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.
Specifications
Modalities
Supported Parameters
Max Output Tokens
131,072Reasoning Configuration
- Default
- Thinking on
- Turning thinking off
- Not possible (always thinks)
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
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.
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…
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):…
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.