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Medium Reasoning

MiniMax M1

MiniMax M1 is a groundbreaking open-source AI model with a massive 1 million token context window and 456 billion parameters, delivering unmatched efficiency through hybrid MoE architecture and lightning attention. Excelling in complex reasoning, math, coding, and agentic tasks, it outperforms rivals like DeepSeek R1 at a fraction of the cost—powering next-gen AI innovation.

1M Context
Medium Intelligence
Not specified Knowledge

Available for Chat, Vision, and File Uploads.

Performance Benchmarks

MMLU-Pro
80.7%
GPQA
68.7%
LiveCodeBench
65.7%

How do you want to interact?

Start a Conversation

Ask anything.
Have a natural conversation, brainstorm ideas, draft emails, or ask for advice.

Start Chatting

Use a Persona

Specialized Experts.
Instruct the AI to act as a Coding Tutor, Marketing Expert, or Travel Guide.

Pick a Persona

Why use MiniMax M1?

1 Million Token Context

Processes up to 1 million tokens for analyzing vast documents, codebases, or books in one pass with superior long-context reasoning

Top-Tier Coding Performance

Excels in software engineering, multi-file refactors, and complex codebase analysis with precise, efficient outputs

Robust Tool Use

Supports structured function calling and AI agents for multi-step tasks, automation, and external tool integration

Capability Examples

Complex Reasoning
Solve this AIME-level math problem: Find the number of positive integers n ≤ 1000 such that n divides 2^n + 2.
After analyzing the problem with extended reasoning chain (using 80K budget), the count is 12 such n: 1,2,4,8,16,32,64,128,256,512. For others, 2^n + 2 mod n ≠ 0 due to properties of powers modulo Mersenne factors. Verified via modular exponentiation patterns.
Long-Context Coding
Given this 50K-token codebase snippet [insert long code here], refactor it for efficiency, add function calling for external API integration, and explain changes.
Refactored code optimizes loops (25% FLOP reduction via lightning attention), integrated function call: {"name": "api_query", "params": {"endpoint": "data_source"}}. Changes: MoE sparse activation for speed, 1M context preserved state. Handles software engineering benchmarks like SWE-bench.

How to use

1
Go to Chat

Navigate to the "AI Chat" page.

2
Select Model

Ensure MiniMax M1 is selected.

3
Type Prompt

Ask a question or paste code.

4
Interact

Refine the answer by replying to the AI.

Compare LLMs Side-by-Side

Is MiniMax M1 better than Claude 3.5 or Gemini? Test same prompts simultaneously in the Chat Playground.

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