GPT-6 Sol vs MiniMax M3
Pricing, context window and real answers (September 2026)
GPT-6 Sol (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-6 Sol |  MiniMax M3 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Input (per 1M tokens) | ¥357.4 | ¥53.61 |
| Output (per 1M tokens) | ¥1,787 | ¥214.44 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,251 | ¥161 |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Release date | 9/22/2026 | 5/31/2026 |
| Input modalities | file, image, text | text, image, video |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | #84 · ELO 1,441 |
| Arena · Japanese | Unranked | #77 · ELO 1,398 |
| Arena · coding | Unranked | #73 · 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, MiniMax M3: ¥214.44 per 1M output tokens, 88% less than GPT-6 Sol.
- For long documents, GPT-6 Sol: 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-6 Sol
“Strawberry” is spelled **s-t-r-a-w-b-e-r-r-y**. There’s one **r** near the beginning and two near the end, for a total of **3**.
2.7s76 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-6 Sol
`users` is `undefined` when `UserList` renders, so calling `users.map(...)` throws the error. The component needs an array, but its parent may not be passing `users`, or the data may not have loaded yet.
You can default it to an empty array:
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => <li key={user.id}>{user.name}</li>)}
</ul>
);
}
```
Also check the parent component to make sure it passes an array:
```jsx
<UserList users={users} />
```
If `users` comes from an API, initialize its state as `[]` or show a loading state until the data arrives.
2.2s161 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-6 Sol
The main issues are the bare `except`, which hides errors such as malformed JSON, and retrying every non-200 response, including client errors that usually won’t improve with another attempt. The function also sleeps after its final attempt.
```python
import time
import requests
def get_data(url, retries=3):
if retries < 1:
raise ValueError("retries must be at least 1")
for attempt in range(retries):
try:
response = requests.get(url, timeout=10)
except requests.RequestException:
if attempt == retries - 1:
raise
else:
# Retry rate limits and server errors, but not other client errors.…
10.3s814 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-6 Sol or MiniMax M3?
- Per 1M output tokens, GPT-6 Sol is ¥1,787 and MiniMax M3 is ¥214.44 on FastMetal (yen, before tax), so MiniMax M3 is cheaper.
- How do the context windows of GPT-6 Sol and MiniMax M3 compare?
- GPT-6 Sol takes 1,050,000 tokens; MiniMax M3 takes 1,048,576.
- Can I use GPT-6 Sol and MiniMax M3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-6-sol" 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-6 Sol and MiniMax M3 from the browser chat and the API. No monthly fee.