Beam 1.0 501B A23B vs Gemini 3.7 Flash
Pricing, context window and real answers (October 2026)
Beam 1.0 501B A23B (Reflection AI) and Gemini 3.7 Flash (Google), 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 |  Gemini 3.7 Flash | |
|---|---|---|
| Provider | Reflection AI | |
| Input (per 1M tokens) | $0.422 | $0.7913 |
| Output (per 1M tokens) | $1.27 | $3.96 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $1.06 | $2.77 |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Release date | 10/16/2026 | 8/13/2026 |
| Input modalities | text | text, image, video, file, audio |
| Throughput (p50) | — | 614 tokens/s (n=26) |
| Arena · overall | Unranked | #17 · ELO 1,488 |
| Arena · Japanese | Unranked | #3 · ELO 1,512 |
| Arena · coding | Unranked | #41 · ELO 1,518 |
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, 68% less than Gemini 3.7 Flash.
- 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
Gemini 3.7 Flash
There are **3** 'r's in the word "strawberry".
### Step-by-step reasoning:
1. **Break down the word into individual letters:**
* 1st letter: **s**
* 2nd letter: **t**
* 3rd letter: **r** *(1st 'r')*
* 4th letter: **a**
* 5th letter: **w**
* 6th letter: **b**
* 7th letter: **e**
* 8th letter: **r** *(2nd 'r')*
* 9th letter: **r** *(3rd 'r')*
* 10th letter: **y**
2. **Identify the positions of 'r':**
* The 3rd letter is an **r** (in "st**r**aw").
* The 8th letter is an **r** (in "be**r**ry").
* The 9th letter is an **r** (in "ber**r**y").
3. **Total count:** 1 + 1 + 1 = **3**.
4.5s530 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
Gemini 3.7 Flash
### Why This Error Happens
This error occurs because the `users` prop is `undefined` when the component renders. Since `map` is an Array method, calling `undefined.map()` causes JavaScript to throw a `TypeError`.
This usually happens when:
1. Data is being fetched asynchronously (e.g., via `fetch` or `axios`), and the component renders **before** the data has arrived.
2. The parent component forgot to pass the `users` prop (`<UserList />`).
3. The initial state in the parent component was initialized as `undefined` (e.g., `const [users, setUsers] = useState()`).
---
### How to Fix It
Here are the best ways to fix it, depending on your use case:
#### Solution 1: Default Parameter (Recom…
9.9s1355 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
Gemini 3.7 Flash
Here is a detailed review of your function, followed by refactored versions.
---
### Key Issues & Areas for Improvement
1. **Imports inside the function (PEP 8):**
Imports should be placed at the top of the file, not inside a function, to avoid repeated import overhead and improve readability.
2. **Bare `except:` clause (Anti-pattern):**
Catching everything with `except:` intercepts `KeyboardInterrupt`, `SystemExit`, and memory errors, making debugging difficult. Catch specific exceptions like `requests.RequestException` and `ValueError` (for JSON decoding).
3. **Retrying on non-retryable errors:**
A status code like `404 Not Found` or `401 Unauthorized` will never succeed on a…
13.2s2117 output tokens
Frequently asked questions
- Which is cheaper, Beam 1.0 501B A23B or Gemini 3.7 Flash?
- Per 1M output tokens, Beam 1.0 501B A23B is $1.27 and Gemini 3.7 Flash is $3.96 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 Gemini 3.7 Flash compare?
- Beam 1.0 501B A23B takes 1,048,576 tokens; Gemini 3.7 Flash takes 1,048,576.
- Can I use Beam 1.0 501B A23B and Gemini 3.7 Flash with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "beam-1.0" or "gemini-3.7-flash" 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 Gemini 3.7 Flash from the browser chat and the API. No monthly fee.