GPT-6 Sol vs Kimi K3
Pricing, context window and real answers (September 2026)
GPT-6 Sol (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-6 Sol |  Kimi K3 | |
|---|---|---|
| Provider | OpenAI | Moonshot |
| Input (per 1M tokens) | ¥357.4 | ¥504 |
| Output (per 1M tokens) | ¥1,787 | ¥2,520 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,251 | ¥1,764 |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Release date | 9/22/2026 | 7/16/2026 |
| Input modalities | file, image, text | text, image |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #17 · ELO 1,485 |
| Arena · Japanese | Unranked | #2 · ELO 1,511 |
| Arena · coding | Unranked | #7 · ELO 1,538 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-6 Sol: ¥1,787 per 1M output tokens, 29% less than Kimi K3.
- For long documents, GPT-6 Sol: a 1,050,000-token context window against 1,048,576 for Kimi K3.
- 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-6 Sol
“Strawberry” is spelled **s-t-r-a-w-b-e-r-r-y**. There’s one **r** near the beginning and two near the end, for a total of **3**.
2.7s76 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-6 Sol
`users` is `undefined` when `UserList` renders, so calling `users.map(...)` throws the error. The component needs an array, but its parent may not be passing `users`, or the data may not have loaded yet.
You can default it to an empty array:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
Also check the parent component to make sure it passes an array:
```jsx
<UserList users={users} />
```
If `users` comes from an API, initialize its state as `[]` or show a loading state until the data arrives.
2.2s161 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-6 Sol
The main issues are the bare `except`, which hides errors such as malformed JSON, and retrying every non-200 response, including client errors that usually won’t improve with another attempt. The function also sleeps after its final attempt.
```python
import time
import requests
def get_data(url, retries=3):
if retries < 1:
raise ValueError("retries must be at least 1")
for attempt in range(retries):
try:
response = requests.get(url, timeout=10)
except requests.RequestException:
if attempt == retries - 1:
raise
else:
# Retry rate limits and server errors, but not other client errors.…
10.3s814 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-6 Sol or Kimi K3?
- Per 1M output tokens, GPT-6 Sol is ¥1,787 and Kimi K3 is ¥2,520 on FastMetal (yen, before tax), so GPT-6 Sol is cheaper.
- How do the context windows of GPT-6 Sol and Kimi K3 compare?
- GPT-6 Sol takes 1,050,000 tokens; Kimi K3 takes 1,048,576.
- Can I use GPT-6 Sol and Kimi K3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-6-sol" 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-6 Sol and Kimi K3 from the browser chat and the API. No monthly fee.