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Kimi K2

KimiKimi오픈 웨이트MIT · 상업적 사용 가능

설명

Kimi K2-Instruct-0905 is the latest, most capable version of Kimi K2, achieving state-of-the-art performance in frontier knowledge, math, and coding among non-thinking models. This Mixture-of-Experts model features 32 billion activated parameters and 1 trillion total parameters, meticulously optimized for agentic tasks. Key features include enhanced agentic coding intelligence, extended context length to 256K tokens, and a hybrid architecture trained with MuonClip optimizer on 15.5T tokens. The model achieves 65.8% on SWE-bench Verified (single attempt), 47.3% on SWE-bench Multilingual, and excels at tool use with 70.6% on Tau2-retail. It is a reflex-grade model without long thinking, designed to act and execute complex tasks seamlessly.

출시일
2025-07-11
파라미터
1.0T
컨텍스트 길이
131K
모달리티
text

능력 레이더

37
general
51
coding
68
reasoning
48
science
60
agents
0
multimodal

랭킹

도메인#순위점수소스
에이전트형 역량97
39.0
LS
코딩 랭킹220
50.0
AA
종합 랭킹230
51.0
AA
과학247
49.0
AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Agents

Terminal-Bench30.0%자체 보고
Terminus25.0%자체 보고

Biology

GPQANYU + Cohere + Anthropic (2023)75.1%자체 보고

Chemistry

SuperGPQA57.2%자체 보고

Code

HumanEvalOpenAI (2021)93.3%자체 보고
EvalPlus0.80 / 100자체 보고
SWE-bench Verified (Agentic Coding)65.8%자체 보고
SWE-Bench Verified65.8%자체 보고
Aider-Polyglot60.0%자체 보고
LiveCodeBench53.7%자체 보고
SWE-bench Multilingual47.3%자체 보고

Communication

Tau2 Retail70.6%자체 보고
Tau2 Telecom65.8%자체 보고
Tau2 Airline56.5%자체 보고
Multi-Challenge54.1%자체 보고

Factuality

SimpleQA31.0%자체 보고

Finance

MMLU89.5%자체 보고
MMLU-Pro81.1%자체 보고
ACEBench76.5%자체 보고

General

MMLU-Redux92.7%자체 보고
C-Eval92.5%자체 보고
MMLU-redux-2.090.2%자체 보고
IFEvalGoogle Research (2023)89.8%자체 보고
MultiPL-E85.7%자체 보고
TriviaQA85.1%자체 보고
CSimpleQA78.4%자체 보고
LiveBench76.4%자체 보고
LiveCodeBench v653.7%자체 보고
SWE-bench Verified (Agentless)51.8%자체 보고

Math

MATH-50097.4%자체 보고
GSM8k97.3%자체 보고
CBNSL95.6%자체 보고
CNMO 202474.3%자체 보고
MATH70.2%자체 보고
AIME 202469.6%자체 보고
PolyMath-en65.1%자체 보고
AIME 202549.5%자체 보고
HMMT 202538.8%자체 보고
Humanity's Last Exam4.7%자체 보고

Reasoning

AutoLogi89.5%자체 보고
ZebraLogic89.0%자체 보고
HumanEval-ER81.1%자체 보고
MuSR76.4%자체 보고
SWE-bench Verified (Multiple Attempts)71.6%자체 보고
OJBench27.1%자체 보고

AA 평가 지수

(Artificial Analysis)
Math Index(Artificial Analysis)
57.0
Intelligence Index(Artificial Analysis)
19.7
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
1.0
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.8
Aime(MAA (Mathematical Association of America))
0.7
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.6
Aime 25(MAA (Mathematical Association of America))
0.6
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.6
Lcr(Artificial Analysis)
0.5
Ifbench(Google Research (2023))
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.3
Terminalbench Hard(Stanford × Laude Institute (2026))
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.1

LLM Stats 카테고리 점수

(LLM Stats (zeroeval))
Instruction Following
90
Language
90
Structured Output
90
Legal
80
Finance
80
Healthcare
80
Biology
80
Math
70
Physics
70
Frontend Development
70
Chemistry
70
Reasoning
60
General
60
Communication
60
Economics
60
Tool Calling
60
Code
50
Factuality
30
Agents
20
Vision
0

가격

입력 가격$0.57 / 1M 토큰
출력 가격$2.3 / 1M 토큰
혼합 가격 (3:1)$1.002 / 1M 토큰

속도

토큰/초0.0
첫 토큰 지연0.00s
첫 응답 지연0.00s

공급자 가격 순위

공급자 가격 순위

7개 공급자

최저가: OpenCode Zen최고가: LLM Gateway
공급자입력출력
1OpenCode Zen최저가
$0.4
$2.5
2FastRouter
$0.55
$2.2
3Kimi주요
$0.57
$2.3
4OpenRouter
$0.57
$2.3
5Kilo Gateway
$0.57
$2.3
6Vercel AI Gateway
$0.57
$2.3
7LLM Gateway
$0.57
$2.3

이 모델의 다양한 API 공급자 간 가격 비교.

외부 링크

LLM StatsArtificial Analysis