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
Model weightsContext Window
256.0K
Max Output
262.1K
Avg output tokens (7d)
341 tokens
Input Price (Auto)
$0.60/1M
Output Price (Auto)
$2.50/1M
Cache Read (Auto)
$0.30/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
24.0
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
76.7%
Better than 63% of models compared
HLE
Humanity's Last Exam
6.4%
Better than 44% of models compared
IFBench
Instruction-following benchmark
41.7%
Better than 43% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
73.4%
Better than 65% of models compared
AA-LCR
Long context reasoning evaluation
53.7%
Better than 56% of models compared
Coding
SciCode
Python programming for scientific computing
30.7%
Better than 43% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
23.5%
Better than 63% of models compared
LiveCodeBench
Contamination-free coding benchmark
61.0%
Better than 67% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
57.3%
Better than 54% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
81.9%
Better than 77% of models compared
Last updated Aug 16, 2026
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