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Very High Reasoning

Kimi K2

Kimi K2 is a 1 trillion parameter open-source AI model from Moonshot AI that delivers frontier performance across reasoning, coding, and agentic tasks at a fraction of the cost of proprietary alternatives. Optimized for autonomous workflows and tool use through advanced synthetic data training, it combines the power of established models with open-weight accessibility and enterprise-grade efficiency.

128k Context
Very High Intelligence
Dec '24 Knowledge

Available for Chat, Vision, and File Uploads.

Performance Benchmarks

MMLU
87.8%
HumanEval
94.5%
GSM8k
92.1%

How do you want to interact?

Start a Conversation

Ask anything.
Have a natural conversation, brainstorm ideas, draft emails, or ask for advice.

Start Chatting

Use a Persona

Specialized Experts.
Instruct the AI to act as a Coding Tutor, Marketing Expert, or Travel Guide.

Pick a Persona

Why use Kimi K2?

Native Multimodality

Pre-trained on vision-language tokens, excels in visual knowledge, cross-modal reasoning, and agentic tool use grounded in visual inputs

Coding with Vision

Generates code from visual specifications like UI designs and video workflows, orchestrates tools for visual data processing

Agent Swarm

Coordinates self-directed swarm of up to 100 specialized agents for parallel execution of complex tasks, reducing time by 4.5x

Capability Examples

Agentic Coding Task
Write a Python function to scrape weather data from an API, parse it, and generate a daily report.
python def get_weather_report(city, api_key): import requests data = requests.get(f'api.weather.com?city={city}&key={api_key}').json() temp = data['temp'] report = f"Weather in {city}: {temp}°C" return report Here's the complete, tested function with error handling and sample usage.[fas fa-code]
Multi-Step Research Workflow
Research the latest trends in MoE models, summarize key benchmarks, and suggest 3 applications.
Kimi K2 leads open-source MoE with 1T params (32B active), topping SWE-Bench (65.8), Tau2-Bench (66.1). Trends: Agentic focus via RL on 15.5T tokens, 256k context. Applications: 1) Autonomous coding agents. 2) Long-doc analysis. 3) Tool-chaining for research.[fas fa-search]

How to use

1
Go to Chat

Navigate to the "AI Chat" page.

2
Select Model

Ensure Kimi K2 is selected.

3
Type Prompt

Ask a question or paste code.

4
Interact

Refine the answer by replying to the AI.

Compare LLMs Side-by-Side

Is Kimi K2 better than Claude 3.5 or Gemini? Test same prompts simultaneously in the Chat Playground.

Open Chat Playground

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