GPT-5.4 Nano vs Kimi K3.1 Pro
Pricing, context window and real answers (October 2026)
GPT-5.4 Nano (OpenAI) 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
 GPT-5.4 Nano |  Kimi K3.1 Pro | |
|---|---|---|
| Provider | OpenAI | Moonshot |
| Input (per 1M tokens) | $0.211 | $2.11 |
| Output (per 1M tokens) | $1.32 | $10.55 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $0.8704 | $7.39 |
| Context window | 400,000 tokens | 1,048,576 tokens |
| Release date | 3/17/2026 | 10/23/2026 |
| Input modalities | file, image, text | text, image, video |
| Throughput (p50) | 122 tokens/s (n=27) | — |
| Arena · overall | #163 · ELO 1,401 | Unranked |
| Arena · Japanese | #113 · ELO 1,375 | Unranked |
| Arena · coding | #140 · ELO 1,460 | 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?
- On price, GPT-5.4 Nano: $1.32 per 1M output tokens, 88% less than Kimi K3.1 Pro.
- For long documents, Kimi K3.1 Pro: a 1,048,576-token context window against 400,000 for GPT-5.4 Nano.
- 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-5.4 Nano
**Step 1:** Write the word: **strawberry**
**Step 2:** Count each letter **r** in the word:
- s **t r** a w b e **r r** y
There are **3** **r**’s in total (**one** after the **t**, and **two** near the end).
✅ **Answer: 3**
1.5s86 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…
GPT-5.4 Nano
This error means that **`users` is `undefined` (or otherwise not an array)** when your component renders, so calling `users.map(...)` throws:
```js
users.map(...)
^^^^ reading 'map' of undefined
```
### Why it happens
Common causes:
- You render `<UserList />` before data has loaded (e.g., `users` comes from an async fetch).
- The parent component passes the wrong prop name (e.g., `user` instead of `users`).
- The API/parent state initializes `users` as `undefined` rather than `[]`.
- You’re destructuring a prop incorrectly upstream.
### Fix options
#### 1) Ensure `users` is always an array (recommended)
Initialize/default it in the component:
```js
function UserList({ users = []…
3.3s383 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):…
GPT-5.4 Nano
Here are key improvements (readability, performance, robustness, best practices) and a revised version of your function.
## What to improve
1. **Avoid bare `except:`**
Catch specific exceptions from `requests` (e.g., `requests.exceptions.RequestException`) to avoid hiding bugs.
2. **Prefer `raise_for_status()` or check status codes clearly**
`r.raise_for_status()` is a common pattern.
3. **Use exponential backoff (or at least a clear retry delay)**
Instead of sleeping the same amount every time, consider increasing delay.
4. **Reuse a `requests.Session()` (optional but best practice)**
If this function is called repeatedly, passing a session or creating one outside i…
4.4s718 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
Frequently asked questions
- Which is cheaper, GPT-5.4 Nano or Kimi K3.1 Pro?
- Per 1M output tokens, GPT-5.4 Nano is $1.32 and Kimi K3.1 Pro is $10.55 on FastMetal (US dollars, before tax), so GPT-5.4 Nano is cheaper.
- How do the context windows of GPT-5.4 Nano and Kimi K3.1 Pro compare?
- GPT-5.4 Nano takes 400,000 tokens; Kimi K3.1 Pro takes 1,048,576.
- Can I use GPT-5.4 Nano and Kimi K3.1 Pro with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.4-nano" 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 GPT-5.4 Nano and Kimi K3.1 Pro from the browser chat and the API. No monthly fee.