gpt-oss-20b vs Llama 3.1 8B Instruct
Pricing, context window and real answers (September 2026)
gpt-oss-20b (OpenAI) 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
 gpt-oss-20b |  Llama 3.1 8B Instruct | |
|---|---|---|
| Provider | OpenAI | Meta |
| Input (per 1M tokens) | ¥5.36 | ¥8.94 |
| Output (per 1M tokens) | ¥25.02 | ¥14.3 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥18 | ¥16 |
| Context window | 131,072 tokens | 131,072 tokens |
| Release date | 8/5/2025 | 7/23/2024 |
| Input modalities | text | text |
| Throughput (p50) | — | — |
| Arena · overall | #252 · ELO 1,317 | #329 · ELO 1,211 |
| Arena · Japanese | #179 · ELO 1,256 | #243 · ELO 1,087 |
| Arena · coding | #232 · ELO 1,369 | #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, 43% less than gpt-oss-20b.
- On the Overall arena board, gpt-oss-20b ranks higher (#252; Llama 3.1 8B Instruct is #329).
- On the Japanese arena board, gpt-oss-20b ranks higher (#179; Llama 3.1 8B Instruct is #243).
- On the Coding arena board, gpt-oss-20b ranks higher (#232; Llama 3.1 8B Instruct is #323).
- 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
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…
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
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):…
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
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, gpt-oss-20b or Llama 3.1 8B Instruct?
- Per 1M output tokens, gpt-oss-20b is ¥25.02 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 gpt-oss-20b and Llama 3.1 8B Instruct compare?
- gpt-oss-20b takes 131,072 tokens; Llama 3.1 8B Instruct takes 131,072.
- Which ranks higher, gpt-oss-20b or Llama 3.1 8B Instruct?
- gpt-oss-20b ranks higher on the public arena (gpt-oss-20b #179, Llama 3.1 8B Instruct #243). Ranks move as the leaderboard updates.
- Can I use gpt-oss-20b and Llama 3.1 8B Instruct with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-oss-20b" 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 gpt-oss-20b and Llama 3.1 8B Instruct from the browser chat and the API. No monthly fee.