Private AI
MiniMax M2.7 is the first model deeply involved in iterating on its own training. It excels in real-world software engineering (SWE-Pro 56.22%), end-to-end project delivery (VIBE-Pro 55.6%), and complex office workflows with strong tool-use compliance and agentic capabilities.
Added Mar 18, 2026
Model weightsContext Window
204.8K
Max Output
131.1K
Avg output tokens (7d)
1.8K tokens
Input Price (Auto)
$0.25/1M
Output Price (Auto)
$1.01/1M
Cache Read (Auto)
$0.13/1M
Capabilities
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
38.1
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Coding Index
52.6
GPQA Diamond
Graduate-level scientific reasoning
87.4%
Better than 88% of models compared
HLE
Humanity's Last Exam
28.1%
Better than 87% of models compared
IFBench
Instruction-following benchmark
75.7%
Better than 94% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
84.8%
Better than 76% of models compared
AA-LCR
Long context reasoning evaluation
68.7%
Better than 89% of models compared
SciCode
Python programming for scientific computing
47.0%
Better than 88% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
39.4%
Last updated Aug 4, 2026
Artificial AnalysisBetter than 86% of models compared
