gpt-oss-20b vs LLM-jp-3.1 8x13B instruct4
Pricing, context window and real answers (September 2026)
gpt-oss-20b (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-oss-20b | LLM-jp-3.1 8x13B instruct4 | |
|---|---|---|
| Provider | OpenAI | LLM-jp |
| Input (per 1M tokens) | ¥5.36 | ¥16 |
| Output (per 1M tokens) | ¥25.02 | ¥79 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥18 | ¥56 |
| Context window | 131,072 tokens | 4,096 tokens |
| Release date | 8/5/2025 | 3/21/2026 |
| Input modalities | text | text |
| Throughput (p50) | — | — |
| Arena · overall | #252 · ELO 1,317 | Unranked |
| Arena · Japanese | #179 · ELO 1,256 | Unranked |
| Arena · coding | #232 · ELO 1,369 | 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-oss-20b: ¥25.02 per 1M output tokens, 68% less than LLM-jp-3.1 8x13B instruct4.
- For long documents, gpt-oss-20b: a 131,072-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-oss-20b
**Count of ‘r’ in “strawberry”: 3**
---
### Step‑by‑step reasoning
1. **Write out the word in individual letters**
```
s t r a w b e r r y
```
2. **Identify each ‘r’**
- The first ‘r’: appears after the “t” → **r**
- The second ‘r’: appears in the part “berry” → **r**
- The third ‘r’: the next letter after that → **r**
3. **Verify there are no more letters left**
The remaining letters are “b”, “e”, “y”, none of which are “r”.
4. **Count the identified ‘r’s**
1 (first) + 1 (second) + 1 (third) = **3**
---
### Quick recap
- Word: **strawberry**
- Letters containing “r”: positions 3, 8, and 9.
- Total count: **3**.
11.6s371 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-oss-20b
### Why does the error happen?
`users.map(...)` can only run when **`users` is an array**.
The stack trace shows that the crash happens on line 12 of `UserList.js`, which is the
exact spot where the code tries to call `.map`.
The value that is being passed to `UserList` (or the initial value that the parent
creates) is **`undefined`** (or it could be `null`/`{}`). When JavaScript tries to
read `users.map`, it throws:
```
TypeError: Cannot read properties of undefined (reading 'map')
```
Typical reasons for this are:
1. The parent component **didn’t pass the `users` prop** at all.
2. The parent passed it but the value was **`undefined` / `null`** because data
hasn’t been loaded ye…
11.4s1303 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-oss-20b
Below is a quick “code‑review” style list that touches the three axes you asked for – **readability**, **performance**, and **best practices**.
After the bullet‑list I’ll paste a refactored version that incorporates the most common fixes.
---
## 1. Readability
| Issue | Why it hurts | Quick fix |
|-------|--------------|-----------|
| **Imports inside the function** | Every call recompiles the import tables and makes the module’s top‑level slower. | Move `import requests` and `import time` to the module’s global header. |
| **Bare `except:`** | Catches *everything* (KeyboardInterrupt, SystemExit, MemoryError, etc.) and swallows useful tracebacks. | Catch only the expected network-relate…
24.6s2267 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-oss-20b or LLM-jp-3.1 8x13B instruct4?
- Per 1M output tokens, gpt-oss-20b is ¥25.02 and LLM-jp-3.1 8x13B instruct4 is ¥79 on FastMetal (yen, before tax), so gpt-oss-20b is cheaper.
- How do the context windows of gpt-oss-20b and LLM-jp-3.1 8x13B instruct4 compare?
- gpt-oss-20b takes 131,072 tokens; LLM-jp-3.1 8x13B instruct4 takes 4,096.
- Can I use gpt-oss-20b and LLM-jp-3.1 8x13B instruct4 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-oss-20b" 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-oss-20b and LLM-jp-3.1 8x13B instruct4 from the browser chat and the API. No monthly fee.
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