GPT-5.6 Luna vs MiMo-V2.5
Pricing, context window and real answers (August 2026)
GPT-5.6 Luna (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
 GPT-5.6 Luna | MiMo-V2.5 | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Input (per 1M tokens) | ¥35.74 | ¥25.02 |
| Output (per 1M tokens) | ¥214.44 | ¥50.04 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥143 | ¥50 |
| Context window | 1,050,000 tokens | 1,050,000 tokens |
| Release date | 7/9/2026 | 4/22/2026 |
| Input modalities | file, image, text | text, audio, image, video |
| Arena · overall | #63 · ELO 1,452 | #92 · ELO 1,434 |
| Arena · Japanese | #36 · ELO 1,444 | #137 · ELO 1,322 |
| Arena · coding | #69 · ELO 1,496 | #76 · 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, 77% less than GPT-5.6 Luna.
- On the Overall arena board, GPT-5.6 Luna ranks higher (#63; MiMo-V2.5 is #92).
- On the Japanese arena board, GPT-5.6 Luna ranks higher (#36; MiMo-V2.5 is #137).
- On the Coding arena board, GPT-5.6 Luna ranks higher (#69; MiMo-V2.5 is #76).
- 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-5.6 Luna
The word **“strawberry”** is spelled:
**s – t – r – a – w – b – e – r – r – y**
The letter **“r”** appears at positions **3, 8, and 9**.
**Answer: 3**
3.0s120 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-5.6 Luna
`users` is `undefined` when `UserList` renders, so calling `.map()` on it fails. `.map()` only exists on arrays.
Common causes include:
- The parent does not pass a `users` prop.
- The prop name differs, such as `userList` instead of `users`.
- Users are loaded asynchronously and are initially undefined.
- The API response has a different shape, such as `{ data: [...] }`.
### Provide a default value
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
The parent should pass an array:
```jsx
<UserList users={users} />
```
If the list comes from state, initialize it as an empty…
4.8s507 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-5.6 Luna
### Main issues
- Imports should be at module level, not inside the function.
- A bare `except:` catches everything, including programming errors and `KeyboardInterrupt`.
- The function sleeps even after the final failed attempt.
- It retries all HTTP statuses, including permanent errors such as `404`.
- `status_code == 200` excludes other successful `2xx` responses.
- `if item["active"] == True` should generally be `if item.get("active") is True`.
- A `requests.Session` can reuse connections and improve performance.
- Returning `[]` for every failure makes it impossible to distinguish “no active items” from “request failed.”
- Retries should generally use backoff rather than a fixed delay.…
23.3s1978 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
Frequently asked questions
- Which is cheaper, GPT-5.6 Luna or MiMo-V2.5?
- Per 1M output tokens, GPT-5.6 Luna is ¥214.44 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-5.6 Luna and MiMo-V2.5 compare?
- GPT-5.6 Luna takes 1,050,000 tokens; MiMo-V2.5 takes 1,050,000.
- Which ranks higher, GPT-5.6 Luna or MiMo-V2.5?
- GPT-5.6 Luna ranks higher on the public arena (GPT-5.6 Luna #36, MiMo-V2.5 #137). Ranks move as the leaderboard updates.
- Can I use GPT-5.6 Luna and MiMo-V2.5 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.6-luna" 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-5.6 Luna and MiMo-V2.5 from the browser chat and the API. No monthly fee.