Claude Haiku 5.5 vs GLM 5.3 FlashX
Pricing, context window and real answers (October 2026)
Claude Haiku 5.5 (Anthropic) and GLM 5.3 FlashX (Z.ai), 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
 Claude Haiku 5.5 |  GLM 5.3 FlashX | |
|---|---|---|
| Provider | Anthropic | Z.ai |
| Input (per 1M tokens) | $0.1055 | $0.407 |
| Output (per 1M tokens) | $0.5275 | $1.38 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $0.3693 | $1.10 |
| Context window | 1,000,000 tokens | 1,048,576 tokens |
| Release date | 10/7/2026 | 9/18/2026 |
| Input modalities | text, image, file | text, image, video |
| Throughput (p50) | — | 325 tokens/s (n=14) |
| Arena · overall | Unranked | Unranked |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | Unranked |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-02; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, Claude Haiku 5.5: $0.5275 per 1M output tokens, 62% less than GLM 5.3 FlashX.
- For long documents, GLM 5.3 FlashX: a 1,048,576-token context window against 1,000,000 for Claude Haiku 5.5.
- 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.
Claude Haiku 5.5
There are **3** r's in "strawberry."
1. **Spell out the word:** s, t, r, a, w, b, e, r, r, y
2. **Go through each letter and count the r's:**
- Position 3: **r** (count = 1)
- Position 8: **r** (count = 2)
- Position 9: **r** (count = 3)
3. **Check the rest:** s, t, a, w, b, e, and y are not r's.
Total: **3**
2.4s200 output tokens
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
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…
Claude Haiku 5.5
The error means `users` is `undefined` when `UserList` renders, so `.map` is called on nothing. The component destructures the `users` prop, but the parent didn't pass it, or passed `undefined`.
## Common causes
**1. The parent doesn't pass the prop, or uses a different name**
```jsx
<UserList /> // users is undefined
<UserList user={users} /> // wrong name: "user" instead of "users"
```
**2. The data hasn't loaded yet (most common with fetched data)**
```jsx
function App() {
const [users, setUsers] = useState(); // undefined initially
useEffect(() => {
fetch('/api/users').then(r => r.json()).then(setUsers);
}, []);
return <UserList users={users} />;…
5.1s888 output tokens
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
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):…
Claude Haiku 5.5
## Issues
**Correctness and robustness**
1. **Bare `except:`** catches everything, including `KeyboardInterrupt` and `SystemExit`, so Ctrl+C may not stop the program. Catch specific exceptions: `requests.RequestException` for network problems and `ValueError` for invalid JSON.
2. **Retries non-retryable errors.** A 404 or 401 won't succeed on retry, so retrying wastes time. Only retry transient failures such as 429, 5xx, timeouts, and connection errors.
3. **Sleeps after the final attempt.** The loop sleeps even when no retry follows.
4. **Fixed sleep with no backoff.** Exponential backoff is the standard approach for retries.
5. **Silent failure.** Every failure returns `[]` with no loggin…
18.1s4096 output tokens
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
Frequently asked questions
- Which is cheaper, Claude Haiku 5.5 or GLM 5.3 FlashX?
- Per 1M output tokens, Claude Haiku 5.5 is $0.5275 and GLM 5.3 FlashX is $1.38 on FastMetal (US dollars, before tax), so Claude Haiku 5.5 is cheaper.
- How do the context windows of Claude Haiku 5.5 and GLM 5.3 FlashX compare?
- Claude Haiku 5.5 takes 1,000,000 tokens; GLM 5.3 FlashX takes 1,048,576.
- Can I use Claude Haiku 5.5 and GLM 5.3 FlashX with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-haiku-5-5" or "glm-5.3-flashx" 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 Claude Haiku 5.5 and GLM 5.3 FlashX from the browser chat and the API. No monthly fee.