GPT-4.1 Nano vs LLM-jp-3.1 8x13B instruct4
Pricing, context window and real answers (September 2026)
GPT-4.1 Nano (OpenAI) 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
 GPT-4.1 Nano | LLM-jp-3.1 8x13B instruct4 | |
|---|---|---|
| Provider | OpenAI | LLM-jp |
| Input (per 1M tokens) | ¥17.87 | ¥16 |
| Output (per 1M tokens) | ¥71.48 | ¥79 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥54 | ¥56 |
| Context window | 1,047,576 tokens | 4,096 tokens |
| Release date | 4/14/2025 | 3/21/2026 |
| Input modalities | image, text, file | text |
| Throughput (p50) | — | — |
| Arena · overall | #243 · ELO 1,322 | Unranked |
| Arena · Japanese | #195 · ELO 1,234 | Unranked |
| Arena · coding | #226 · ELO 1,374 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-4.1 Nano: ¥71.48 per 1M output tokens, 10% less than LLM-jp-3.1 8x13B instruct4.
- For long documents, GPT-4.1 Nano: a 1,047,576-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.
GPT-4.1 Nano
Let's analyze the word "strawberry" step by step to count the number of 'r's.
1. Write down the word: **strawberry**
2. Examine each letter one by one:
- s: no
- t: no
- r: yes (first 'r')
- a: no
- w: no
- b: no
- e: no
- r: yes (second 'r')
- r: yes (third 'r')
- y: no
3. Counting the 'r's found:
- First 'r' (at position 3)
- Second 'r' (at position 8)
- Third 'r' (at position 9)
So, there are **3** 'r's in "strawberry."
**Final answer: 3**
2.0s183 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…
GPT-4.1 Nano
The error:
```
TypeError: Cannot read properties of undefined (reading 'map')
```
indicates that `users` is `undefined` at the time your `UserList` component is rendering, and you're trying to call `map` on it.
### Why is this happening?
In React, if a prop (`users` in this case) is not provided or is undefined, trying to do `users.map(...)` causes this error. This can happen if:
- The parent component does not pass `users`.
- `users` might be `null` or `undefined` initially, especially if data fetching is involved.
### How to fix it
**Option 1: Provide a default value for `users`**
Ensure that `users` defaults to an empty array if it is not provided:
```jsx
function UserList({ users…
4.3s514 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):…
GPT-4.1 Nano
Here's a review and an improved version of your function:
### Key improvements:
1. **Move imports to the top**: Imports should generally be at the top of the file, not inside functions.
2. **Specify exception types**: Catch specific exceptions rather than a generic `except`.
3. **Use context managers if needed**: Not necessary here, but good to consider.
4. **Avoid repeated code**: The sleep statement is the same whether there is a request exception or a non-200 status.
5. **Simplify filtering**: Use list comprehensions for clarity.
6. **Improve variable names**: For readability.
7. **Add optional headers or parameters** if needed (not required here).
8. **Optional:** Add more descriptive e…
3.4s391 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, GPT-4.1 Nano or LLM-jp-3.1 8x13B instruct4?
- Per 1M output tokens, GPT-4.1 Nano is ¥71.48 and LLM-jp-3.1 8x13B instruct4 is ¥79 on FastMetal (yen, before tax), so GPT-4.1 Nano is cheaper.
- How do the context windows of GPT-4.1 Nano and LLM-jp-3.1 8x13B instruct4 compare?
- GPT-4.1 Nano takes 1,047,576 tokens; LLM-jp-3.1 8x13B instruct4 takes 4,096.
- Can I use GPT-4.1 Nano and LLM-jp-3.1 8x13B instruct4 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-4.1-nano" 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 GPT-4.1 Nano and LLM-jp-3.1 8x13B instruct4 from the browser chat and the API. No monthly fee.
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