Beam 1.0 501B A23B vs Qwen3.7 Max
Pricing, context window and real answers (October 2026)
Beam 1.0 501B A23B (Reflection AI) 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
| Beam 1.0 501B A23B |  Qwen3.7 Max | |
|---|---|---|
| Provider | Reflection AI | Qwen |
| Input (per 1M tokens) | $0.422 | $2.64 |
| Output (per 1M tokens) | $1.27 | $7.92 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $1.06 | $6.60 |
| Context window | 1,048,576 tokens | 262,144 tokens |
| Release date | 10/16/2026 | 5/21/2026 |
| Input modalities | text | text |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #39 · ELO 1,474 |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | #28 · ELO 1,524 |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-15; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, Beam 1.0 501B A23B: $1.27 per 1M output tokens, 84% less than Qwen3.7 Max.
- For long documents, Beam 1.0 501B A23B: a 1,048,576-token context window against 262,144 for Qwen3.7 Max.
- 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.
Beam 1.0 501B A23B
The word “strawberry” is spelled:
s - t - r - a - w - b - e - r - r - y
The letter “r” appears in these positions:
- s**r**awberry (1st r)
- strawbe**r**ry (2nd r)
- strawber**r**y (3rd r)
Therefore, there are **3** r's in “strawberry.”
7.6s278 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…
Beam 1.0 501B A23B
The error means `users` is `undefined` when `UserList` renders, so calling `.map` on `undefined` throws.
### Common causes
1. Parent renders `<UserList />` without a `users` prop.
2. Parent passes `users={data}` where `data` is still `undefined` (e.g., fetch not resolved).
3. Destructured prop name mismatch.
### Fixes
**1. Default the prop**
```js
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
**2. Guard in JSX**
```js
{Array.isArray(users) && users.map(user => <li key={user.id}>{user.name}</li>)}
```
**3. Optional chaining**
```js
{users?.map(user => <li key={user.id}>{user.name}</li>)}
```
Note…
12.8s414 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):…
Beam 1.0 501B A23B
Here are some key issues and improvements:
### Main issues in the original
- **Imports inside the function** run on every call and hurt readability.
- **Bare `except:`** catches `KeyboardInterrupt`, `SystemExit`, and programming errors.
- **Retries every non-200 response**, including `404`/`400`, which usually should not be retried.
- **`item["active"] == True`** can raise `KeyError` and is stricter than necessary unless you truly need exact boolean equality.
- **Fixed sleep and unnecessary final sleep** before returning.
- **Repeated `item["name"]` / `item["id"]`** lookups are slightly slower and less clean than a comprehension.
- No handling/validation for malformed JSON or non-list respo…
16.8s1927 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, Beam 1.0 501B A23B or Qwen3.7 Max?
- Per 1M output tokens, Beam 1.0 501B A23B is $1.27 and Qwen3.7 Max is $7.92 on FastMetal (US dollars, before tax), so Beam 1.0 501B A23B is cheaper.
- How do the context windows of Beam 1.0 501B A23B and Qwen3.7 Max compare?
- Beam 1.0 501B A23B takes 1,048,576 tokens; Qwen3.7 Max takes 262,144.
- Can I use Beam 1.0 501B A23B and Qwen3.7 Max with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "beam-1.0" 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 Beam 1.0 501B A23B and Qwen3.7 Max from the browser chat and the API. No monthly fee.