How much does the MiniMax M2.7 API cost?

On FastMetal, MiniMax M2.7 is billed per token in yen: ¥53.61 per 1M input tokens and ¥214.44 per 1M output tokens, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.

Can I call MiniMax M2.7 with the OpenAI SDK?

Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "minimax-m2.7" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.

What is the context window of MiniMax M2.7?

204,800 tokens, shared between the prompt and the response.

What do I need to try MiniMax M2.7?

Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.

Back to Models

minimax/minimax-m2-7

MiniMax M2.7

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments. Trained for production-grade performance, M2.7 handles workflows such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. It delivers strong results on benchmarks including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while achieving a 1495 ELO on GDPval-AA, setting a new standard for multi-agent systems operating in real-world digital workflows.

3/18/2026

204,800 tokens

Input: ¥53.61/M

Output: ¥214.44/M

Try in Chat Get API Key

Specifications

Modalities

Input

text

Output

text

Supported Parameters

include_reasoning

max_tokens

reasoning

response_format

temperature

tool_choice

tools

top_p

Max Output Tokens

131,072

Reasoning Configuration

Default: Thinking on
Turning thinking off: Not possible (always thinks)

How to control thinking, and what it costs

Code Examples

curl https://api.fastmetal.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "minimax-m2.7",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

How MiniMax M2.7 actually answers

Real responses to our standard prompts, recorded on FastMetal.

Count the number of 'r's in 'strawberry'

Count the number of 'r's in 'strawberry'. Explain your reasoning step by step.

**Step‑by‑step counting** 1. Write the word **strawberry** as a sequence of its letters: `s‑t‑r‑a‑w‑b‑e‑r‑r‑y` 2. Go through each letter and check whether it is the letter **r** (case‑insensitive). | Position | Letter | Is it “r”? | |----------|--------|------------| | 1 | s | No | | 2 | t | No | | 3 | **r** | Yes → count = 1 | | 4 | a | No | | 5 | w | No | | 6 | b | No | | 7 | e | No | | 8 | **r** | Yes → count = 2 | | 9 | **r** | Yes → count = 3 | | 10 | y | No | 3. After checking all ten positions, the total number of times the letter **…

11.1s response475 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…

# Fixing the "Cannot read properties of undefined" Error ## The Problem The error occurs because `users` is `undefined` when the component renders. The `.map()` method can't be called on `undefined`. This typically happens when: - The parent component doesn't pass the `users` prop - The data is still loading/fetching - The initial state is `undefined` instead of an empty array --- ## Solutions ### 1. Add a Default Parameter (Recommended) ```javascript function UserList({ users = [] }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` ### 2. Use Optional Chaining ```javascript function UserList({ users }) { return ( <ul>…

14.2s response695 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):…

# Code Review: `get_data` Function ## Issues Identified ### 1. **Critical Issues** ```python # ❌ Bare except clause - catches everything including KeyboardInterrupt except: time.sleep(2) ``` ```python # ❌ Comparing to True - redundant comparison if item["active"] == True: ``` ```python # ❌ No JSON error handling - r.json() can raise ValueError data = r.json() ``` ### 2. **Code Quality Issues** | Issue | Location | Problem | |-------|----------|---------| | Imports inside function | Line 2-3 | Should be at module level | | Magic numbers | `timeout=10`, `sleep(2)` | Not descriptive | | No docstring | Function | No documentation | | No type hints | Function signature | Missing type safet…

31.7s response1690 output tokens

Compare these answers side by side with other models →

Frequently asked questions

How much does the MiniMax M2.7 API cost?: On FastMetal, MiniMax M2.7 is billed per token in yen: ¥53.61 per 1M input tokens and ¥214.44 per 1M output tokens, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.
Can I call MiniMax M2.7 with the OpenAI SDK?: Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "minimax-m2.7" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.
What is the context window of MiniMax M2.7?: 204,800 tokens, shared between the prompt and the response.
What do I need to try MiniMax M2.7?: Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.