GPT-5.6 Terra vs Solar Pro 4
Pricing, context window and real answers (October 2026)
GPT-5.6 Terra (OpenAI) and Solar Pro 4 (Upstage), 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 | Solar Pro 4 | |
|---|---|---|
| Provider | OpenAI | Upstage |
| Input (per 1M tokens) | $2.11 | $0.099 |
| Output (per 1M tokens) | $12.66 | $0.396 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $8.44 | $0.297 |
| Context window | 1,050,000 tokens | 524,288 tokens |
| Release date | 7/9/2026 | 8/10/2026 |
| Input modalities | file, image, text | text |
| Throughput (p50) | 192 tokens/s (n=26) | 90 tokens/s (n=26) |
| Arena · overall | #50 · ELO 1,466 | #182 · ELO 1,386 |
| Arena · Japanese | #23 · ELO 1,475 | #158 · ELO 1,312 |
| Arena · coding | #43 · ELO 1,516 | #136 · ELO 1,461 |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-08; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, Solar Pro 4: $0.396 per 1M output tokens, 97% less than GPT-5.6 Terra.
- On the Overall arena board, GPT-5.6 Terra ranks higher (#50; Solar Pro 4 is #182).
- On the Japanese arena board, GPT-5.6 Terra ranks higher (#23; Solar Pro 4 is #158).
- On the Coding arena board, GPT-5.6 Terra ranks higher (#43; Solar Pro 4 is #136).
- For long documents, GPT-5.6 Terra: a 1,050,000-token context window against 524,288 for Solar Pro 4.
- 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
Solar Pro 4
The word "strawberry" contains **3** 'r's. Here's the step-by-step breakdown:
1. **Spell out the word explicitly** to isolate each letter:
`s - t - r - a - w - b - e - r - r - y`
2. **Scan through the letters in order** and count every instance of the lowercase letter `r`:
- `s` → 0
- `t` → 0
- `r` → **1**
- `a` → 0
- `w` → 0
- `b` → 0
- `e` → 0
- `r` → **2**
- `r` → **3**
- `y` → 0
3. **Total the count**: The three `r`s appear at positions 3, 8, and 9 in the 10-letter word.
**Final count: 3**
11.4s215 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
Solar Pro 4
### What's Causing the Error
The error `TypeError: Cannot read properties of undefined (reading 'map')` means that the `users` prop being passed to your `UserList` component is `undefined`. Since you're calling `.map()` directly on it, JavaScript throws an error because `undefined` doesn't have a `map` method.
This typically happens when:
- The parent component hasn't passed the `users` prop
- The prop is still loading (e.g., from an API call)
- The prop is conditionally undefined
---
### How to Fix It
You have a few options to handle this safely:
#### ✅ Option 1: Add a Default Prop Value (Recommended)
Provide a fallback empty array so `.map()` always has something to work with:
```j…
24.7s539 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
Solar Pro 4
Here’s a breakdown of the issues in the original function, followed by a refactored version and a detailed explanation of the improvements.
### 🔍 Key Issues in the Original Code
| Area | Problem |
|------|---------|
| **Import organization** | `import` inside the function is evaluated on every call. Imports should live at the top of the module. |
| **Exception handling** | Bare `except:` catches `SystemExit`, `KeyboardInterrupt`, and other fatal errors. Always catch specific exceptions (`requests.RequestException`). |
| **Loose equality** | `== True` is redundant and can cause subtle bugs. Use `if item["active"]:` or `.get()`. |
| **HTTP status handling** | Calling `.json()` only on `200`…
17.5s1172 output tokens
Frequently asked questions
- Which is cheaper, GPT-5.6 Terra or Solar Pro 4?
- Per 1M output tokens, GPT-5.6 Terra is $12.66 and Solar Pro 4 is $0.396 on FastMetal (US dollars, before tax), so Solar Pro 4 is cheaper.
- How do the context windows of GPT-5.6 Terra and Solar Pro 4 compare?
- GPT-5.6 Terra takes 1,050,000 tokens; Solar Pro 4 takes 524,288.
- Which ranks higher, GPT-5.6 Terra or Solar Pro 4?
- GPT-5.6 Terra ranks higher on the public arena (GPT-5.6 Terra #23, Solar Pro 4 #158). Ranks move as the leaderboard updates.
- Can I use GPT-5.6 Terra and Solar Pro 4 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-5.6-terra" or "solar-pro4" 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 Solar Pro 4 from the browser chat and the API. No monthly fee.