Kimi K2 0905. 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.
Added Sep 25, 2025
Context Window
256.0K
Max Output
262.1K
Input Price (Auto)
$0.42/1M
Output Price (Auto)
$1.89/1M
Capabilities
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
30.9
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Coding Index
25.9
Agentic Index
37.7
GPQA Diamond
Graduate-level scientific reasoning
76.7%
Better than 75% of models compared
HLE
Humanity's Last Exam
6.3%
Better than 56% of models compared
IFBench
Instruction-following benchmark
41.7%
Better than 51% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
73.4%
Better than 72% of models compared
AA-LCR
Long context reasoning evaluation
52.3%
Better than 69% of models compared
GDPval-AA
Economically valuable tasks
18.2%
Better than 77% of models compared
CritPt
Research-level physics reasoning
0.0%
Better than 36% of models compared
SciCode
Python programming for scientific computing
30.7%
Better than 54% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
23.5%
Better than 71% of models compared
AIME 2025
American Invitational Mathematics Examination 2025
57.3%
Better than 54% of models compared
MMLU-Pro
Professional and academic subject knowledge
81.9%
Better than 77% of models compared
AA-Omniscience Accuracy
Proportion of correctly answered questions
25.4%
Better than 88% of models compared
Last updated May 15, 2026
Artificial AnalysisLiveCodeBench
Contamination-free coding benchmark
61.0%
Better than 67% of models compared
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
69.6%
Better than 78% of models compared
