MiniMax M2

Name: MiniMax M2
Author: MiniMax

MiniMax

MiniMax M2 is a large language model by MiniMax, designed for versatile performance across reasoning, coding, mathematics, and conversation. It supports multimodal inputs and features a large context window, making it suitable for complex analytical and creative tasks.

Key Specifications

Parameters

230.0B

Context

1.0M

Release Date

October 26, 2025

Average Score

60.5%

API Documentation Repository Model Weights Results Blog

Timeline

Key dates in the model's history

Announcement / Last Update

October 26, 2025

Today

October 5, 2026

Technical Specifications

Parameters

230.0B

Training Tokens

Knowledge Cutoff

Family

Capabilities

MultimodalZeroEval

Pricing & Availability

Input (per 1M tokens)

$0.30

Output (per 1M tokens)

$1.20

Max Input Tokens

1.0M

Max Output Tokens

1.0M

Supported Features

Function CallingStructured OutputCode ExecutionWeb SearchBatch InferenceFine-tuning

Benchmark Results

Model performance metrics across various tests and benchmarks

Programming

Programming skills tests

SWE-Bench Verified

• Self-reported

69.4%

Reasoning

Logical reasoning and analysis

GPQA

Diamond subset • Self-reported

78.0%

Other Tests

Specialized benchmarks

LiveCodeBench

• Self-reported

83.0%

MMLU-Pro

• Self-reported

82.0%

AIME 2025

• Self-reported

78.0%

Tau-bench

• Self-reported

77.0%

AA-Index

• Self-reported

61.0%

BrowseComp

• Self-reported

44.0%

BrowseComp-zh

• Self-reported

48.5%

Humanity's Last Exam

without tools • Self-reported

12.5%

• Self-reported

72.0%

Multi-SWE-Bench

• Self-reported

36.2%

SciCode

• Self-reported

36.0%

SWE-bench Multilingual

• Self-reported

56.5%

Tau2 Telecom

• Self-reported

87.0%

Terminal-Bench

• Self-reported

46.3%

License & Metadata

License

mit

Announcement Date

October 26, 2025

Last Updated

October 26, 2025

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