Model comparison

GPT-4o-mini vs MiMo-V2.5

Pricing, context window and real answers (September 2026)

GPT-4o-mini (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-4o-miniMiMo-V2.5
ProviderOpenAIXiaomi
Input (per 1M tokens)¥26.81¥25.02
Output (per 1M tokens)¥107.22¥50.04
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥80¥50
Context window128,000 tokens1,050,000 tokens
Release date7/18/20244/22/2026
Input modalitiestext, image, filetext, audio, image, video
Throughput (p50)
Arena · overall#251 · ELO 1,318#96 · ELO 1,434
Arena · Japanese#187 · ELO 1,250#141 · ELO 1,321
Arena · coding#259 · ELO 1,348#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, 53% less than GPT-4o-mini.
  • On the Overall arena board, MiMo-V2.5 ranks higher (#96; GPT-4o-mini is #251).
  • On the Japanese arena board, MiMo-V2.5 ranks higher (#141; GPT-4o-mini is #187).
  • On the Coding arena board, MiMo-V2.5 ranks higher (#81; GPT-4o-mini is #259).
  • For long documents, MiMo-V2.5: a 1,050,000-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

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-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

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-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

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

Compare on more prompts →

Frequently asked questions

Which is cheaper, GPT-4o-mini or MiMo-V2.5?
Per 1M output tokens, GPT-4o-mini is ¥107.22 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-4o-mini and MiMo-V2.5 compare?
GPT-4o-mini takes 128,000 tokens; MiMo-V2.5 takes 1,050,000.
Which ranks higher, GPT-4o-mini or MiMo-V2.5?
MiMo-V2.5 ranks higher on the public arena (GPT-4o-mini #187, MiMo-V2.5 #141). Ranks move as the leaderboard updates.
Can I use GPT-4o-mini and MiMo-V2.5 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4o-mini" 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-4o-mini and MiMo-V2.5 from the browser chat and the API. No monthly fee.

More comparisons with GPT-4o-mini

More comparisons with MiMo-V2.5