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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: $0.3165/M
Output: $1.27/M

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

Data policy

Prompt retention
Unknown — we could not confirm
Training
Unknown — not declared

"Unknown" does not mean "safe". It means we could not confirm it.

Whether a provider trains on prompts is a declared value from our terms with them. Retention is determined from the upstream listing for every host this model can reach. Neither is guessed.

Measured performance

Time to first response (p50)1.3s

    Measured through FastMetal's own gateway over the last 30 days (660 first-response samples).

    Time to first response is measured to the first streamed chunk; throughput counts all output tokens, including reasoning tokens. These are observations, not a performance guarantee.

    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: $0.3165 per 1M input tokens and $1.27 per 1M output tokens on a US-dollar account, 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.

    Try MiniMax M2.7 right now

    MiniMax M2.7 is available on FastMetal through one API key. Start in the browser, or call it from the OpenAI SDK.