Private AI
MiniMax M3 Thinking is the adaptive-thinking version of MiniMax's open-weights frontier model for coding, agent workflows, tool use, long-context tasks, and native multimodal understanding. MiniMax reports 59.0% on SWE-Bench Pro and 66.0% on Terminal Bench 2.1, with Sparse Attention designed to scale context to 1M. It starts with a 512K context cap on NanoGPT for now.
Added Jun 1, 2026
Model weightsContext Window
512.0K
Max Output
80.0K
Avg output tokens (7d)
2.3K tokens
Input Price (Auto)
$0.31/1M
Output Price (Auto)
$1.26/1M
Cache Read (Auto)
$0.063/1M
Capabilities
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
44.4
Choose explicit providers for this model. Auto routing remains available as the default option.
Loading provider options…
Coding Index
58.6
GPQA Diamond
Graduate-level scientific reasoning
92.9%
Better than 99% of models compared
HLE
Humanity's Last Exam
37.1%
Better than 97% of models compared
IFBench
Instruction-following benchmark
82.9%
Better than 99% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
88.9%
Better than 81% of models compared
AA-LCR
Long context reasoning evaluation
74.0%
Better than 98% of models compared
SciCode
Python programming for scientific computing
45.4%
Better than 89% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
42.4%
Last updated Jun 22, 2026
Artificial AnalysisBetter than 90% of models compared
