GPT-5 Mini vs Kimi K2.6
Pricing, context window and real answers (September 2026)
GPT-5 Mini (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 Mini |  Kimi K2.6 | |
|---|---|---|
| Provider | OpenAI | Moonshot |
| Input (per 1M tokens) | ¥44.68 | ¥159.6 |
| Output (per 1M tokens) | ¥357.4 | ¥672 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥223 | ¥496 |
| Context window | 400,000 tokens | 262,144 tokens |
| Release date | 8/7/2025 | 4/20/2026 |
| Input modalities | text, image, file | text, image |
| Throughput (p50) | — | — |
| Arena · overall | #163 · ELO 1,390 | #52 · ELO 1,460 |
| Arena · Japanese | #109 · ELO 1,365 | #36 · ELO 1,443 |
| Arena · coding | #172 · ELO 1,431 | #39 · 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 Mini: ¥357.4 per 1M output tokens, 47% less than Kimi K2.6.
- On the Overall arena board, Kimi K2.6 ranks higher (#52; GPT-5 Mini is #163).
- On the Japanese arena board, Kimi K2.6 ranks higher (#36; GPT-5 Mini is #109).
- On the Coding arena board, Kimi K2.6 ranks higher (#39; GPT-5 Mini is #172).
- For long documents, GPT-5 Mini: a 400,000-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 Mini
We examine the word "strawberry" letter by letter:
1. s — not an r (count = 0)
2. t — not an r (count = 0)
3. r — an r (count = 1)
4. a — not an r (count = 1)
5. w — not an r (count = 1)
6. b — not an r (count = 1)
7. e — not an r (count = 1)
8. r — an r (count = 2)
9. r — an r (count = 3)
10. y — not an r (count = 3)
Total number of 'r's = 3.
5.2s382 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 Mini
That error means users is undefined when you call users.map(...). map is an Array method, so calling it on undefined throws "Cannot read properties of undefined (reading 'map')".
Common causes
- The parent component didn't pass a users prop.
- users is still loading (e.g. fetched asynchronously) and is null/undefined until the fetch completes.
- The parent initialized users to null instead of an empty array.
How to fix
Choose one or more of these approaches depending on your app:
1) Initialize the parent state as an array
If users is state in the parent, initialize it to [] so the child always receives an array:
const [users, setUsers] = useState([]);
// fetch and setUsers(data)
2) Give…
8.0s966 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 Mini
Thanks — this is a nice simple function, but it can be improved in several ways: move imports to module scope, avoid broad except:, use connection pooling (Session) for performance, use specific exception types, add logging and docstring, avoid comparing to True, use list comprehensions, validate JSON shape, and implement backoff (or use urllib3 Retry).
Below are two improved alternatives and a short rationale for the changes.
1) A simple, clear improvement (small changes, explicit errors, backoff + jitter)
- Moves imports to top-level
- Uses requests.Session for connection pooling
- Catches specific exceptions (requests.RequestException, ValueError)
- Uses list comprehension and item.get(…
13.6s1702 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 Mini or Kimi K2.6?
- Per 1M output tokens, GPT-5 Mini is ¥357.4 and Kimi K2.6 is ¥672 on FastMetal (yen, before tax), so GPT-5 Mini is cheaper.
- How do the context windows of GPT-5 Mini and Kimi K2.6 compare?
- GPT-5 Mini takes 400,000 tokens; Kimi K2.6 takes 262,144.
- Which ranks higher, GPT-5 Mini or Kimi K2.6?
- Kimi K2.6 ranks higher on the public arena (GPT-5 Mini #109, Kimi K2.6 #36). Ranks move as the leaderboard updates.
- Can I use GPT-5 Mini and Kimi K2.6 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5-mini" 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 Mini and Kimi K2.6 from the browser chat and the API. No monthly fee.