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Kimi K2
Kimi K2 is an open-source large language model with 1T parameters and an MoE architecture released by Moonshot AI. It specializes in code generation, mathematical reasoning, and Agent tool invocation capabilities, and supports a 128K context.
Intelligence(Medium)
Speed(Slow)
Input Supported Modalities
No
Is Reasoning Model
128,000
Context Window
16,000
Maximum Output Tokens
2025-07-01
Knowledge Cutoff
Pricing
￥4.1 /M tokens
Input
￥16.56 /M tokens
Output
￥9.27 /M tokens
Blended Price
Quick Simple Comparison
Kimi K2
￥0.57
Basic Parameters
Kimi K2Technical Parameters
Parameter Count
1,000,000.0M
Context Length
128.00k tokens
Training Data Cutoff
2025-07-01
Open Source Category
Open Weights (Permissive License)
Multimodal Support
Text Only
Throughput
45
Release Date
2025-07-11
Response Speed
31.853,682 tokens/s
Benchmark Scores
Below is the performance of Kimi K2 in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
57.59
Large Language Model Intelligence Level
Coding Index
36.52
Indicator of AI model performance on coding tasks
Math Index
83.23
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
82.4
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
76.6
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
7
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
55.6
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
17.5
The model's capability in code generation for scientific computing or specific scientific domains
HumanEval
92.6
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
97.1
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
69.3
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
GPT 5 Mini
openai
￥1.8
Input tokens/million
￥14.4
Output tokens/million
400k
Context Length
GPT 5 Standard
openai
￥63
Input tokens/million
￥504
Output tokens/million
400k
Context Length
GPT 5 Nano
openai
￥0.36
Input tokens/million
￥2.88
Output tokens/million
400k
Context Length
GPT 5
openai
￥9
Input tokens/million
￥72
Output tokens/million
400k
Context Length
GLM 4.5
chatglm
￥0.43
Input tokens/million
￥1.01
Output tokens/million
131k
Context Length
Gemini 2.0 Flash Lite (Preview)
google
￥0.58
Input tokens/million
￥2.16
Output tokens/million
1M
Context Length
Gemini 1.0 Pro
google
￥3.6
Input tokens/million
￥10.8
Output tokens/million
33k
Context Length
Qwen2.5 Coder Instruct 32B
alibaba
￥0.65
Input tokens/million
￥0.65
Output tokens/million
131k
Context Length