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Kimi K2

KimiKimi开源权重MIT · 商用许可

描述

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.

发布日期
2025-07-11
参数规模
1.0T
上下文长度
131K
支持模态
text

能力雷达图

33
general
56
coding
68
reasoning
55
science
60
agents
0
multimodal

排行榜排名

领域#排名分数来源
代码能力榜314
48.0
AA
通用能力榜274
46.0
AA
科学能力325
44.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Chat

IFEvalGoogle Research (2023)89.8%自报
Tau2 Airline56.5%自报
Multi-Challenge54.1%自报

Communication

Tau2 Retail70.6%自报
Tau2 Telecom65.8%自报

Factuality

SimpleQA31.0%自报

General

C-Eval92.5%自报
MMLU89.5%自报
MultiPL-E85.7%自报
TriviaQA85.1%自报
CSimpleQA78.4%自报
ACEBench76.5%自报
Aider-Polyglot60.0%自报
SWE-bench Verified (Agentless)51.8%自报

Language

MMLU-Redux92.7%自报
MMLU-redux-2.090.2%自报
MMLU-Pro81.1%自报

Math

MATH-50097.4%自报
GSM8k97.3%自报
CBNSL95.6%自报
LiveBench76.4%自报
CNMO 202474.3%自报
MATH70.2%自报
AIME 202469.6%自报
PolyMath-en65.1%自报
AIME 202549.5%自报
HMMT 202538.8%自报

Reasoning

HumanEvalOpenAI (2021)93.3%自报
AutoLogi89.5%自报
ZebraLogic89.0%自报
HumanEval-ER81.1%自报
EvalPlus0.80 / 100自报
MuSR76.4%自报
GPQANYU + Cohere + Anthropic (2023)75.1%自报
SWE-bench Verified (Multiple Attempts)71.6%自报
SWE-bench Verified (Agentic Coding)65.8%自报
SWE-Bench Verified65.8%自报
SuperGPQA57.2%自报
LiveCodeBench v653.7%自报
LiveCodeBench53.7%自报
SWE-bench Multilingual47.3%自报
Terminal-Bench30.0%自报
OJBench27.1%自报
Terminus25.0%自报
Humanity's Last Exam4.7%自报

AA 评测指数

(Artificial Analysis)
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
97.1
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
82.4
Gpqa(NYU + Cohere + Anthropic (2023))
76.6
Aime(MAA (Mathematical Association of America))
69.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
61.1
Math Index(Artificial Analysis)
57.0
Aime 25(MAA (Mathematical Association of America))
57.0
Livecodebench(UC Berkeley + MIT + Cornell (2024))
55.6
Lcr(Artificial Analysis)
53.0
Ifbench(Google Research (2023))
41.5
Terminalbench Hard(Stanford × Laude Institute (2026))
15.9
Intelligence Index(Artificial Analysis)
12.7
Hle(Center for AI Safety + Scale AI (2025))
7.4

LLM Stats 分类评分

(LLM Stats (zeroeval))
Instruction Following
90
Language
90
Structured Output
90
Legal
80
Finance
80
Healthcare
80
Biology
80
Chat
70
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

定价

输入价格$0.57 / 1M tokens
输出价格$2.3 / 1M tokens
混合价格(3:1)$1.002 / 1M tokens

速度

Tokens/秒0.0
首Token延迟0.00s
首回答延迟0.00s

供应商价格排行

供应商价格排行

7 个供应商

最便宜: OpenCode Zen最贵: DevPass (LLM Gateway)
供应商输入输出
1OpenCode Zen最便宜
$0.4
$2.5
2FastRouter
$0.55
$2.2
3Kimi主要
$0.57
$2.3
4OpenRouter
$0.57
$2.3
5Kilo Gateway
$0.57
$2.3
6Vercel AI Gateway
$0.57
$2.3
7DevPass (LLM Gateway)
$0.57
$2.3

比较该模型在不同 API 供应商之间的定价。

外部链接