GPT-5.6 Terra vs Inkling
Pricing, context window and real answers (August 2026)
GPT-5.6 Terra (OpenAI) and Inkling (Thinkingmachines), 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 | Inkling | |
|---|---|---|
| Provider | OpenAI | Thinkingmachines |
| Input (per 1M tokens) | ¥357.4 | ¥178.7 |
| Output (per 1M tokens) | ¥2,144.4 | ¥723.74 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,430 | ¥541 |
| Context window | 1,050,000 tokens | 524,288 tokens |
| Release date | 7/9/2026 | 7/17/2026 |
| Input modalities | file, image, text | text, image, audio |
| Arena · overall | #34 · ELO 1,468 | #71 · ELO 1,443 |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | #22 · ELO 1,521 | #64 · ELO 1,496 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Inkling: ¥723.74 per 1M output tokens, 66% less than GPT-5.6 Terra.
- On the Overall arena board, GPT-5.6 Terra ranks higher (#34; Inkling is #71).
- On the Coding arena board, GPT-5.6 Terra ranks higher (#22; Inkling is #64).
- For long documents, GPT-5.6 Terra: a 1,050,000-token context window against 524,288 for Inkling.
- 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
Inkling
Let's break down the word **"strawberry"** letter by letter:
1. **s**
2. **t**
3. **r** ← (1st 'r')
4. **a**
5. **w**
6. **b**
7. **e**
8. **r** ← (2nd 'r')
9. **r** ← (3rd 'r')
10. **y**
So the spelling is: s-t-**r**-a-w-b-e-**r**-**r**-y
Counting them up:
- One 'r' in "str" (the 3rd letter)
- Two 'r's in "berry" (the 8th and 9th letters)
**Total: 3 'r's** in "strawberry".**
2.4s417 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
Inkling
The error occurs because `users` is `undefined` when `UserList` renders, so `users.map` fails.
This usually happens when:
- The parent doesn't pass the prop (`<UserList />` instead of `<UserList users={...} />`)
- Data is still loading (e.g., API hasn't returned yet)
## Quick Fix
Provide a default empty array so `.map` always has an array to work with:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
Alternatively, guard against undefined explicitly:
```jsx
function UserList({ users }) {
if (!users) return null; // or a loading state
return (
<ul>
{users.map(user => <li key={…
4.9s585 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
Inkling
Here is a review with an improved version followed by explanations.
### Issues in the original
- **Imports inside the function**: Re-importing on every call is inefficient.
- **Bare `except:`**: Catches `SystemExit`, `KeyboardInterrupt`, etc.
- **Silent failures**: No logging; errors disappear.
- **Magic numbers**: `10`, `2`, `200` are hard-coded.
- **Data validation missing**: Assumes `data` is a list and every item has `"active"`, `"name"`, and `"id"` (will crash with `KeyError`).
- **Performance**: Uses `.append()` in a loop instead of a list comprehension.
- **Ambiguous return**: `[]` means both "success with no results" and "total failure".
### Improved version
```python
import loggi…
54.1s5649 output tokens
Frequently asked questions
- Which is cheaper, GPT-5.6 Terra or Inkling?
- Per 1M output tokens, GPT-5.6 Terra is ¥2,144.4 and Inkling is ¥723.74 on FastMetal (yen, before tax), so Inkling is cheaper.
- How do the context windows of GPT-5.6 Terra and Inkling compare?
- GPT-5.6 Terra takes 1,050,000 tokens; Inkling takes 524,288.
- Which ranks higher, GPT-5.6 Terra or Inkling?
- GPT-5.6 Terra ranks higher on the public arena (GPT-5.6 Terra #34, Inkling #71). Ranks move as the leaderboard updates.
- Can I use GPT-5.6 Terra and Inkling with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.6-terra" or "inkling" 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 Inkling from the browser chat and the API. No monthly fee.