GLM 5.3 vs MiniMax M3.1 Flash
Pricing, context window and real answers (October 2026)
GLM 5.3 (Z.ai) and MiniMax M3.1 Flash (MiniMax), 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 |  MiniMax M3.1 Flash | |
|---|---|---|
| Provider | Z.ai | MiniMax |
| Input (per 1M tokens) | $1.48 | $0.1583 |
| Output (per 1M tokens) | $4.65 | $0.633 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $3.80 | $0.4748 |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Release date | 8/18/2026 | 10/19/2026 |
| Input modalities | text | text, image |
| Throughput (p50) | 89 tokens/s (n=16) | — |
| Arena · overall | #28 · ELO 1,479 | Unranked |
| Arena · Japanese | #27 · ELO 1,464 | Unranked |
| Arena · coding | #27 · ELO 1,525 | Unranked |
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, MiniMax M3.1 Flash: $0.633 per 1M output tokens, 86% less than GLM 5.3.
- 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
# 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: Go through each letter and mark the 'r's.**
| Position | Letter | Is it 'r'? |
|----------|--------|------------|
| 1 | s | No |
| 2 | t | No |
| 3 | **r** | ✅ Yes (1st) |
| 4 | a | No |
| 5 | w | No |
| 6 | b | No |
| 7 | e | No |
| 8 | **r** | ✅ Yes (2nd) |
| 9 | **r** | ✅ Yes (3rd) |
| 10 | y | No |
**Step 3: Tally the results.**
- 1st 'r' in "st**r**awberry"
- 2nd 'r' in "strawbe**r**ry"
- 3rd 'r' in "strawber**r**y"
## Answer: There are **3** 'r's in "strawberry."
(Note: two of them appear together in the "rr" near the end, which is easy to miss when c…
5.8s493 output tokens
MiniMax M3.1 Flash
1. Spell **strawberry**:
**s – t – r – a – w – b – e – r – r – y**
2. Count the letter **r**: it appears at positions **3, 8, and 9**.
**Total: 3 “r”s.**
3.0s193 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
## What's happening
The error means `users` is `undefined` when the component renders. `undefined` doesn't have a `.map()` method, so JavaScript throws a `TypeError`. Since destructured props that aren't passed default to `undefined`, something upstream isn't providing the value you expect.
## Common causes
1. **The parent doesn't pass the prop, or uses a different name:**
```jsx
<UserList /> {/* missing users */}
<UserList userList={users} /> {/* prop name mismatch */}
```
2. **Async data hasn't loaded yet** — the component renders before an API call completes, and the initial value is `undefined`:
```jsx
const [users, setUsers] = useState(); // undefin…
17.1s1345 output tokens
MiniMax M3.1 Flash
The error occurs because `users` is `undefined` when `UserList` renders. Calling `.map()` on `undefined` causes the `TypeError`.
This commonly happens when:
- `<UserList />` is rendered without passing the `users` prop.
- The prop has a different name, such as `user`.
- Data is still loading and the parent initializes its state as `undefined`.
- An API response is accessed before it exists.
### Immediate fix
Provide a default empty array:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
Then pass the actual data from the parent:
```jsx
const [users, setUsers] = useState([…
7.3s744 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
Here's a breakdown of the issues, followed by a refactored version.
## Readability
- **Move imports to module level.** PEP 8 requires top-level imports; importing inside a function hides dependencies and adds overhead on every call (small, but pointless).
- **`item["active"] == True`** → just `item.get("active")`. Comparing to `True` with `==` is flagged by PEP 8, and `.get()` avoids a `KeyError` if the key is missing.
- **Use a list comprehension** instead of initializing a list and appending in a loop.
- **Rename things.** `get_data` doesn't say what it does (`fetch_active_items`?), and `response` beats `r`. Use `_` for the unused loop counter.
- **Magic numbers** (`2`, `10`) should be n…
75.0s6434 output tokens
MiniMax M3.1 Flash
The function is understandable, but it has a few important issues:
- `except:` catches programming errors such as `KeyError`, `TypeError`, and even `KeyboardInterrupt`.
- Every non-200 response is retried, including permanent failures such as 400, 401, and 404.
- It sleeps after the final failed attempt.
- Returning `[]` makes a failed request indistinguishable from a successful response containing no active records.
- A fixed delay can cause clients to retry simultaneously; exponential backoff and `Retry-After` are preferable.
- `item["active"] == True` should be `item.get("active") is True` if the API contract says it is a JSON boolean.
- A `Session` can reuse connections, while `requests…
146.5s
Frequently asked questions
- Which is cheaper, GLM 5.3 or MiniMax M3.1 Flash?
- Per 1M output tokens, GLM 5.3 is $4.65 and MiniMax M3.1 Flash is $0.633 on FastMetal (US dollars, before tax), so MiniMax M3.1 Flash is cheaper.
- How do the context windows of GLM 5.3 and MiniMax M3.1 Flash compare?
- GLM 5.3 takes 1,048,576 tokens; MiniMax M3.1 Flash takes 1,048,576.
- Can I use GLM 5.3 and MiniMax M3.1 Flash with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "glm-5.3" or "minimax-m3.1-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 GLM 5.3 and MiniMax M3.1 Flash from the browser chat and the API. No monthly fee.