GPT-4.1 Mini vs MiMo-V2.6-Flash
Pricing, context window and real answers (September 2026)
GPT-4.1 Mini (OpenAI) and MiMo-V2.6-Flash (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
 GPT-4.1 Mini | MiMo-V2.6-Flash | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Input (per 1M tokens) | ¥71.48 | ¥25.02 |
| Output (per 1M tokens) | ¥285.92 | ¥50.04 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥214 | ¥50 |
| Context window | 1,047,576 tokens | 1,048,576 tokens |
| Release date | 4/14/2025 | 9/21/2026 |
| Input modalities | image, text, file | text, image, video, audio |
| Throughput (p50) | — | — |
| Arena · overall | #172 · ELO 1,383 | Unranked |
| Arena · Japanese | #135 · ELO 1,330 | Unranked |
| Arena · coding | #164 · ELO 1,433 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, MiMo-V2.6-Flash: ¥50.04 per 1M output tokens, 82% less than GPT-4.1 Mini.
- For long documents, MiMo-V2.6-Flash: a 1,048,576-token context window against 1,047,576 for GPT-4.1 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 Mini
Let's count the number of 'r's in the word "strawberry" step by step:
1. Write down the word: s t r a w b e r r y
2. Look at each letter and check if it is 'r':
- s → not 'r'
- t → not 'r'
- r → yes, 1st 'r'
- a → not 'r'
- w → not 'r'
- b → not 'r'
- e → not 'r'
- r → yes, 2nd 'r'
- r → yes, 3rd 'r'
- y → not 'r'
3. Total number of 'r's found: 3
**Answer:** There are 3 'r's in the word "strawberry".
2.0s176 output tokens
MiMo-V2.6-Flash
## Counting the 'r's in 'strawberry'
**Step 1: Write out each letter of the word individually:**
`s - t - r - a - w - b - e - r - r - y`
**Step 2: Go through each letter one by one and check if it's an 'r':**
| Position | Letter | Is it 'r'? | Running Count |
|----------|--------|------------|---------------|
| 1 | s | ❌ | 0 |
| 2 | t | ❌ | 0 |
| 3 | **r** | ✅ | **1** |
| 4 | a | ❌ | 1 |
| 5 | w | ❌ | 1 |
| 6 | b | ❌ | 1 |
| 7 | e | ❌ | 1 |
| 8 | **r** | ✅ | **2** |
| 9 | **r** | ✅ | **3** |
| 10 | y | ❌ | 3 |
**Answer: There are 3 'r's in 'strawberry'.** 🍓
The first 'r' appears at position 3 (after "st"), and the remaining two are the double 'rr' near the end of the word.
6.5s379 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 Mini
The error **"TypeError: Cannot read properties of undefined (reading 'map')"** means that the `users` prop passed to your `UserList` component is `undefined` at the time the component tries to render, so calling `.map()` on it throws an error.
### What's causing the error?
- Your component expects `users` to be an array, but for some reason it is `undefined` when the component renders.
- This could happen if:
- The parent component that passes the `users` prop did not pass it or passed `undefined`.
- The data is being fetched asynchronously and hasn't arrived yet.
- The default prop is missing or no default fallback is handled.
### How to fix it?
You want to ensure `users` is alway…
8.1s465 output tokens
MiMo-V2.6-Flash
## Cause of the Error
The error occurs because the `users` prop is `undefined` when the component first renders. When you try to call `.map()` on `undefined`, it throws:
```
TypeError: Cannot read properties of undefined (reading 'map')
```
This typically happens when:
1. The **parent component** hasn't passed `users` yet (e.g., data is still loading from an API)
2. The prop name **doesn't match** between parent and child
3. The prop is **intentionally optional** but used unconditionally
## Fixes
### 1. Default parameter value (simplest fix)
Set a default value for `users` so it's always an array:
```js
function UserList({ users = [] }) {
return (
<ul>
{users.map(user =>…
7.6s547 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 Mini
Your function is functional but can be improved for readability, performance, and best practices. Here are some suggestions and an improved version of your function:
### Issues and improvements
1. **Imports**: Import at the top of the file rather than inside the function.
2. **Catch specific exceptions**: Avoid bare `except:` clauses. Catch specific exceptions like `requests.RequestException` or `json.decoder.JSONDecodeError`.
3. **Use list comprehension**: Instead of a loop with `append()`, use list comprehension for clarity and conciseness.
4. **Check boolean conditions directly**: Instead of `item["active"] == True`, just use `item["active"]`.
5. **Avoid sleeping after last retry**: No…
5.6s690 output tokens
MiMo-V2.6-Flash
# Code Review: `get_data`
## Issues Identified
| Category | Issue |
|----------|-------|
| **Readability** | Imports inside function, vague names (`i`, `r`), no docstring/type hints |
| **Performance** | Manual loop instead of list comprehension, no `requests.Session` (no connection reuse) |
| **Best Practices** | Bare `except`, `== True`, silent failures, no backoff, no error propagation |
---
## Improved Version
```python
import time
import logging
import requests
from typing import Optional
logger = logging.getLogger(__name__)
def get_data(
url: str,
retries: int = 3,
timeout: float = 10,
backoff_factor: float = 2.0,
) -> Optional[list[dict]]:
"""
Fetch dat…
18.9s1208 output tokens
Frequently asked questions
- Which is cheaper, GPT-4.1 Mini or MiMo-V2.6-Flash?
- Per 1M output tokens, GPT-4.1 Mini is ¥285.92 and MiMo-V2.6-Flash is ¥50.04 on FastMetal (yen, before tax), so MiMo-V2.6-Flash is cheaper.
- How do the context windows of GPT-4.1 Mini and MiMo-V2.6-Flash compare?
- GPT-4.1 Mini takes 1,047,576 tokens; MiMo-V2.6-Flash takes 1,048,576.
- Can I use GPT-4.1 Mini and MiMo-V2.6-Flash with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4.1-mini" or "mimo-v2.6-flash" 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 Mini and MiMo-V2.6-Flash from the browser chat and the API. No monthly fee.