaper, GPT-4.1 Nano or GPT-5 Mini?
Per 1M output tokens, GPT-4.1 Nano is ¥71.48 and GPT-5 Mini is ¥357.4 on FastMetal (yen, before tax), so GPT-4.1 Nano is cheaper.
How do the context windows of GPT-4.1 Nano and GPT-5 Mini compare?
GPT-4.1 Nano takes 1,047,576 tokens; GPT-5 Mini takes 400,000.
Which ranks higher, GPT-4.1 Nano or GPT-5 Mini?
GPT-5 Mini ranks higher on the public arena (GPT-4.1 Nano #195, GPT-5 Mini #109). Ranks move as the leaderboard updates.
Can I use GPT-4.1 Nano and GPT-5 Mini with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4.1-nano" 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-4.1 Nano and GPT-5 Mini from the browser chat and the API. No monthly fee.

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