GPT-5.6 Luna vs Kimi K2.6
Pricing, context window and real answers (August 2026)
GPT-5.6 Luna (OpenAI) and Kimi K2.6 (Moonshot), 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 |  Kimi K2.6 | |
|---|---|---|
| Provider | OpenAI | Moonshot |
| Input (per 1M tokens) | ¥35.74 | ¥169.77 |
| Output (per 1M tokens) | ¥214.44 | ¥714.8 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥143 | ¥527 |
| Context window | 1,050,000 tokens | 262,144 tokens |
| Release date | 7/9/2026 | 4/20/2026 |
| Input modalities | file, image, text | text, image |
| Arena · overall | #63 · ELO 1,452 | #49 · ELO 1,461 |
| Arena · Japanese | #36 · ELO 1,444 | #35 · ELO 1,445 |
| Arena · coding | #69 · ELO 1,496 | #34 · ELO 1,514 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-5.6 Luna: ¥214.44 per 1M output tokens, 70% less than Kimi K2.6.
- On the Overall arena board, Kimi K2.6 ranks higher (#49; GPT-5.6 Luna is #63).
- On the Japanese arena board, Kimi K2.6 ranks higher (#35; GPT-5.6 Luna is #36).
- On the Coding arena board, Kimi K2.6 ranks higher (#34; GPT-5.6 Luna is #69).
- For long documents, GPT-5.6 Luna: a 1,050,000-token context window against 262,144 for Kimi K2.6.
- 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
Kimi K2.6
Here is the step-by-step count:
**Step 1:** Write out the word and number each letter.
1. s
2. t
3. **r** ← 1st 'r'
4. a
5. w
6. b
7. e
8. **r** ← 2nd 'r'
9. **r** ← 3rd 'r'
10. y
**Step 2:** Identify the positions containing the letter 'r'.
- The 3rd letter is **r**
- The 8th letter is **r**
- The 9th letter is **r**
**Step 3:** Tally the total.
There are **3** letter 'r's in "strawberry".
4.5s352 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
Kimi K2.6
The error occurs because `users` is `undefined` when your component renders. The `.map()` method only works on arrays, so calling it on `undefined` throws this error.
This usually happens when:
- The parent component hasn't finished fetching data yet
- The `users` prop isn't being passed at all
- The prop is misspelled in the parent component
## Quick Fix
Set a **default value** for the `users` prop:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
## Alternative Fixes
**Optional chaining** (renders nothing if undefined):
```jsx
{users?.map(user => <li key={user.id}>{user.name}</li>)}
```…
71.8s864 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
Kimi K2.6
Here is a refactored version followed by a breakdown of the improvements.
### Refactored Function
```python
import logging
import time
from typing import Any
import requests
logger = logging.getLogger(__name__)
def fetch_active_items(
url: str,
*,
retries: int = 3,
timeout: float = 10.0,
backoff: float = 2.0,
) -> list[dict[str, Any]]:
"""Fetch active items from an API endpoint with retry logic.
Args:
url: The API endpoint URL.
retries: Number of retry attempts for transient failures.
timeout: HTTP request timeout in seconds.
backoff: Base delay in seconds between retries (linear backoff).
Returns:
A list of activ…
17.9s4061 output tokens
Frequently asked questions
- Which is cheaper, GPT-5.6 Luna or Kimi K2.6?
- Per 1M output tokens, GPT-5.6 Luna is ¥214.44 and Kimi K2.6 is ¥714.8 on FastMetal (yen, before tax), so GPT-5.6 Luna is cheaper.
- How do the context windows of GPT-5.6 Luna and Kimi K2.6 compare?
- GPT-5.6 Luna takes 1,050,000 tokens; Kimi K2.6 takes 262,144.
- Which ranks higher, GPT-5.6 Luna or Kimi K2.6?
- Kimi K2.6 ranks higher on the public arena (GPT-5.6 Luna #36, Kimi K2.6 #35). Ranks move as the leaderboard updates.
- Can I use GPT-5.6 Luna and Kimi K2.6 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.6-luna" or "kimi-k2.6" 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 Kimi K2.6 from the browser chat and the API. No monthly fee.