gpt-oss-120b vs Kimi K3
Pricing, context window and real answers (August 2026)
gpt-oss-120b (OpenAI) and Kimi K3 (Moonshot), 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-120b |  Kimi K3 | |
|---|---|---|
| Provider | OpenAI | Moonshot |
| Input (per 1M tokens) | ¥16 | ¥536.1 |
| Output (per 1M tokens) | ¥79 | ¥2,680.5 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥56 | ¥1,876 |
| Context window | 131,072 tokens | 1,048,576 tokens |
| Release date | 8/5/2025 | 7/16/2026 |
| Input modalities | text | text, image |
| Arena · overall | #186 · ELO 1,352 | #11 · ELO 1,486 |
| Arena · Japanese | #123 · ELO 1,320 | Unranked |
| Arena · coding | #190 · ELO 1,390 | #8 · ELO 1,530 |
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-120b: ¥79 per 1M output tokens, 97% less than Kimi K3.
- On the Overall arena board, Kimi K3 ranks higher (#11; gpt-oss-120b is #186).
- On the Coding arena board, Kimi K3 ranks higher (#8; gpt-oss-120b is #190).
- For long documents, Kimi K3: a 1,048,576-token context window against 131,072 for gpt-oss-120b.
- 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-120b
**Step‑by‑step count of the letter “r” in the word “strawberry”**
1. Write out the word with each letter in order, labeling its position:
| Position | Letter |
|----------|--------|
| 1 | s |
| 2 | t |
| 3 | **r** |
| 4 | a |
| 5 | w |
| 6 | b |
| 7 | e |
| 8 | **r** |
| 9 | **r** |
|10 | y |
2. Scan the list and mark every occurrence of the letter **r**.
- Position 3 → r (first occurrence)
- Position 8 → r (second occurrence)
- Position 9 → r (third occurrence)
3. Count the marked entries: there are **3** marked positions.
**Result:** The word “strawberry” contains **3** occurrences of the letter **r**…
1.7s332 output tokens
Kimi K3
# Counting the 'r's in "strawberry"
**Step 1: Write out each letter with its position**
| Position | Letter |
|----------|--------|
| 1 | s |
| 2 | t |
| 3 | **r** ✓ |
| 4 | a |
| 5 | w |
| 6 | b |
| 7 | e |
| 8 | **r** ✓ |
| 9 | **r** ✓ |
| 10 | y |
**Step 2: Identify each 'r'**
- Position 3: the 'r' in "st**r**"
- Position 8: the first 'r' in "be**r**ry"
- Position 9: the second 'r' in "ber**r**y"
**Step 3: Verify by splitting the word**
"Strawberry" = "straw" + "berry"
- "straw" contains **1** r
- "berry" contains **2** r's
**Answer: There are 3 r's in "strawberry."** 🍓
12.2s594 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-120b
### Why the `map` can’t be called
`Array.prototype.map` is a method that exists only on **arrays** (or array‑like objects).
When you see
```
TypeError: Cannot read properties of undefined (reading 'map')
at UserList (...)
```
it means that the variable you think is an array – `users` in this case – is actually **`undefined`** (or `null`).
React is trying to evaluate this line:
```jsx
{users.map(user => <li key={user.id}>{user.name}</li>)}
```
and it crashes because you can’t read `.map` from `undefined`.
---
## Common reasons `users` ends up undefined
| Reason | Typical scenario | How it shows up |
|--------|------------------|-----------------|
| **Prop not passed** | `<Use…
7.3s1610 output tokens
Kimi K3
## What's causing it
The error means `users` is `undefined` when the component renders — `.map()` only exists on arrays, so calling it on `undefined` throws. Your component code is fine; the problem is **upstream**: whatever renders `<UserList />` isn't passing a valid array.
The most common culprit is **async data fetching with uninitialized state** in the parent:
```jsx
function App() {
const [users, setUsers] = useState(); // ← undefined!
useEffect(() => {
fetch('/api/users')
.then(res => res.json())
.then(setUsers);
}, []);
return <UserList users={users} />; // undefined on first render
}
```
The component renders *before* the fetch resolves, so `users` is `…
47.5s1756 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-120b
Below is a **step‑by‑step review** of the original `get_data` implementation followed by a **refactored version** that addresses readability, performance, and modern Python best‑practice concerns.
---
## 1. What the original function does
```python
def get_data(url, retries=3):
import requests
import time
for i in range(retries):
try:
r = requests.get(url, timeout=10)
if r.status_code == 200:
data = r.json()
result = []
for item in data:
if item["active"] == True:
result.append({"name": item["name"], "id": item["id"]})
return result…
14.4s3132 output tokens
Kimi K3
This works, but there are several issues worth addressing. Here's a breakdown, followed by an improved version.
## Issues
### Correctness & best practices
1. **Bare `except:`** — catches *everything*, including `KeyboardInterrupt` and programming bugs like `KeyError` on a malformed item (which then get pointlessly retried). Catch `requests.RequestException` specifically.
2. **Silent failures** — errors are swallowed with no logging, and returning `[]` makes "API is down" indistinguishable from "no active items." At minimum, log; ideally, raise after the final attempt.
3. **Retrying non-retryable errors** — a 400/401/404 will never succeed on retry, but the code sleeps and retries anyway. O…
57.6s8060 output tokens
Frequently asked questions
- Which is cheaper, gpt-oss-120b or Kimi K3?
- Per 1M output tokens, gpt-oss-120b is ¥79 and Kimi K3 is ¥2,680.5 on FastMetal (yen, before tax), so gpt-oss-120b is cheaper.
- How do the context windows of gpt-oss-120b and Kimi K3 compare?
- gpt-oss-120b takes 131,072 tokens; Kimi K3 takes 1,048,576.
- Which ranks higher, gpt-oss-120b or Kimi K3?
- Kimi K3 ranks higher on the public arena (gpt-oss-120b #123, Kimi K3 #11). Ranks move as the leaderboard updates.
- Can I use gpt-oss-120b and Kimi K3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-oss-120b" or "kimi-k3" 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-120b and Kimi K3 from the browser chat and the API. No monthly fee.