Model comparison

DeepSeek V4.1 Flash vs MiniMax M3.1 Flash

Pricing, context window and real answers (October 2026)

DeepSeek V4.1 Flash (DeepSeek) 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

deepseek logoDeepSeek V4.1 Flashminimax logoMiniMax M3.1 Flash
ProviderDeepSeekMiniMax
Input (per 1M tokens)$0.211$0.1583
Output (per 1M tokens)$0.633$0.633
Typical cost (1,000 in + 500 out tokens × 1,000 calls)$0.5275$0.4748
Context window1,048,576 tokens1,048,576 tokens
Release date9/10/202610/19/2026
Input modalitiestext, imagetext, image
Throughput (p50)168 tokens/s (n=23)—
Arena · overall#38 · ELO 1,475Unranked
Arena · Japanese#40 · ELO 1,445Unranked
Arena · coding#29 · ELO 1,523Unranked

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?

  • Output pricing is identical ($0.633 per 1M tokens).
  • 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.

DeepSeek V4.1 Flash

The word **“strawberry”** has **3** letter **“r”**s. Step-by-step: 1. Spell it out: **s t r a w b e r r y** 2. Find each **r**: - Position 3: **r** in “str” - Position 8: first **r** in “berry” - Position 9: second **r** in “berry” 3. Total: **3** **Answer: 3**
7.5s226 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…

DeepSeek V4.1 Flash

The error means that `users` is `undefined` when `UserList` renders, so JavaScript cannot call `.map()` on it. Your component expects a `users` prop: ```jsx function UserList({ users }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` But it is being rendered without `users`, or `users` has not loaded yet. Common causes: 1. Parent renders it without the prop: ```jsx <UserList /> ``` instead of: ```jsx <UserList users={users} /> ``` 2. The prop name is different: ```jsx <UserList userList={users} /> ``` 3. The data is fetched asynchronously and is initially `undefined`: ```jsx const [users, setUsers] = useState(); useEffect(…
16.0s945 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):…

DeepSeek V4.1 Flash

Here are the main improvements: - Move imports to module level. - Avoid bare `except`; catch specific exceptions. - Use a `requests.Session` for connection reuse. - Retry only transient network/HTTP failures, not all errors. - Use exponential backoff and don’t sleep after the final attempt. - Use a list comprehension for readability/performance. - Add type hints, logging, constants, and basic JSON validation. - Avoid `== True`; use `is True` or a truthy check depending on API contract. Example refactor: ```python from __future__ import annotations import logging import time from typing import Any import requests logger = logging.getLogger(__name__) TIMEOUT = (3.05, 10) # connect time…
31.5s5142 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

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Frequently asked questions

Which is cheaper, DeepSeek V4.1 Flash or MiniMax M3.1 Flash?
Both are $0.633 per 1M output tokens on FastMetal (US dollars, before tax).
How do the context windows of DeepSeek V4.1 Flash and MiniMax M3.1 Flash compare?
DeepSeek V4.1 Flash takes 1,048,576 tokens; MiniMax M3.1 Flash takes 1,048,576.
Can I use DeepSeek V4.1 Flash and MiniMax M3.1 Flash with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4.1-flash" 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 DeepSeek V4.1 Flash and MiniMax M3.1 Flash from the browser chat and the API. No monthly fee.

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