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moonshotai/kimi-k2

moonshotai/kimi-k2

131,072 context · $0.57/M input tokens · $2.30/M output tokens

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...

Pricing

Pay-per-use

No upfront costs, pay only for what you use

Input$0.57 / M Tokens
Output$2.30 / M Tokens

Try the model

moonshotai/kimi-k2
Online
moonshot
Hi! I am a helpful AI assistant. What can I do for you?

API Usage

Use the following code examples to integrate with our API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="moonshotai/kimi-k2",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Model Introduction

Moonshotai kimi-k2

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 bill

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.


Why It Looks Great

  • Large Language Model architecture for efficient processing
  • 131072 context window for long document handling
  • Competitive pricing at $0.5/$2.6 per million tokens

Key Features

  • Context Window: 131072 tokens
  • Max Output: N/A tokens
  • Vision: Supported
  • Function Calling: Supported

Specifications

SpecificationValue
ProviderMoonshotai
Model TypeLarge Language Model (LLM)
ArchitectureN/A
Context Window131072 tokens
Max Outputtokens
InputText
OutputText
VisionSupported
Function CallingSupported

Pricing

Token TypeCost per Million Tokens
Input$0.5
Output$2.6

How to Use

  1. Write your prompt — describe the task, provide context, and specify desired output format.
  2. Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: moonshotai/kimi-k2


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="moonshotai/kimi-k2",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "moonshotai/kimi-k2",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: moonshotai/kimi-k2
  • Provider: Moonshotai

Info

Providermoonshot
Typellm

Supported Functionality

Input
Text
Output
Text
Context131,072
Max Output131,072
Vision-
Function Calling✓ Supported

API Access Guide

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDmoonshotai/kimi-k2

Kimi K2 API

moonshotai/kimi-k2

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...

Input

$0.57 /M

Output

$2.3 /M

Context

131K

Max Output

131K

Tool Use

Supported

Try Kimi K2 on WaveSpeedAI

Access Kimi K2 through our unified API — OpenAI-compatible, no cold starts, transparent pricing.

Frequently Asked Questions about Kimi K2

How much does Kimi K2 cost via the API?+

Pricing on WaveSpeedAI: $0.57 per million input tokens and $2.30 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of Kimi K2?+

Kimi K2 supports up to 131K tokens of context with up to 131K tokens of output per request.

Is Kimi K2 OpenAI-compatible?+

Yes. WaveSpeedAI exposes Kimi K2 through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.

How do I get started with Kimi K2?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Kimi K2 before paying per token.

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