Moonshot AI's distinct Kimi K2 Thinking checkpoint is a mandatory-reasoning model for long-horizon agentic workflows and multi-step tool use.
Added Nov 6, 2025
Model weightsContext Window
262.1K
Max Output
98.3K
Avg output tokens (7d)
1.4K tokens
Input Price (Auto)
$0.60/1M
Output Price (Auto)
$2.50/1M
Cache Read (Auto)
$0.15/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
33.5
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
83.8%
Better than 77% of models compared
HLE
Humanity's Last Exam
23.8%
Better than 79% of models compared
IFBench
Instruction-following benchmark
68.1%
Better than 81% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
93.0%
Better than 89% of models compared
AA-LCR
Long context reasoning evaluation
70.3%
Better than 80% of models compared
Coding
SciCode
Python programming for scientific computing
42.4%
Better than 78% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
31.1%
Better than 73% of models compared
LiveCodeBench
Contamination-free coding benchmark
85.3%
Better than 96% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
94.7%
Better than 96% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
84.8%
Better than 89% of models compared
Last updated Aug 16, 2026
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