GPT-5.6 Terra vs MiMo-V2.6-Pro
Pricing, context window and real answers (September 2026)
GPT-5.6 Terra (OpenAI) and MiMo-V2.6-Pro (Xiaomi), 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 | MiMo-V2.6-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Input (per 1M tokens) | ¥357.4 | ¥77.73 |
| Output (per 1M tokens) | ¥2,144.4 | ¥155.47 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,430 | ¥155 |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Release date | 7/9/2026 | 9/21/2026 |
| Input modalities | file, image, text | text, image, video, audio |
| Throughput (p50) | — | — |
| Arena · overall | #45 · ELO 1,466 | Unranked |
| Arena · Japanese | #20 · ELO 1,467 | Unranked |
| Arena · coding | #35 · ELO 1,518 | Unranked |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, MiMo-V2.6-Pro: ¥155.47 per 1M output tokens, 93% less than GPT-5.6 Terra.
- For long documents, GPT-5.6 Terra: a 1,050,000-token context window against 1,048,576 for MiMo-V2.6-Pro.
- 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
MiMo-V2.6-Pro
# Counting the 'r's in "strawberry"
## Step 1: Spell out the word letter by letter
| Position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|----------|---|---|---|---|---|---|---|---|---|----|
| Letter | s | t | r | a | w | b | e | r | r | y |
## Step 2: Identify every 'r'
- **Position 3** → **r** ✅ (1st 'r')
- **Position 8** → **r** ✅ (2nd 'r')
- **Position 9** → **r** ✅ (3rd 'r')
All other letters (s, t, a, w, b, e, y) are not 'r'.
## Answer
There are **3** 'r's in "strawberry."
22.0s327 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
MiMo-V2.6-Pro
# Fixing `Cannot read properties of undefined (reading 'map')`
## The Problem
The `users` prop is `undefined` when the component renders. This happens because `.map()` is being called on something that doesn't exist — JavaScript can't iterate over `undefined`.
This typically occurs when:
- The parent component doesn't pass the `users` prop at all
- The data is still loading (e.g., from an API call)
- A destructuring default doesn't exist
## The Fix
### Option 1: Provide a default value (simplest)
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
### Option 2: Add a safety check with conditi…
32.9s575 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
MiMo-V2.6-Pro
# Code Review: `get_data` Function
## Issues Identified
Here's my review organized by category, with a final improved version at the end.
---
### 🔴 Best Practices
1. **Imports inside the function** — `import requests` and `import time` are executed on *every* call. Move them to the top of the file (module-level).
2. **Bare `except:`** — This catches *everything*, including `KeyboardInterrupt` and `SystemExit`. Always catch specific exceptions.
3. **`== True` comparison** — Verbose and unnecessary. Use the object's truthiness directly.
4. **No logging** — Silent failures make debugging nearly impossible.
5. **Magic numbers** — `timeout=10` and `time.sleep(2)` are unexplained constan…
42.5s983 output tokens
Frequently asked questions
- Which is cheaper, GPT-5.6 Terra or MiMo-V2.6-Pro?
- Per 1M output tokens, GPT-5.6 Terra is ¥2,144.4 and MiMo-V2.6-Pro is ¥155.47 on FastMetal (yen, before tax), so MiMo-V2.6-Pro is cheaper.
- How do the context windows of GPT-5.6 Terra and MiMo-V2.6-Pro compare?
- GPT-5.6 Terra takes 1,050,000 tokens; MiMo-V2.6-Pro takes 1,048,576.
- Can I use GPT-5.6 Terra and MiMo-V2.6-Pro with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.6-terra" or "mimo-v2.6-pro" 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 MiMo-V2.6-Pro from the browser chat and the API. No monthly fee.