Kimi K2.6 vs Llama 3.1 8B Instruct
Pricing, context window and real answers (September 2026)
Kimi K2.6 (Moonshot) and Llama 3.1 8B Instruct (Meta), 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
 Kimi K2.6 |  Llama 3.1 8B Instruct | |
|---|---|---|
| Provider | Moonshot | Meta |
| Input (per 1M tokens) | ¥159.6 | ¥8.94 |
| Output (per 1M tokens) | ¥672 | ¥14.3 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥496 | ¥16 |
| Context window | 262,144 tokens | 131,072 tokens |
| Release date | 4/20/2026 | 7/23/2024 |
| Input modalities | text, image | text |
| Throughput (p50) | — | — |
| Arena · overall | #52 · ELO 1,460 | #329 · ELO 1,211 |
| Arena · Japanese | #36 · ELO 1,443 | #243 · ELO 1,087 |
| Arena · coding | #39 · ELO 1,514 | #323 · ELO 1,260 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Llama 3.1 8B Instruct: ¥14.3 per 1M output tokens, 98% less than Kimi K2.6.
- On the Overall arena board, Kimi K2.6 ranks higher (#52; Llama 3.1 8B Instruct is #329).
- On the Japanese arena board, Kimi K2.6 ranks higher (#36; Llama 3.1 8B Instruct is #243).
- On the Coding arena board, Kimi K2.6 ranks higher (#39; Llama 3.1 8B Instruct is #323).
- For long documents, Kimi K2.6: a 262,144-token context window against 131,072 for Llama 3.1 8B Instruct.
- 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.
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
Llama 3.1 8B Instruct
To count the number of 'r's in 'strawberry', I will break down the word into its individual letters and examine each one. Here's the step-by-step process:
1. The word 'strawberry' consists of the following letters: s-t-r-a-w-b-e-r-r-y.
2. I will start by counting the letters that are not 'r'. The word has 1 's', 1 't', 1 'a', 1 'w', 1 'b', 1 'e', 1 'y'.
3. Next, I will count the number of 'r's. The word has 2 'r's, one of which is part of the letter combination 'rr'.
Therefore, there are 2 'r's in the word 'strawberry'.
9.7s169 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…
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
Llama 3.1 8B Instruct
The error `TypeError: Cannot read properties of undefined (reading 'map')` typically occurs when you're trying to access a property (in this case, `map`) on an object that is `undefined`.
In your case, the `users` prop passed to the `UserList` component is `undefined`. This is likely because the parent component that renders `UserList` is not passing the `users` prop, or the prop is not being properly initialized.
To fix this error, you can add a simple check to ensure that `users` is not `undefined` before trying to call `map` on it:
```javascript
function UserList({ users }) {
if (!users) return null; // or return a default message, e.g. "No users found"
return (
<ul>
{us…
7.9s292 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):…
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
Llama 3.1 8B Instruct
Here are some suggestions for improving the function's readability, performance, and best practices:
**Readability Improvements**
1. **Function name**: Consider renaming `get_data` to `fetch_active_items` to better reflect its purpose.
2. **Variable naming**: Use more descriptive variable names, such as `response` instead of `r`, and `active_items` instead of `result`.
3. **Code organization**: Break up the function into smaller, more focused sections. This will improve readability and make it easier to understand the logic.
4. **Type hints**: Add type hints for function parameters and return types to make the code more self-documenting.
**Performance Improvements**
1. **Use a more effic…
29.7s533 output tokens
Frequently asked questions
- Which is cheaper, Kimi K2.6 or Llama 3.1 8B Instruct?
- Per 1M output tokens, Kimi K2.6 is ¥672 and Llama 3.1 8B Instruct is ¥14.3 on FastMetal (yen, before tax), so Llama 3.1 8B Instruct is cheaper.
- How do the context windows of Kimi K2.6 and Llama 3.1 8B Instruct compare?
- Kimi K2.6 takes 262,144 tokens; Llama 3.1 8B Instruct takes 131,072.
- Which ranks higher, Kimi K2.6 or Llama 3.1 8B Instruct?
- Kimi K2.6 ranks higher on the public arena (Kimi K2.6 #36, Llama 3.1 8B Instruct #243). Ranks move as the leaderboard updates.
- Can I use Kimi K2.6 and Llama 3.1 8B Instruct with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "kimi-k2.6" or "llama-3.1-8b-instruct" 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 Kimi K2.6 and Llama 3.1 8B Instruct from the browser chat and the API. No monthly fee.