Claude Sonnet 5.5 vs Kimi K3.1 Pro
Pricing, context window and real answers (October 2026)
Claude Sonnet 5.5 (Anthropic) and Kimi K3.1 Pro (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
 Claude Sonnet 5.5 |  Kimi K3.1 Pro | |
|---|---|---|
| Provider | Anthropic | Moonshot |
| Input (per 1M tokens) | $2.11 | $2.11 |
| Output (per 1M tokens) | $10.55 | $10.55 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $7.39 | $7.39 |
| Context window | 1,000,000 tokens | 1,048,576 tokens |
| Release date | 9/28/2026 | 10/23/2026 |
| Input modalities | text, image, file | text, image, video |
| Throughput (p50) | 319 tokens/s (n=24) | — |
| Arena · overall | #29 · ELO 1,478 | Unranked |
| Arena · Japanese | #27 · ELO 1,468 | Unranked |
| Arena · coding | #26 · ELO 1,528 | Unranked |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-22; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- Output pricing is identical ($10.55 per 1M tokens).
- For long documents, Kimi K3.1 Pro: a 1,048,576-token context window against 1,000,000 for Claude Sonnet 5.5.
- 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.
Claude Sonnet 5.5
Let me go through the word letter by letter.
**strawberry**
| Position | Letter |
|---|---|
| 1 | s |
| 2 | t |
| 3 | **r** ← 1st |
| 4 | a |
| 5 | w |
| 6 | b |
| 7 | e |
| 8 | **r** ← 2nd |
| 9 | **r** ← 3rd |
| 10 | y |
**Step-by-step reasoning:**
1. I split the word into individual letters: s-t-r-a-w-b-e-r-r-y (10 letters total).
2. I checked each letter for 'r'.
3. The first 'r' is in position 3, in "str…".
4. The second and third 'r's are in positions 8 and 9, in the "…rry" ending.
**Answer: There are 3 r's in "strawberry".**
A common mistake is to see "berry" as having only one 'r' (or to treat the double-r as a single letter), which leads to the incorrect answer of 2.
3.1s332 output tokens
Kimi K3.1 Pro
There are **3** ‘r’s in **“strawberry.”**
1. Write out each letter: **s – t – r – a – w – b – e – r – r – y**
2. Locate the ‘r’s: positions **3, 8, and 9**.
3. Count them: **1 + 1 + 1 = 3**.
11.3s
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…
Claude Sonnet 5.5
## Cause
`users` is `undefined` when the component renders, so `users.map(...)` throws. This happens when:
1. **The parent doesn't pass the prop**, or passes it under a different name (e.g. `<UserList data={x} />` or a typo like `user=`).
2. **The data loads asynchronously.** On the first render, the state or fetch result hasn't arrived yet.
3. **The value is wrong.** For example, the API returns `{ users: [...] }` and you passed the whole object, or you're reading a property that doesn't exist (`response.data.users` vs `response.users`).
## Fixes
### 1. Default value (simplest)
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{use…
6.7s824 output tokens
Kimi K3.1 Pro
## What's causing the error
The error means `users` is `undefined` when the component renders, and you can't call `.map()` on `undefined`. The component itself is fine — the problem is that whatever renders `<UserList />` either isn't passing the prop, or is passing a value that isn't an array yet.
The most common cause is **async data fetching**: the parent renders `UserList` before the data has loaded.
```jsx
function App() {
const [users, setUsers] = useState(); // ❌ undefined on first render
useEffect(() => {
fetch('/api/users')
.then(res => res.json())
.then(setUsers);
}, []);
return <UserList users={users} />; // users is undefined here initially
}
```
On…
36.3s
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):…
Claude Sonnet 5.5
# Code Review
## Main Issues
### 1. Bare `except:` hides bugs (most important)
It catches everything, including `KeyboardInterrupt` and `SystemExit`. It also wraps your parsing logic, so a missing `"active"` key (`KeyError`) or bad JSON is treated as a network failure, retried 3 times with sleeps, and then silently becomes `[]`. Catch only `requests.RequestException`, and keep parsing outside the `try`.
### 2. Silent failure
Returning `[]` after all retries fails is indistinguishable from "the server returned no active items." Callers can't tell whether something went wrong. Raise an exception (or at least log) once retries are exhausted.
### 3. Retry logic
- It sleeps after the final at…
20.9s3003 output tokens
Kimi K3.1 Pro
The timeout and bounded retry loop are good starting points. The biggest issue is that failures—and even programming errors—are silently converted into retries and then `[]`.
### Suggested improvements
- **Avoid bare `except:`**. It catches `KeyboardInterrupt`, `KeyError`, JSON/schema errors, and other bugs. Retry only expected transient network failures; let malformed responses fail visibly.
- **Use a deliberate retry policy**. Retrying `401`, `403`, or `404` usually wastes time. Retry only transient statuses, use exponential backoff, and avoid sleeping after the final attempt.
- **Do not use `[]` for both failure and no results**. Prefer raising the final exception so callers can disting…
560.2s
Our write-up on this matchup
Kimi K3.1 Pro vs Claude Sonnet 5.5: same price, 2.7x the billFrequently asked questions
- Which is cheaper, Claude Sonnet 5.5 or Kimi K3.1 Pro?
- Both are $10.55 per 1M output tokens on FastMetal (US dollars, before tax).
- How do the context windows of Claude Sonnet 5.5 and Kimi K3.1 Pro compare?
- Claude Sonnet 5.5 takes 1,000,000 tokens; Kimi K3.1 Pro takes 1,048,576.
- Can I use Claude Sonnet 5.5 and Kimi K3.1 Pro with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-sonnet-5-5" or "kimi-k3.1-pro" 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 Claude Sonnet 5.5 and Kimi K3.1 Pro from the browser chat and the API. No monthly fee.