MiniMax M1

MiniMax-M1 is a hybrid MoE reasoning model with 40K thinking budget. World's first open-weight, large-scale hybrid-attention model with lightning attention for efficient test-time compute scaling. Excels at complex tasks requiring extensive reasoning.

Added Jan 8, 2025

Pricing

Auto routing · per 1M tokens
Input
$0.14
Output
$1.33
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Specifications

Context window
1M
Max output
131.1K
Parameters
456B / 45.9B
Total / active
Avg output (7d)
266 tokens
Longer than 22% of models

Benchmarks

Sourced from Artificial Analysis.

Intelligence Index

10.0

Better than 40% of models compared

Agentic work

T²-Bench Telecom (legacy)

Legacy fallback · Conversational AI agents in dual-control scenarios

31.6%

Better than 39% of models compared

Reasoning

HLE

Humanity's Last Exam

7.8%

Better than 45% of models compared

IFBench

Instruction-following benchmark

41.2%

Better than 41% of models compared

Coding

Terminal-Bench Hard (legacy)

Legacy fallback · Agentic coding and terminal use

2.3%

Better than 20% of models compared

LiveCodeBench

Contamination-free coding benchmark

65.7%

Better than 74% of models compared

Math

AIME 2025

American Invitational Mathematics Examination 2025

13.7%

Better than 17% of models compared

AIME

American Invitational Mathematics Examination

81.3%

Better than 89% of models compared

Math-500

Diverse mathematical problem solving benchmark

97.2%

Better than 88% of models compared

Knowledge

MMLU-Pro

Professional and academic subject knowledge

80.8%

Better than 71% of models compared

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

68.2%

Better than 45% of models compared

Last updated Oct 3, 2026

Artificial Analysis

Providers

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