LangMart: MiniMax: MiniMax M2

Model Overview

Description

MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning, tool use, and multi-step task execution while maintaining low latency and deployment efficiency.

The model excels in code generation, multi-file editing, compile-run-fix loops, and test-validated repair, showing strong results on SWE-Bench Verified, Multi-SWE-Bench, and Terminal-Bench. It also performs competitively in agentic evaluations such as BrowseComp and GAIA, effectively handling long-horizon planning, retrieval, and recovery from execution errors.

Benchmarked by Artificial Analysis, MiniMax-M2 ranks among the top open-source models for composite intelligence, spanning mathematics, science, and instruction-following. Its small activation footprint enables fast inference, high concurrency, and improved unit economics, making it well-suited for large-scale agents, developer assistants, and reasoning-driven applications that require responsiveness and cost efficiency.

To avoid degrading this model's performance, MiniMax highly recommends preserving reasoning between turns. Learn more about using reasoning_details to pass back reasoning in our docs.

Description

LangMart: MiniMax: MiniMax M2 is a language model provided by minimax. This model offers advanced capabilities for natural language processing tasks.

Provider

minimax

Specifications

Pricing

Capabilities

• Frequency penalty
• Include reasoning
• Max tokens
• Min p
• Presence penalty
• Reasoning
• Repetition penalty
• Response format
• Seed
• Stop
• Structured outputs
• Temperature
• Tool choice
• Tools
• Top k
• Top p