FastMetal

Model comparison

GPT-6.1 Sol vs MiniMax M3.1 Flash

Pricing, context window and real answers (October 2026)

GPT-6.1 Sol (OpenAI) and MiniMax M3.1 Flash (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-6.1 Solminimax logoMiniMax M3.1 Flash
ProviderOpenAIMiniMax
Input (per 1M tokens)$2.11$0.1583
Output (per 1M tokens)$10.55$0.633
Typical cost (1,000 in + 500 out tokens × 1,000 calls)$7.39$0.4748
Context window1,050,000 tokens1,048,576 tokens
Release date9/29/202610/19/2026
Input modalitiesfile, image, texttext, image
Throughput (p50)89 tokens/s (n=17)—
Arena · overall#22 · ELO 1,484Unranked
Arena · JapaneseUnrankedUnranked
Arena · coding#10 · ELO 1,540Unranked

Prices are FastMetal's rates, before tax.

Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-15; category names mapped and ratings rounded by FastMetal.

Which should you pick?

  • On price, MiniMax M3.1 Flash: $0.633 per 1M output tokens, 94% 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 M3.1 Flash.
  • 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 M3.1 Flash

1. Spell **strawberry**: **s – t – r – a – w – b – e – r – r – y** 2. Count the letter **r**: it appears at positions **3, 8, and 9**. **Total: 3 “r”s.**
3.0s193 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 M3.1 Flash

The error occurs because `users` is `undefined` when `UserList` renders. Calling `.map()` on `undefined` causes the `TypeError`. This commonly happens when: - `<UserList />` is rendered without passing the `users` prop. - The prop has a different name, such as `user`. - Data is still loading and the parent initializes its state as `undefined`. - An API response is accessed before it exists. ### Immediate fix Provide a default empty array: ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => ( <li key={user.id}>{user.name}</li> ))} </ul> ); } ``` Then pass the actual data from the parent: ```jsx const [users, setUsers] = useState([…
7.3s744 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 M3.1 Flash

The function is understandable, but it has a few important issues: - `except:` catches programming errors such as `KeyError`, `TypeError`, and even `KeyboardInterrupt`. - Every non-200 response is retried, including permanent failures such as 400, 401, and 404. - It sleeps after the final failed attempt. - Returning `[]` makes a failed request indistinguishable from a successful response containing no active records. - A fixed delay can cause clients to retry simultaneously; exponential backoff and `Retry-After` are preferable. - `item["active"] == True` should be `item.get("active") is True` if the API contract says it is a JSON boolean. - A `Session` can reuse connections, while `requests…
146.5s

Compare on more prompts →

Frequently asked questions

Which is cheaper, GPT-6.1 Sol or MiniMax M3.1 Flash?
Per 1M output tokens, GPT-6.1 Sol is $10.55 and MiniMax M3.1 Flash is $0.633 on FastMetal (US dollars, before tax), so MiniMax M3.1 Flash is cheaper.
How do the context windows of GPT-6.1 Sol and MiniMax M3.1 Flash compare?
GPT-6.1 Sol takes 1,050,000 tokens; MiniMax M3.1 Flash takes 1,048,576.
Can I use GPT-6.1 Sol and MiniMax M3.1 Flash with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gpt-6.1-sol" or "minimax-m3.1-flash" 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 M3.1 Flash from the browser chat and the API. No monthly fee.

Create a free accountTry GPT-6.1 Sol in chatTry MiniMax M3.1 Flash in chat

More comparisons with GPT-6.1 Sol

More comparisons with MiniMax M3.1 Flash