GPT-5.4 Nano vs Qwen3.7 Max
Pricing, context window and real answers (September 2026)
GPT-5.4 Nano (OpenAI) and Qwen3.7 Max (Qwen), 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 |  Qwen3.7 Max | |
|---|---|---|
| Provider | OpenAI | Qwen |
| Input (per 1M tokens) | ¥35.74 | ¥263.58 |
| Output (per 1M tokens) | ¥223.38 | ¥790.75 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥147 | ¥659 |
| Context window | 400,000 tokens | 1,000,000 tokens |
| Release date | 3/17/2026 | 5/21/2026 |
| Input modalities | file, image, text | text |
| Throughput (p50) | — | — |
| Arena · overall | #146 · ELO 1,402 | #34 · ELO 1,473 |
| Arena · Japanese | #107 · ELO 1,368 | Unranked |
| Arena · coding | #128 · ELO 1,460 | #21 · ELO 1,525 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GPT-5.4 Nano: ¥223.38 per 1M output tokens, 72% less than Qwen3.7 Max.
- On the Overall arena board, Qwen3.7 Max ranks higher (#34; GPT-5.4 Nano is #146).
- On the Coding arena board, Qwen3.7 Max ranks higher (#21; GPT-5.4 Nano is #128).
- For long documents, Qwen3.7 Max: a 1,000,000-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
Qwen3.7 Max
To count the number of 'r's in the word "strawberry", let's break the word down letter by letter from left to right:
1. **s** - not an 'r'
2. **t** - not an 'r'
3. **r** - This is the **1st** 'r'
4. **a** - not an 'r'
5. **w** - not an 'r'
6. **b** - not an 'r'
7. **e** - not an 'r'
8. **r** - This is the **2nd** 'r'
9. **r** - This is the **3rd** 'r'
10. **y** - not an 'r'
By examining each character individually, we can see that the letter 'r' appears in the 3rd, 8th, and 9th positions.
Therefore, there are **3** 'r's in "strawberry".
15.1s842 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-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
Qwen3.7 Max
This error occurs because the `users` prop being passed to your `UserList` component is **`undefined`** at the time React tries to render it. JavaScript cannot call the `.map()` method on `undefined`, which throws the error.
This usually happens for one of three reasons:
1. **Asynchronous Data Fetching:** The parent component is fetching `users` from an API. On the *initial render*, the data hasn't arrived yet, so the variable is `undefined`.
2. **Missing Prop:** The parent component forgot to pass the `users` prop (e.g., `<UserList />` instead of `<UserList users={myUsers} />`).
3. **Incorrect State Initialization:** The parent component initialized its state as `undefined` or `null` inste…
34.9s1851 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-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
Qwen3.7 Max
Here is a comprehensive review of your function, broken down by readability, performance, and best practices, followed by a refactored version.
### 1. Readability & Style (PEP 8)
* **Imports inside the function:** Imports should generally be placed at the top of the file, not inside the function. This makes dependencies clear and avoids slight overhead on every function call.
* **`item["active"] == True`:** In Python, explicitly comparing to `True` is discouraged (PEP 8). You should just use `if item.get("active"):`. Using `.get()` also prevents `KeyError` if the key is missing.
* **Manual List Building:** The `for` loop with `.append()` can be replaced with a much cleaner and faster **list…
58.3s3301 output tokens
Frequently asked questions
- Which is cheaper, GPT-5.4 Nano or Qwen3.7 Max?
- Per 1M output tokens, GPT-5.4 Nano is ¥223.38 and Qwen3.7 Max is ¥790.75 on FastMetal (yen, before tax), so GPT-5.4 Nano is cheaper.
- How do the context windows of GPT-5.4 Nano and Qwen3.7 Max compare?
- GPT-5.4 Nano takes 400,000 tokens; Qwen3.7 Max takes 1,000,000.
- Which ranks higher, GPT-5.4 Nano or Qwen3.7 Max?
- Qwen3.7 Max ranks higher on the public arena (GPT-5.4 Nano #107, Qwen3.7 Max #34). Ranks move as the leaderboard updates.
- Can I use GPT-5.4 Nano and Qwen3.7 Max with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.4-nano" or "qwen3.7-max" 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 Qwen3.7 Max from the browser chat and the API. No monthly fee.