Model comparison

GPT-6 Luna vs MiniMax M3

Pricing, context window and real answers (September 2026)

GPT-6 Luna (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

openai logoGPT-6 Lunaminimax logoMiniMax M3
ProviderOpenAIMiniMax
Input (per 1M tokens)¥17.87¥53.61
Output (per 1M tokens)¥89.35¥214.44
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥63¥161
Context window1,050,000 tokens1,048,576 tokens
Release date9/22/20265/31/2026
Input modalitiesfile, image, texttext, image, video
Throughput (p50)
Arena · overallUnranked#84 · ELO 1,441
Arena · JapaneseUnranked#77 · ELO 1,398
Arena · codingUnranked#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, GPT-6 Luna: ¥89.35 per 1M output tokens, 58% less than MiniMax M3.
  • For long documents, GPT-6 Luna: 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 Luna

In **“strawberry”**, the letter **r** appears at positions 3, 8, and 9. So there are **3** “r”s.
2.7s94 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 Luna

`users` is `undefined` when `UserList` renders, so calling `users.map(...)` throws. This often happens because the parent didn’t pass the prop or because data hasn’t loaded yet. If an empty list is acceptable until the data arrives, provide a default: ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => ( <li key={user.id}>{user.name}</li> ))} </ul> ); } ``` Also check that the parent passes `users`: ```jsx <UserList users={users} /> ``` If `users` is loaded asynchronously, initialize it as an array: ```jsx const [users, setUsers] = useState([]); ``` If `null` is also possible, normalize it before mapping, for example `(users ?? […
3.8s289 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 Luna

Key improvements: - Move imports to module scope. - Catch `requests.RequestException` instead of using a bare `except`; the current handler can hide programming errors as well as network failures. - Call `raise_for_status()` so unsuccessful HTTP responses are handled explicitly. - Use a list comprehension instead of building the result manually. - Replace `item["active"] == True` with `item.get("active") is True` if the field is expected to be the Boolean `True`. - Add backoff between attempts. A fixed two-second delay can make retries slower than necessary. - Decide whether failures should raise an exception or return `[]`. Returning `[]` makes a failed request indistinguishable from a suc…
16.5s1713 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

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Frequently asked questions

Which is cheaper, GPT-6 Luna or MiniMax M3?
Per 1M output tokens, GPT-6 Luna is ¥89.35 and MiniMax M3 is ¥214.44 on FastMetal (yen, before tax), so GPT-6 Luna is cheaper.
How do the context windows of GPT-6 Luna and MiniMax M3 compare?
GPT-6 Luna takes 1,050,000 tokens; MiniMax M3 takes 1,048,576.
Can I use GPT-6 Luna and MiniMax M3 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-6-luna" 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 Luna and MiniMax M3 from the browser chat and the API. No monthly fee.

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