Model comparison

GPT-4.1 Nano vs MiMo-V2.5

Pricing, context window and real answers (September 2026)

GPT-4.1 Nano (OpenAI) and MiMo-V2.5 (Xiaomi), 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 NanoMiMo-V2.5
ProviderOpenAIXiaomi
Input (per 1M tokens)¥17.87¥25.02
Output (per 1M tokens)¥71.48¥50.04
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥54¥50
Context window1,047,576 tokens1,050,000 tokens
Release date4/14/20254/22/2026
Input modalitiesimage, text, filetext, audio, image, video
Throughput (p50)
Arena · overall#243 · ELO 1,322#96 · ELO 1,434
Arena · Japanese#195 · ELO 1,234#141 · ELO 1,321
Arena · coding#226 · ELO 1,374#81 · ELO 1,491

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

Which should you pick?

  • On price, MiMo-V2.5: ¥50.04 per 1M output tokens, 30% less than GPT-4.1 Nano.
  • On the Overall arena board, MiMo-V2.5 ranks higher (#96; GPT-4.1 Nano is #243).
  • On the Japanese arena board, MiMo-V2.5 ranks higher (#141; GPT-4.1 Nano is #195).
  • On the Coding arena board, MiMo-V2.5 ranks higher (#81; GPT-4.1 Nano is #226).
  • For long documents, MiMo-V2.5: a 1,050,000-token context window against 1,047,576 for GPT-4.1 Nano.
  • 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

MiMo-V2.5

# Counting the 'r's in 'strawberry' Let me spell the word out letter by letter: | Position | Letter | Is it 'r'? | |----------|--------|------------| | 1 | **s** | ❌ | | 2 | **t** | ❌ | | 3 | **r** | ✅ (1) | | 4 | **a** | ❌ | | 5 | **w** | ❌ | | 6 | **b** | ❌ | | 7 | **e** | ❌ | | 8 | **r** | ✅ (2) | | 9 | **r** | ✅ (3) | | 10 | **y** | ❌ | ## Answer: **3** 'r's The three r's are found at positions **3**, **8**, and **9** in the word.
14.9s313 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

MiMo-V2.5

This error occurs because your `users` prop is `undefined` when the component tries to call `.map()` on it. This usually happens when: 1. The parent component doesn't pass a `users` prop 2. The `users` data is still loading (asynchronous operation) 3. There's a typo in the prop name when passing from parent ## How to Fix It ### 1. Add Default Props or Prop Validation Add a default value for the `users` prop: ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } // Or with PropTypes import PropTypes from 'prop-types'; function UserList({ users }) { return ( <ul> {users.map(user => <li key…
11.2s808 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

MiMo-V2.5

# Code Review: `get_data` Function ## Issues Identified | Category | Issue | Severity | |----------|-------|----------| | Style | Imports inside function body | Medium | | Reliability | Bare `except` catches `KeyboardInterrupt`/`SystemExit` | High | | Reliability | Silent failures — no logging | Medium | | Readability | `== True` comparison (redundant) | Low | | Readability | No docstring or type hints | Medium | | Performance | Could use list comprehension | Low | | Robustness | No exponential backoff on retries | Medium | | Robustness | `r.json()` can fail silently under bare except | High | | Style | Uninformative variable names (`r`, `i`) | Low | | Config | Magic numbers hardcoded (`ti…
33.6s1854 output tokens

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Frequently asked questions

Which is cheaper, GPT-4.1 Nano or MiMo-V2.5?
Per 1M output tokens, GPT-4.1 Nano is ¥71.48 and MiMo-V2.5 is ¥50.04 on FastMetal (yen, before tax), so MiMo-V2.5 is cheaper.
How do the context windows of GPT-4.1 Nano and MiMo-V2.5 compare?
GPT-4.1 Nano takes 1,047,576 tokens; MiMo-V2.5 takes 1,050,000.
Which ranks higher, GPT-4.1 Nano or MiMo-V2.5?
MiMo-V2.5 ranks higher on the public arena (GPT-4.1 Nano #195, MiMo-V2.5 #141). Ranks move as the leaderboard updates.
Can I use GPT-4.1 Nano and MiMo-V2.5 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4.1-nano" or "mimo-v2.5" 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 MiMo-V2.5 from the browser chat and the API. No monthly fee.

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