Private AI
MiniMax M2.1 builds on M2 with enhanced context understanding and improved complex tool use. 230B parameter MoE model (10B active) optimized for agentic workflows and long-horizon tasks.
Added Jan 20, 2025
Model weightsContext Window
200.0K
Max Output
131.1K
Input Price (Auto)
$0.31/1M
Output Price (Auto)
$1.26/1M
Cache Read (Auto)
$0.032/1M
Capabilities
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
31.4
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GPQA Diamond
Graduate-level scientific reasoning
83.0%
Better than 79% of models compared
HLE
Humanity's Last Exam
22.2%
Better than 82% of models compared
IFBench
Instruction-following benchmark
69.9%
Better than 84% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
85.4%
Better than 78% of models compared
AA-LCR
Long context reasoning evaluation
59.0%
Better than 71% of models compared
SciCode
Python programming for scientific computing
40.7%
Better than 77% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
28.8%
AIME 2025
American Invitational Mathematics Examination 2025
82.7%
Better than 79% of models compared
MMLU-Pro
Professional and academic subject knowledge
87.5%
Better than 98% of models compared
Last updated Jul 20, 2026
Artificial AnalysisBetter than 71% of models compared
LiveCodeBench
Contamination-free coding benchmark
81.0%
Better than 93% of models compared
