Kimi K2 0711 version. Kimi-k2 is a Mixture-of-Experts (MoE) foundation model with exceptional coding and agent capabilities, featuring 1 trillion total parameters and 32 billion activated parameters. In benchmark evaluations covering general knowledge reasoning, programming, mathematics, and agent-related tasks, the K2 model outperforms other leading open-source models. Quantized at FP8.
Context Window
128.0K
Max Output
8.2K
Input Price (Auto)
$0.42/1M
Output Price (Auto)
$1.89/1M
Capabilities
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
26.3
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Coding Index
22.1
GPQA Diamond
Graduate-level scientific reasoning
76.6%
Better than 75% of models compared
HLE
Humanity's Last Exam
7.0%
Better than 60% of models compared
IFBench
Instruction-following benchmark
41.5%
Better than 50% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
61.1%
Better than 65% of models compared
AA-LCR
Long context reasoning evaluation
51.0%
Better than 67% of models compared
SciCode
Python programming for scientific computing
34.5%
Better than 63% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
15.9%
Better than 60% of models compared
AIME 2025
American Invitational Mathematics Examination 2025
57.0%
Better than 54% of models compared
AIME
American Invitational Mathematics Examination
69.3%
Better than 79% of models compared
MMLU-Pro
Professional and academic subject knowledge
82.4%
Better than 80% of models compared
Last updated May 15, 2026
Artificial AnalysisLiveCodeBench
Contamination-free coding benchmark
55.6%
Better than 62% of models compared
Math-500
Diverse mathematical problem solving benchmark
97.1%
Better than 87% of models compared
