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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...

Prezzi

Pay-per-use

Nessun costo iniziale, paga solo per ciò che usi

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

Prova il modello

moonshotai/kimi-k2
Online
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Ciao! Sono un assistente IA utile. Come posso aiutarti?

Utilizzo API

Usa i seguenti esempi di codice per integrare la nostra 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)

Introduzione al modello

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
Tipollm

Funzionalità supportate

Input
Testo
Output
Testo
Contesto131,072
Output massimo131,072
Vision-
Function Calling✓ Supportato

Guida all'accesso API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
ID modellomoonshotai/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

Contesto

131K

Output max

131K

Uso strumenti

Supportato

Prova Kimi K2 su WaveSpeedAI

Accedi a Kimi K2 tramite la nostra API unificata — compatibile con OpenAI, senza cold start, prezzi trasparenti.

Domande frequenti su Kimi K2

Quanto costa Kimi K2 via API?+

Prezzi su WaveSpeedAI: $0.57 per milione di token in input e $2.30 per milione di token in output. Prompt caching e batch processing sono fatturati separatamente e riducono il costo effettivo su carichi lunghi e ripetitivi.

Qual è la context window di Kimi K2?+

Kimi K2 supporta fino a 131K token di contesto e fino a 131K token di output per richiesta.

Kimi K2 è compatibile con OpenAI?+

Sì. WaveSpeedAI espone Kimi K2 tramite un endpoint compatibile con OpenAI all'indirizzo https://llm.wavespeed.ai/v1. Punta l'SDK ufficiale di OpenAI a questa base URL con la tua API key WaveSpeedAI — senza altre modifiche al codice.

Come si inizia con Kimi K2?+

Accedi a WaveSpeedAI, crea una API key in Access Keys, poi invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. I nuovi account ricevono crediti gratuiti per testare Kimi K2.

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