Beam 1.0 501B A23B vs gpt-oss-20b
Pricing, context window and real answers (October 2026)
Beam 1.0 501B A23B (Reflection AI) and gpt-oss-20b (OpenAI), 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 |  gpt-oss-20b | |
|---|---|---|
| Provider | Reflection AI | OpenAI |
| Input (per 1M tokens) | $0.422 | $0.0317 |
| Output (per 1M tokens) | $1.27 | $0.1477 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $1.06 | $0.1055 |
| Context window | 1,048,576 tokens | 131,072 tokens |
| Release date | 10/16/2026 | 8/5/2025 |
| Input modalities | text | text |
| Throughput (p50) | — | 115 tokens/s (n=20) |
| Arena · overall | Unranked | #267 · ELO 1,317 |
| Arena · Japanese | Unranked | #192 · ELO 1,255 |
| Arena · coding | Unranked | #249 · ELO 1,368 |
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, gpt-oss-20b: $0.1477 per 1M output tokens, 88% less than Beam 1.0 501B A23B.
- For long documents, Beam 1.0 501B A23B: a 1,048,576-token context window against 131,072 for gpt-oss-20b.
- 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
gpt-oss-20b
**Count of ‘r’ in “strawberry”: 3**
---
### Step‑by‑step reasoning
1. **Write out the word in individual letters**
```
s t r a w b e r r y
```
2. **Identify each ‘r’**
- The first ‘r’: appears after the “t” → **r**
- The second ‘r’: appears in the part “berry” → **r**
- The third ‘r’: the next letter after that → **r**
3. **Verify there are no more letters left**
The remaining letters are “b”, “e”, “y”, none of which are “r”.
4. **Count the identified ‘r’s**
1 (first) + 1 (second) + 1 (third) = **3**
---
### Quick recap
- Word: **strawberry**
- Letters containing “r”: positions 3, 8, and 9.
- Total count: **3**.
11.6s371 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
gpt-oss-20b
### Why does the error happen?
`users.map(...)` can only run when **`users` is an array**.
The stack trace shows that the crash happens on line 12 of `UserList.js`, which is the
exact spot where the code tries to call `.map`.
The value that is being passed to `UserList` (or the initial value that the parent
creates) is **`undefined`** (or it could be `null`/`{}`). When JavaScript tries to
read `users.map`, it throws:
```
TypeError: Cannot read properties of undefined (reading 'map')
```
Typical reasons for this are:
1. The parent component **didn’t pass the `users` prop** at all.
2. The parent passed it but the value was **`undefined` / `null`** because data
hasn’t been loaded ye…
11.4s1303 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
gpt-oss-20b
Below is a quick “code‑review” style list that touches the three axes you asked for – **readability**, **performance**, and **best practices**.
After the bullet‑list I’ll paste a refactored version that incorporates the most common fixes.
---
## 1. Readability
| Issue | Why it hurts | Quick fix |
|-------|--------------|-----------|
| **Imports inside the function** | Every call recompiles the import tables and makes the module’s top‑level slower. | Move `import requests` and `import time` to the module’s global header. |
| **Bare `except:`** | Catches *everything* (KeyboardInterrupt, SystemExit, MemoryError, etc.) and swallows useful tracebacks. | Catch only the expected network-relate…
24.6s2267 output tokens
Frequently asked questions
- Which is cheaper, Beam 1.0 501B A23B or gpt-oss-20b?
- Per 1M output tokens, Beam 1.0 501B A23B is $1.27 and gpt-oss-20b is $0.1477 on FastMetal (US dollars, before tax), so gpt-oss-20b is cheaper.
- How do the context windows of Beam 1.0 501B A23B and gpt-oss-20b compare?
- Beam 1.0 501B A23B takes 1,048,576 tokens; gpt-oss-20b takes 131,072.
- Can I use Beam 1.0 501B A23B and gpt-oss-20b with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "beam-1.0" or "gpt-oss-20b" 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 gpt-oss-20b from the browser chat and the API. No monthly fee.