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Kimi K2 Thinking

KimiKimiOpen WeightMIT · Commercial OK

설명

Kimi K2 Thinking is the latest, most capable version of open-source thinking model. Starting with Kimi K2, it is built as a thinking agent that reasons step-by-step while dynamically invoking tools. It sets a new state-of-the-art on Humanity's Last Exam (HLE), BrowseComp, and other benchmarks by dramatically scaling multi-step reasoning depth and maintaining stable tool-use across 200–300 sequential calls. At the same time, K2 Thinking is a native INT4 quantization model with 256k context window, achieving lossless reductions in inference latency and GPU memory usage. Key features include deep thinking & tool orchestration with end-to-end training to interleave chain-of-thought reasoning with function calls, native INT4 quantization via Quantization-Aware Training (QAT) achieving lossless 2x speed-up, and stable long-horizon agency maintaining coherent goal-directed behavior across up to 200–300 consecutive tool invocations.

출시일
2025-11-06
파라미터
1.0T
컨텍스트 길이
262K
모달리티
text

능력 레이더

51
general
53
coding
93
reasoning
57
science추정
50
agents
0
multimodal

전용 과학 벤치마크가 없을 때 Science는 추론 프록시를 사용하여 추정합니다.

랭킹

도메인#순위점수소스
Agents & Tools63
54.0
LS
Code Ranking60
70.0
AA
General Ranking47
79.0
AA
Math Reasoning12
96.0
AA
Reasoning56
66.0
LS
Science56
70.0
AA

벤치마크 점수 (LLM Stats)

Agents

BrowseComp60.2%자체 보고
Terminal-Bench47.1%자체 보고

Biology

GPQA84.5%자체 보고
SciCode44.8%자체 보고

Code

SWE-Bench Verified71.3%자체 보고
SWE-bench Multilingual61.1%자체 보고
Multi-SWE-Bench41.9%자체 보고

Communication

WritingBench73.8%자체 보고

Economics

FinSearchComp-T347.4%자체 보고

Finance

MMLU-Pro84.6%자체 보고

General

MMLU-Redux94.4%자체 보고
LiveCodeBench v683.1%자체 보고

Healthcare

HealthBench58.0%자체 보고

Math

AIME 2025100.0%자체 보고
HMMT 202597.5%자체 보고
IMO-AnswerBench78.6%자체 보고
Humanity's Last Exam51.0%자체 보고

Reasoning

FRAMES87.0%자체 보고
BrowseComp-zh62.3%자체 보고
Seal-056.3%자체 보고
OJBench48.7%자체 보고

AA 평가 지수

Math Index
94.7
Intelligence Index
40.9
Coding Index
34.8
Aime 25
0.9
Tau2
0.9
Livecodebench
0.9
Mmlu Pro
0.8
Gpqa
0.8
Ifbench
0.7
Lcr
0.7
Scicode
0.4
Terminalbench Hard
0.3
Hle
0.2

LLM Stats 카테고리 점수

General
90
Language
90
Finance
80
Legal
80
Math
80
Writing
70
Communication
70
Creativity
70
Frontend Development
70
Healthcare
70
Reasoning
70
Biology
60
Chemistry
60
Physics
60
Search
60
Vision
50
Agents
50
Code
50

가격

입력 가격$0.6 / 1M tokens
출력 가격$2.5 / 1M tokens
혼합 가격 (3:1)$1.075 / 1M tokens

속도

토큰/초126.7 tokens/s
첫 토큰 지연0.91s
첫 응답 지연16.69s

사용 가능한 프로바이더

(LS 내부 단위)

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