GPT-5.6 Luna vs MiMo-V2.6-Pro
Pricing, context window and real answers (November 2026)
GPT-5.6 Luna (OpenAI) and MiMo-V2.6-Pro (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-V2.6-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Input (per 1M tokens) | $0.211 | $0.459 |
| Output (per 1M tokens) | $1.27 | $0.9179 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $0.844 | $0.9179 |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Release date | 7/9/2026 | 9/21/2026 |
| Input modalities | file, image, text | text, image, video, audio |
| Throughput (p50) | 163 tokens/s (n=28) | 126 tokens/s (n=28) |
| Arena · overall | #76 · ELO 1,453 | #29 · ELO 1,480 |
| Arena · Japanese | #58 · ELO 1,433 | Unranked |
| Arena · coding | #78 · ELO 1,502 | #14 · ELO 1,538 |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-28; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, MiMo-V2.6-Pro: $0.9179 per 1M output tokens, 28% less than GPT-5.6 Luna.
- On the Overall arena board, MiMo-V2.6-Pro ranks higher (#29; GPT-5.6 Luna is #76).
- On the Coding arena board, MiMo-V2.6-Pro ranks higher (#14; GPT-5.6 Luna is #78).
- For long documents, GPT-5.6 Luna: a 1,050,000-token context window against 1,048,576 for MiMo-V2.6-Pro.
- 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-V2.6-Pro
# Counting the 'r's in "strawberry"
## Step 1: Spell out the word letter by letter
| Position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|----------|---|---|---|---|---|---|---|---|---|----|
| Letter | s | t | r | a | w | b | e | r | r | y |
## Step 2: Identify every 'r'
- **Position 3** → **r** ✅ (1st 'r')
- **Position 8** → **r** ✅ (2nd 'r')
- **Position 9** → **r** ✅ (3rd 'r')
All other letters (s, t, a, w, b, e, y) are not 'r'.
## Answer
There are **3** 'r's in "strawberry."
22.0s327 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-V2.6-Pro
# Fixing `Cannot read properties of undefined (reading 'map')`
## The Problem
The `users` prop is `undefined` when the component renders. This happens because `.map()` is being called on something that doesn't exist — JavaScript can't iterate over `undefined`.
This typically occurs when:
- The parent component doesn't pass the `users` prop at all
- The data is still loading (e.g., from an API call)
- A destructuring default doesn't exist
## The Fix
### Option 1: Provide a default value (simplest)
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
### Option 2: Add a safety check with conditi…
32.9s575 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-V2.6-Pro
# Code Review: `get_data` Function
## Issues Identified
Here's my review organized by category, with a final improved version at the end.
---
### 🔴 Best Practices
1. **Imports inside the function** — `import requests` and `import time` are executed on *every* call. Move them to the top of the file (module-level).
2. **Bare `except:`** — This catches *everything*, including `KeyboardInterrupt` and `SystemExit`. Always catch specific exceptions.
3. **`== True` comparison** — Verbose and unnecessary. Use the object's truthiness directly.
4. **No logging** — Silent failures make debugging nearly impossible.
5. **Magic numbers** — `timeout=10` and `time.sleep(2)` are unexplained constan…
42.5s983 output tokens
Frequently asked questions
- Which is cheaper, GPT-5.6 Luna or MiMo-V2.6-Pro?
- Per 1M output tokens, GPT-5.6 Luna is $1.27 and MiMo-V2.6-Pro is $0.9179 on FastMetal (US dollars, before tax), so MiMo-V2.6-Pro is cheaper.
- How do the context windows of GPT-5.6 Luna and MiMo-V2.6-Pro compare?
- GPT-5.6 Luna takes 1,050,000 tokens; MiMo-V2.6-Pro takes 1,048,576.
- Which ranks higher, GPT-5.6 Luna or MiMo-V2.6-Pro?
- MiMo-V2.6-Pro ranks higher on the public arena (GPT-5.6 Luna #58, MiMo-V2.6-Pro #29). Ranks move as the leaderboard updates.
- Can I use GPT-5.6 Luna and MiMo-V2.6-Pro with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.6-luna" or "mimo-v2.6-pro" 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-V2.6-Pro from the browser chat and the API. No monthly fee.