Claude Sonnet 5 vs GLM 5.3 Flash
Pricing, context window and real answers (August 2026)
Claude Sonnet 5 (Anthropic) and GLM 5.3 Flash (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 Sonnet 5 |  GLM 5.3 Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai |
| Input (per 1M tokens) | ¥357.4 | ¥13.19 |
| Output (per 1M tokens) | ¥1,787 | ¥43.98 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,251 | ¥35 |
| Context window | 1,000,000 tokens | 1,310,720 tokens |
| Release date | 6/30/2026 | 8/26/2026 |
| Input modalities | text, image, file | text, image, video |
| Arena · overall | #47 · ELO 1,461 | #38 · ELO 1,469 |
| Arena · Japanese | #33 · ELO 1,447 | Unranked |
| Arena · coding | #22 · ELO 1,522 | #11 · ELO 1,531 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, GLM 5.3 Flash: ¥43.98 per 1M output tokens, 98% less than Claude Sonnet 5.
- On the Overall arena board, GLM 5.3 Flash ranks higher (#38; Claude Sonnet 5 is #47).
- On the Coding arena board, GLM 5.3 Flash ranks higher (#11; Claude Sonnet 5 is #22).
- For long documents, GLM 5.3 Flash: a 1,310,720-token context window against 1,000,000 for Claude Sonnet 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 Sonnet 5
# Counting 'r's in "strawberry"
**Step 1: Spell out the word letter by letter**
s - t - r - a - w - b - e - r - r - y
**Step 2: Number each letter position**
| Position | Letter |
|----------|--------|
| 1 | s |
| 2 | t |
| 3 | **r** |
| 4 | a |
| 5 | w |
| 6 | b |
| 7 | e |
| 8 | **r** |
| 9 | **r** |
| 10 | y |
**Step 3: Identify and count the 'r's**
- Position 3: **r** ✓ (1st r)
- Position 8: **r** ✓ (2nd r)
- Position 9: **r** ✓ (3rd r)
**Answer: There are 3 r's in "strawberry"**
5.9s405 output tokens
GLM 5.3 Flash
# Counting 'r's in 'strawberry'
**Step 1: Write out the word letter by letter**
s - t - r - a - w - b - e - r - r - y
**Step 2: Check each letter one at a time**
| Position | Letter | Is it 'r'? |
|----------|--------|-----------|
| 1 | s | No |
| 2 | t | No |
| 3 | r | **Yes! (1)** |
| 4 | a | No |
| 5 | w | No |
| 6 | b | No |
| 7 | e | No |
| 8 | r | **Yes! (2)** |
| 9 | r | **Yes! (3)** |
| 10 | y | No |
**Step 3: Add up the matches**
The 'r's appear at positions 3, 8, and 9.
## Answer: There are **3** 'r's in "strawberry" 🍓
7.2s449 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 Sonnet 5
# Root Cause
The `UserList` component receives `users` as a prop, but at the time it's rendered, `users` is `undefined` — not an empty array, but literally missing. When your code tries to call `.map()` on `undefined`, JavaScript throws that `TypeError`.
This typically happens when:
- The parent component hasn't fetched the data yet (e.g., an API call is still in progress)
- The prop name doesn't match what's being passed down (typo)
- The data source (API/state) genuinely returns `undefined` in some case
# Fixes
**1. Add a default prop value (quick fix)**
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</u…
8.8s750 output tokens
GLM 5.3 Flash
## What's happening
The error means the `users` prop is `undefined` at the time `UserList` renders. Since you can't call `.map()` on `undefined`, JavaScript throws the TypeError.
This usually happens for one of these reasons:
1. **The parent isn't passing the prop** — rendering `<UserList />` without `users`, or with a typo'd prop name like `user={users}`.
2. **Data hasn't loaded yet** — the parent fetches data asynchronously and its state starts as `undefined`:
```jsx
const [users, setUsers] = useState(); // undefined until fetch resolves!
return <UserList users={users} />;
```
3. **API response shape mismatch** — the array is nested, e.g., you need `response.data.users` inst…
31.3s1639 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 Sonnet 5
## Review of `get_data` Function
Here's an improved version followed by an explanation of the changes:
```python
import logging
import time
from typing import Any
import requests
logger = logging.getLogger(__name__)
def get_data(
url: str,
retries: int = 3,
timeout: float = 10.0,
backoff_factor: float = 2.0,
) -> list[dict[str, Any]]:
"""
Fetch active items from the given URL.
Args:
url: The endpoint to fetch data from.
retries: Number of attempts before giving up.
timeout: Request timeout in seconds.
backoff_factor: Multiplier for exponential backoff between retries.
Returns:
A list of dicts with "name" and "id"…
14.0s1299 output tokens
GLM 5.3 Flash
Solid foundation — you're already passing an explicit `timeout` and implementing retries, which many people skip. Here's a breakdown by category:
## Correctness & robustness (most important)
- **Bare `except:`** catches *everything*, including `KeyboardInterrupt` and `SystemExit`, and silently discards the error. Catch specific exceptions: `requests.RequestException` for network issues, `ValueError` for invalid JSON.
- **Retrying non-retryable failures**: a 401/403/404 will never succeed on retry, so you're sleeping 6 seconds for nothing. Only retry transient errors (5xx, 429, timeouts/connection errors).
- **`item["active"]` raises `KeyError`** on malformed data. Use `item.get("active")`…
116.1s6185 output tokens
Frequently asked questions
- Which is cheaper, Claude Sonnet 5 or GLM 5.3 Flash?
- Per 1M output tokens, Claude Sonnet 5 is ¥1,787 and GLM 5.3 Flash is ¥43.98 on FastMetal (yen, before tax), so GLM 5.3 Flash is cheaper.
- How do the context windows of Claude Sonnet 5 and GLM 5.3 Flash compare?
- Claude Sonnet 5 takes 1,000,000 tokens; GLM 5.3 Flash takes 1,310,720.
- Which ranks higher, Claude Sonnet 5 or GLM 5.3 Flash?
- Claude Sonnet 5 ranks higher on the public arena (Claude Sonnet 5 #33, GLM 5.3 Flash #38). Ranks move as the leaderboard updates.
- Can I use Claude Sonnet 5 and GLM 5.3 Flash with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "anthropic-claude-sonnet-5" or "glm-5.3-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 Claude Sonnet 5 and GLM 5.3 Flash from the browser chat and the API. No monthly fee.