moonshot
moonshotai/kimi-k3

moonshotai/kimi-k3

Tanggal rilis: 2026-07-16

1,048,576 context · $3.00/M input tokens · $15.00/M output tokens

Kimi K3 is Moonshot AI's flagship open-weight multimodal reasoning model. It is built for complex coding, knowledge work, and long-horizon agentic workflows, with strong performance on large codebase navigation, tool use, debugging, visual reasoning, and iterative problem solving. WaveSpeed AI exposes moonshotai/kimi-k3 through an OpenAI-compatible API, so it can be used with standard OpenAI SDKs and existing chat-completions-based application flows.

Harga

Bayar sesuai pemakaian

Tanpa biaya di muka, bayar hanya sesuai penggunaan

Input$3.00 / M Tokens
Output$15.00 / M Tokens
Cache Read$0.30 / M Tokens

Coba model

moonshotai/kimi-k3
Online
moonshot
Hai! Saya asisten AI yang siap membantu. Ada yang bisa saya bantu?
Siap memakai model ini di coding agent lokal?Setup agent

Penggunaan API

Gunakan contoh kode berikut untuk integrasi dengan API kami:

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'moonshotai/kimi-k3',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Pengenalan Model

MoonshotAI: Kimi K3

Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at...

This model is available through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.


Why It Looks Great

  • text+image+video->text architecture for Text, Image, Video to Text workloads
  • 1048576 context window for long prompts, document analysis, and multi-turn workflows
  • Vision input support for image understanding and multimodal tasks
  • Function calling and tool-use support for agentic application workflows
  • Structured output support for JSON responses and schema-constrained generation
  • Reasoning controls available through supported parameters

Key Features

  • Context Window: 1048576 tokens
  • Max Input: 104858 tokens
  • Max Output: 943718 tokens
  • Vision: Supported
  • Function Calling: Supported
  • Structured Outputs: Supported
  • Image Generation: Not listed
  • Audio Input: Not listed
  • Supported Parameters: frequency_penalty, include_reasoning, logit_bias, logprobs, max_completion_tokens, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

Specifications

SpecificationValue
Providermoonshot
Model TypeChat Completions model
Architecturetext+image+video->text
Context Window1048576 tokens
Max Input104858 tokens
Max Output943718 tokens
InputText, Image, Video
OutputText
VisionSupported
Function CallingSupported
Structured OutputsSupported
Release DateJuly 16, 2026

How to Use

  1. Write your prompt - describe the task, provide context, and specify the 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-k3


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-k3",
    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-k3",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: moonshotai/kimi-k3
  • Provider: moonshot

Info

Penyediamoonshot
Tipellm

Fitur yang Didukung

Input
TeksGambar
Output
Teks
Konteks1,048,576
Output Maks-
Vision✓ Didukung
Function Calling✓ Didukung

Panduan Akses API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDmoonshotai/kimi-k3

Kimi K3 API

moonshotai/kimi-k3

Kimi K3 is Moonshot AI's flagship open-weight multimodal reasoning model. It is built for complex coding, knowledge work, and long-horizon agentic workflows, with strong performance on large codebase navigation, tool use, debugging, visual reasoning, and iterative problem solving. WaveSpeed AI exposes `moonshotai/kimi-k3` through an OpenAI-compatible API, so it can be used with standard OpenAI SDKs and existing chat-completions-based application flows.

Input

$3 /M

Output

$15 /M

Konteks

1049K

Vision

Didukung

Penggunaan Tool

Didukung

Coba Kimi K3 di WaveSpeedAI

Akses Kimi K3 melalui API terpadu kami — kompatibel dengan OpenAI, tanpa cold start, harga transparan.

Pertanyaan Umum tentang Kimi K3

Berapa biaya Kimi K3 melalui API?+

Harga di WaveSpeedAI: $3.00 per juta token input dan $15.00 per juta token output. Prompt caching dan batch processing ditagih terpisah dan mengurangi biaya efektif pada beban kerja yang panjang dan berulang.

Berapa context window Kimi K3?+

Kimi K3 mendukung hingga 1049K token konteks dengan hingga — token output per permintaan.

Apakah Kimi K3 kompatibel dengan OpenAI?+

WaveSpeedAI menyediakan Kimi K3 di https://llm.wavespeed.ai/v1 melalui antarmuka Chat Completions yang kompatibel dengan OpenAI. Sebagian besar klien OpenAI SDK cukup mengganti base URL dan API key; field opsional bergantung pada model.

Bagaimana memulai dengan Kimi K3?+

Masuk ke WaveSpeedAI, buat API key di Access Keys, lalu kirim permintaan ke https://llm.wavespeed.ai/v1/chat/completions dengan model id yang ditampilkan di atas. Lihat katalog model terbaru untuk ketersediaan, kemampuan, dan harga.

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