Kimi K2

Chat Completions

kimi-k2

MoonShotAI|Created Jul 12, 2025|131.1k context

Chat Completions

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. Kimi K2 excels across a broad range of benchmarks, particularly in coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) tasks. It supports long-context inference up to 128K tokens and is designed with a novel training stack that includes the MuonClip optimizer for stable large-scale MoE training.

Overview Specifications Activity Performance Uptime Examples API Reference

Compare

Pricing-50%

Pay-as-you-go rates for this model. More details can be found here.

Input Tokens (1M)

$0.29

Output Tokens (1M)

$1.15

Capabilities

Input Modalities

Text

Output Modalities

Text

Supported Parameters

Available parameters for API requests

Frequency PenaltyLogit BiasLogprobsMax Completion TokensPresence PenaltyResponse FormatStopTemperatureTop PToolsTool ChoiceParallel Tool Calls

Usage Analytics

Token usage of this model on our platform

Throughput

Time-To-First-Token (TTFT)

Not enough TTFT data

Code Example

Example code for using this model through our API with Python (OpenAI SDK) or cURL. Replace placeholders with your API key and model ID.

Basic request example. Ensure API key permissions. For more details, see our documentation.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.naga.ac/v1",
    api_key="YOUR_API_KEY",
)

resp = client.chat.completions.create(
    model="kimi-k2",
    messages=[
        {"role": "user", "content": "What's 2+2?"}
    ],
    temperature=0.2,
)
print(resp.choices[0].message.content)