GLM 5.3 FlashX vs gpt-oss-20b
Pricing, context window and real answers (September 2026)
GLM 5.3 FlashX (Z.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
 GLM 5.3 FlashX |  gpt-oss-20b | |
|---|---|---|
| Provider | Z.ai | OpenAI |
| Input (per 1M tokens) | ¥66.12 | ¥5.36 |
| Output (per 1M tokens) | ¥223.38 | ¥25.02 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥178 | ¥18 |
| Context window | 1,048,576 tokens | 131,072 tokens |
| Release date | 9/18/2026 | 8/5/2025 |
| Input modalities | text, image, video | text |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #252 · ELO 1,317 |
| Arena · Japanese | Unranked | #179 · ELO 1,256 |
| Arena · coding | Unranked | #232 · ELO 1,369 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, gpt-oss-20b: ¥25.02 per 1M output tokens, 89% less than GLM 5.3 FlashX.
- For long documents, GLM 5.3 FlashX: 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.
GLM 5.3 FlashX
# Counting 'r's in "strawberry"
**Step 1: Write out each letter with its position**
| Position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|----------|---|---|---|---|---|---|---|---|---|----|
| Letter | s | t | r | a | w | b | e | r | r | y |
**Step 2: Check each letter one by one**
- Position 1: **s** → not an 'r'
- Position 2: **t** → not an 'r'
- Position 3: **r** → ✅ 'r' found (count: 1)
- Position 4: **a** → not an 'r'
- Position 5: **w** → not an 'r'
- Position 6: **b** → not an 'r'
- Position 7: **e** → not an 'r'
- Position 8: **r** → ✅ 'r' found (count: 2)
- Position 9: **r** → ✅ 'r' found (count: 3)
- Position 10: **y** → not an 'r'
**Step 3: Tally the results**
The 'r's a…
4.1s549 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…
GLM 5.3 FlashX
## What's Happening
The error means `users` is `undefined` at the time `UserList` renders. You're calling `.map()` on `undefined`, which JavaScript doesn't allow. This almost always happens for one of these reasons:
1. **The parent isn't passing the prop** — `<UserList />` with no `users` prop
2. **Data hasn't loaded yet** — you're fetching asynchronously, so the first render happens before the data arrives
3. **Prop name mismatch** — e.g., passing `user` but reading `users`
4. **Parent state initialized to `undefined`** — e.g., `useState()` instead of `useState([])`
## Fixes
### Option 1: Default parameter (simplest)
```jsx
function UserList({ users = [] }) {
return (
<ul>…
6.8s934 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):…
GLM 5.3 FlashX
# Code Review
The function works, but there are several issues worth addressing — including one subtle bug caused by the bare `except`.
## Correctness issues (most important)
1. **Bare `except:` is dangerous and masks a bug.** It catches *everything*, including `KeyboardInterrupt` and `SystemExit` (so Ctrl+C during a retry sleep is swallowed). Worse: because your data-processing loop sits inside the `try`, a `KeyError` from a malformed item is treated as a network failure — triggering a pointless re-download of the URL and silently discarding the real error. Catch only `requests.RequestException` (and `ValueError` for JSON decode failures).
2. **Silent failure.** Returning `[]` on error…
36.9s5836 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, GLM 5.3 FlashX or gpt-oss-20b?
- Per 1M output tokens, GLM 5.3 FlashX is ¥223.38 and gpt-oss-20b is ¥25.02 on FastMetal (yen, before tax), so gpt-oss-20b is cheaper.
- How do the context windows of GLM 5.3 FlashX and gpt-oss-20b compare?
- GLM 5.3 FlashX takes 1,048,576 tokens; gpt-oss-20b takes 131,072.
- Can I use GLM 5.3 FlashX and gpt-oss-20b with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.3-flashx" 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 GLM 5.3 FlashX and gpt-oss-20b from the browser chat and the API. No monthly fee.