GPT-6.1 Sol vs MiniMax M3
Pricing, context window and real answers (September 2026)
GPT-6.1 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-6.1 Sol |  MiniMax M3 | |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Input (per 1M tokens) | ¥357.4 | ¥47.04 |
| Output (per 1M tokens) | ¥1,787 | ¥184.8 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,251 | ¥139 |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Release date | 9/29/2026 | 5/31/2026 |
| Input modalities | file, image, text | text, image, video |
| Throughput (p50) | — | 290 tokens/s (n=16) |
| Arena · overall | Unranked | #91 · ELO 1,440 |
| Arena · Japanese | Unranked | #83 · ELO 1,395 |
| Arena · coding | Unranked | #81 · ELO 1,495 |
Prices are FastMetal's yen rates before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-09-25; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, MiniMax M3: ¥184.8 per 1M output tokens, 90% less than GPT-6.1 Sol.
- For long documents, GPT-6.1 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-6.1 Sol
“strawberry” is spelled **s-t-r-a-w-b-e-r-r-y**.
The letter **r** appears at positions **3, 8, and 9**.
So, there are **3 r’s** in “strawberry.”
2.8s88 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-6.1 Sol
The error means **`users` is `undefined` when `UserList` renders**. Calling `.map()` on `undefined` throws this error.
This commonly happens when the parent doesn’t pass the `users` prop, or when data hasn’t finished loading yet.
### Fix: provide a default empty array
```jsx
function UserList({ users = [] }) {
return (
<ul>
{users.map(user => (
<li key={user.id}>{user.name}</li>
))}
</ul>
);
}
```
This renders an empty list if `users` is omitted or `undefined`. It does **not** handle `null`.
### Check the parent component too
Make sure it passes an array:
```jsx
<UserList users={users} />
```
If you’re fetching users asynchronously, initialize the stat…
5.8s306 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-6.1 Sol
The function is short, but its main weakness is that it hides failures: a network error, invalid JSON, and a genuinely empty result all return `[]`.
### Suggested improvements
- **Move imports to module scope.** This is conventional and makes dependencies visible. Repeated imports are cached, so the performance benefit is minor.
- **Avoid bare `except:`.** It catches everything, including `KeyboardInterrupt` and `SystemExit`, and can hide programming errors.
- **Handle HTTP errors explicitly.** `raise_for_status()` provides useful exceptions. Retry transient failures such as timeouts, connection errors, HTTP 429, and HTTP 5xx—not permanent errors such as HTTP 404.
- **Don’t sleep after the…
19.0s1094 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-6.1 Sol or MiniMax M3?
- Per 1M output tokens, GPT-6.1 Sol is ¥1,787 and MiniMax M3 is ¥184.8 on FastMetal (yen, before tax), so MiniMax M3 is cheaper.
- How do the context windows of GPT-6.1 Sol and MiniMax M3 compare?
- GPT-6.1 Sol takes 1,050,000 tokens; MiniMax M3 takes 1,048,576.
- Can I use GPT-6.1 Sol and MiniMax M3 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-6.1-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-6.1 Sol and MiniMax M3 from the browser chat and the API. No monthly fee.