Claude Sonnet 4.6 vs LLM-jp-3.1 8x13B instruct4
Pricing, context window and real answers (August 2026)
Claude Sonnet 4.6 (Anthropic) and LLM-jp-3.1 8x13B instruct4 (Llm Jp), 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
 Claude Sonnet 4.6 | LLM-jp-3.1 8x13B instruct4 | |
|---|---|---|
| Provider | Anthropic | Llm Jp |
| Input (per 1M tokens) | ¥554.4 | ¥16 |
| Output (per 1M tokens) | ¥2,772 | ¥79 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,940 | ¥56 |
| Context window | 1,000,000 tokens | 4,096 tokens |
| Release date | 2/17/2026 | 3/21/2026 |
| Input modalities | text, image | text |
| Arena · overall | #32 · ELO 1,472 | Unranked |
| Arena · Japanese | #41 · ELO 1,438 | Unranked |
| Arena · coding | #14 · ELO 1,528 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, LLM-jp-3.1 8x13B instruct4: ¥79 per 1M output tokens, 97% less than Claude Sonnet 4.6.
- For long documents, Claude Sonnet 4.6: a 1,000,000-token context window against 4,096 for LLM-jp-3.1 8x13B instruct4.
- 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.
Claude Sonnet 4.6
## Counting the letter 'r' in 'strawberry'
Let me go through the word letter by letter:
| Position | Letter | Is it 'r'? |
|----------|--------|------------|
| 1 | s | No |
| 2 | t | No |
| 3 | r | ✅ Yes |
| 4 | a | No |
| 5 | w | No |
| 6 | b | No |
| 7 | e | No |
| 8 | r | ✅ Yes |
| 9 | r | ✅ Yes |
| 10 | y | No |
## Result
There are **3 r's** in 'strawberry'.
2.2s181 output tokens
LLM-jp-3.1 8x13B instruct4
To count the number of 'r's in the word 'strawberry', follow these steps:
1. Identify the word: The word we are examining is 'strawberry'.
2. Understand the task: We need to find and count all occurrences of the letter 'r' in this word.
3. Begin with the first letter: The first letter is 's', which is not 'r', so we move on to the next letter.
4. Proceed to the second letter: The second letter is 't', which is also not 'r', so we continue to the third letter.
5. Reach the third letter: The third letter is 'r'. We have found one 'r'.
6. Continue to the fourth letter: The fourth letter is 'a', which is not 'r', so we move on to the fifth letter.
7. Examine the fifth letter: The fifth letter i…
4.0s400 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…
Claude Sonnet 4.6
## Problem Analysis
The error occurs because `users` is `undefined` when the component renders. You're calling `.map()` on `undefined`, which throws a `TypeError`.
**Common causes:**
- The prop isn't passed by the parent component
- Data is still loading asynchronously when the component first renders
- The parent passes `undefined` or a misspelled prop name
---
## Solutions
### Option 1: Default Parameter Value (Simplest Fix)
```javascript
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
This assigns an empty array if `users` is `undefined`, so `.map()` always has an array to work with.
---
###…
9.4s798 output tokens
LLM-jp-3.1 8x13B instruct4
The error TypeError: Cannot read properties of undefined (reading 'map') suggests that the 'users' argument passed to the UserList component is undefined or does not have a 'map' method.
The cause of the problem may be that the users variable is not being passed correctly or is not defined in the parent component. Check the props being passed to the UserList component to ensure that they are defined and contain the expected data.
To fix the issue, you can add some error handling and debugging to your component. Try logging the users variable to the console to verify that it is not undefined:
```jsx
function UserList({ users }) {
console.log("Users:", users);
if (!users) {
return <…
3.0s279 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):…
Claude Sonnet 4.6
## Code Review and Improvements
### Issues Identified
1. **Imports inside function** – should be at module level
2. **Bare `except`** – catches everything including `KeyboardInterrupt`, `SystemExit`
3. **`== True` comparison** – not Pythonic
4. **No logging/error visibility** – silent failures make debugging hard
5. **Magic numbers** – hardcoded `2`, `10` with no explanation
6. **No distinction between retriable/non-retriable errors** – e.g., 404 should not be retried
7. **Inefficient list building** – list comprehension is cleaner
8. **No exponential backoff** – fixed sleep is naive for real-world retry logic
9. **Missing type hints and docstring**
---
### Improved Version
```python
im…
14.4s1099 output tokens
LLM-jp-3.1 8x13B instruct4
The provided Python function aims to get data from a URL using the requests library, filter out specific items based on their "active" field, and return the result. Here are some suggestions to improve readability, performance, and adherence to best practices:
1. Configure the linter (e.g., flake8 or pylint) to ensure code quality and enforce a consistent coding style.
2. Use type hints to improve readability and maintainability.
3. Use context managers (with statement) for handling requests:
4. Rewrite the function using a more functional programming style:
Here's the improved version of the function:
```python
import requests
import time
from typing import List, Dict, Any
def get_da…
3.9s406 output tokens
Frequently asked questions
- Which is cheaper, Claude Sonnet 4.6 or LLM-jp-3.1 8x13B instruct4?
- Per 1M output tokens, Claude Sonnet 4.6 is ¥2,772 and LLM-jp-3.1 8x13B instruct4 is ¥79 on FastMetal (yen, before tax), so LLM-jp-3.1 8x13B instruct4 is cheaper.
- How do the context windows of Claude Sonnet 4.6 and LLM-jp-3.1 8x13B instruct4 compare?
- Claude Sonnet 4.6 takes 1,000,000 tokens; LLM-jp-3.1 8x13B instruct4 takes 4,096.
- Can I use Claude Sonnet 4.6 and LLM-jp-3.1 8x13B instruct4 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-sonnet-4-6" or "llm-jp-3.1-8x13b-instruct4" 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 Claude Sonnet 4.6 and LLM-jp-3.1 8x13B instruct4 from the browser chat and the API. No monthly fee.