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Kimi K2

KimiKimiOpen WeightMIT · Usage Commercial

Description

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.

Date de sortie
2025-07-11
Paramètres
1.0T
Longueur du contexte
131K
Modalités
text

Radar de capacités

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

Classements

Domaine#RangScoreSource
Capacité agentique100
39.0
LS
Classement codage227
50.0
AA
Classement général236
51.0
AA
Science251
49.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

Terminal-Bench30.0%Aut.
Terminus25.0%Aut.

Biology

GPQANYU + Cohere + Anthropic (2023)75.1%Aut.

Chemistry

SuperGPQA57.2%Aut.

Code

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

Communication

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

Factuality

SimpleQA31.0%Aut.

Finance

MMLU89.5%Aut.
MMLU-Pro81.1%Aut.
ACEBench76.5%Aut.

General

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

Math

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

Reasoning

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

Indices d'évaluation AA

(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

Scores par catégorie LLM Stats

(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

Tarification

Prix d'entrée$0.57 / 1M tokens
Prix de sortie$2.3 / 1M tokens
Prix mixte (3:1)$1.002 / 1M tokens

Vitesse

Tokens/sec0.0
Délai du premier token0.00s
Temps de réponse0.00s

Classement des Prix par Fournisseur

Classement des Prix par Fournisseur

7 fournisseurs

Moins cher: OpenCode ZenPlus cher: LLM Gateway
FournisseurEntréeSortie
1OpenCode ZenMoins cher
$0.4
$2.5
2FastRouter
$0.55
$2.2
3KimiPRINCIPAL
$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

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes

LLM StatsArtificial Analysis