Explore MiniMax M2 - Efficient and Versatile AI

MiniMax M2 excels in coding and agentic workflows with efficiency.

Input: text Output: text Context: 196,608 tokens Release: 2025-10-23

MiniMax M2, developed by minimax and released on October 23, 2025, is a compact large language model tailored for coding and agentic workflows. With a context window of 204,800 tokens, it processes text inputs to generate text outputs efficiently. The model features 10 billion activated parameters, excelling in code generation, multi-file editing, and test-validated repair. It supports reasoning-driven applications, making it suitable for developer assistants and large-scale agents. MiniMax M2's design ensures fast inference and responsiveness, ideal for tasks requiring effective reasoning and planning.

Use Cases

Here are a few ways teams apply MiniMax: MiniMax M2 (free) in practice—from fast drafting to multimodal understanding. Adapt these ideas to your workflow.

Enhance coding with multi-file editing

Improve compile-run-fix loops

Facilitate test-validated repair

Support long-horizon planning tasks

Boost developer assistant capabilities

Key Features

A quick look at the capabilities that make this model useful in real projects.

Optimized for end-to-end coding tasks

10 billion activated parameters

Supports multi-step task execution

Handles long-horizon planning

Fast inference with low latency

Specs

Overview

Vendor
minimax

Model ID
minimax/minimax-m2:free

Release
2025-10-23

Modalities & context

Input
text

Output
text

Context
196,608 tokens

Parameters & defaults

Supported parameters: include_reasoning, max_tokens, reasoning, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_p

Defaults: temperature 1, top_p 0.95

Benchmark tests: MiniMax: MiniMax M2 (free)

We ran this model against a few representative prompts to show its range. Review the outputs below and be the judge.

Text

Prompt:

Write 150 words on how AI might positively upend work, leisure and creativity

AI can automate routine work, freeing people to focus on judgment, design, and care. Human-in-the-loop systems will coordinate tasks, monitor quality, and route exceptions to humans, while labor platforms pair skills with projects in near real time. Training adapts to each worker, and safety improves via predictive systems. These shifts should shorten the workweek, expand micro-entrepreneurship, and reduce burnout. In leisure, AI curates schedules, balances effort and recovery, and sparks low-barrier experiences: instant companions for language practice, adaptive workouts, and infinite sandboxes for exploration. Tools translate and explain content on the fly, broaden participation, and suggest cross-cultural exchanges. With boundaries and rituals, tech complements rather than consumes attention. Creativity accelerates as AI becomes a co-author—drafting, editing, and improvising across text, audio, and visuals. Newcomers find their voice through stylistic scaffolding; experts compress the distance between idea and iteration. Community tools remix contributions into open media commons, and small teams produce quality at scale.

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up.end

/ˌəpˈend/

verb

To “upend” means to completely disrupt, overturn, or drastically change the established order or structure of something. It implies a significant shift or alteration that can potentially have far-reaching consequences. When something is upended, it is turned upside down or transformed in a way that challenges conventional norms or expectations. The term often carries a sense of innovation, transformation, and sometimes even a hint of upheaval, indicating that the changes are not just minor adjustments but rather a fundamental reimagining of the status quo.

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