GPT-5.6 Terra vs MiniMax M3
Pricing, context window and real answers (August 2026)
GPT-5.6 Terra (OpenAI) and MiniMax M3 (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
 GPT-5.6 Terra |  MiniMax M3 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Input (per 1M tokens) | ¥357.4 | ¥53.61 |
| Output (per 1M tokens) | ¥2,144.4 | ¥214.44 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,430 | ¥161 |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Release date | 7/9/2026 | 5/31/2026 |
| Input modalities | file, image, text | text, image, video |
| Arena · overall | #34 · ELO 1,468 | #68 · ELO 1,444 |
| Arena · Japanese | Unranked | #49 · ELO 1,414 |
| Arena · coding | #22 · ELO 1,521 | #59 · ELO 1,498 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, MiniMax M3: ¥214.44 per 1M output tokens, 90% less than GPT-5.6 Terra.
- On the Overall arena board, GPT-5.6 Terra ranks higher (#34; MiniMax M3 is #68).
- On the Coding arena board, GPT-5.6 Terra ranks higher (#22; MiniMax M3 is #59).
- For long documents, GPT-5.6 Terra: a 1,050,000-token context window against 1,048,576 for MiniMax M3.
- 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.
GPT-5.6 Terra
“strawberry” is spelled:
s t **r** a w b e **r** **r** y
There are **3** occurrences of the letter **r**.
3.6s71 output tokens
MiniMax M3
# Counting 'r's in "strawberry"
Let me go through the word letter by letter:
**s** - t - **r** - a - w - b - e - **r** - **r** - y
| Position | Letter | Is it 'r'? |
|----------|--------|------------|
| 1 | s | No |
| 2 | t | No |
| 3 | **r** | ✓ (1st) |
| 4 | a | No |
| 5 | w | No |
| 6 | b | No |
| 7 | e | No |
| 8 | **r** | ✓ (2nd) |
| 9 | **r** | ✓ (3rd) |
| 10 | y | No |
## Answer: **3**
The word "strawberry" contains **three 'r's** — one at position 3, and two consecutive 'r's at positions 8 and 9.
25.6s455 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…
GPT-5.6 Terra
The error means `users` is `undefined` when `UserList` renders, so React tries to evaluate:
```js
users.map(...)
```
But `.map()` only exists on arrays.
Common causes:
- The parent component does not pass a `users` prop.
- The user data is loaded asynchronously and has not arrived on the first render.
- The API response shape differs from what you expect, e.g. data is in `response.data.users` rather than `response.data`.
- The parent initializes its user state as `undefined` or `null`.
## Fix options
### 1. Initialize users as an empty array
In the parent component:
```jsx
const [users, setUsers] = useState([]);
```
Then pass it normally:
```jsx
<UserList users={users} />
```
An e…
5.8s559 output tokens
MiniMax M3
# Error Analysis
The error `Cannot read properties of undefined (reading 'map')` tells you that **`users` is `undefined`** when your component runs. JavaScript can't call `.map()` on `undefined`, so it throws this error.
The component itself is fine syntactically — the problem is that the `users` prop isn't being passed, or hasn't loaded yet.
## Common Causes
**1. The prop isn't passed at all:**
```jsx
<UserList /> // No users prop → users is undefined
```
**2. Data is still loading (async fetch):**
```jsx
const [users, setUsers] = useState(); // undefined initially
```
**3. API returns undefined:**
```jsx
const { data } = await fetch('/api/users').then(r => r.json());
setUsers(data);…
32.8s710 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):…
GPT-5.6 Terra
Here are the main areas to improve:
### Issues in the original code
- **Imports inside the function**: Move `requests` and `time` imports to module scope.
- **Bare `except:`**: This catches everything, including `KeyboardInterrupt` and programming errors. Catch `requests.RequestException` (and possibly JSON decoding errors) instead.
- **Status code check**: Prefer `response.raise_for_status()` or `response.ok` over manually checking only for `200`. Successful responses can include other 2xx status codes.
- **`== True`**: Use `if item.get("active"):` instead.
- **Potential `KeyError`**: `item["name"]`, `item["id"]`, and `item["active"]` can fail if the API response is incomplete. Use `.get(…
10.6s939 output tokens
MiniMax M3
## Code Review
This function works for the happy path, but it has several issues around error handling, retries, and readability. Here's a breakdown.
### 🐛 Bugs & Correctness Issues
| # | Issue | Why It Matters |
|---|-------|----------------|
| 1 | `except:` with no exception type | Swallows `KeyboardInterrupt`, `SystemExit`, and *everything else* (typos, `MemoryError`). You lose visibility into real failures. |
| 2 | Retries on every non‑200, including `4xx` | A `404` or `401` will never succeed by retrying — it just wastes time and rate-limit budget. |
| 3 | `if item["active"] == True` | Both linters (PEP 8 E712) and Python idiom prefer `if item["active"]:`. |
| 4 | `item["active"]` (…
33.4s3977 output tokens
Frequently asked questions
- Which is cheaper, GPT-5.6 Terra or MiniMax M3?
- Per 1M output tokens, GPT-5.6 Terra is ¥2,144.4 and MiniMax M3 is ¥214.44 on FastMetal (yen, before tax), so MiniMax M3 is cheaper.
- How do the context windows of GPT-5.6 Terra and MiniMax M3 compare?
- GPT-5.6 Terra takes 1,050,000 tokens; MiniMax M3 takes 1,048,576.
- Which ranks higher, GPT-5.6 Terra or MiniMax M3?
- GPT-5.6 Terra ranks higher on the public arena (GPT-5.6 Terra #34, MiniMax M3 #49). Ranks move as the leaderboard updates.
- Can I use GPT-5.6 Terra and MiniMax M3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.6-terra" or "minimax-m3" 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 GPT-5.6 Terra and MiniMax M3 from the browser chat and the API. No monthly fee.