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...
Pay-per-Use
Keine Vorabkosten, zahlen Sie nur, was Sie nutzen
Verwenden Sie die folgenden Codebeispiele zur Integration mit unserer 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)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.
| Specification | Value |
|---|---|
| Provider | Moonshotai |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 131072 tokens |
| Max Output | tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.5 |
| Output | $2.6 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: moonshotai/kimi-k2
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 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!"}]
}'
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...
Eingabe
$0.57 /M
Ausgabe
$2.3 /M
Kontext
131K
Max. Ausgabe
131K
Tool-Nutzung
Unterstützt
Zugriff auf Kimi K2 über unsere einheitliche API — OpenAI-kompatibel, keine Kaltstarts, transparente Preise.
Preise auf WaveSpeedAI: $0.57 pro Million Input-Tokens und $2.30 pro Million Output-Tokens. Prompt-Caching und Batch-Verarbeitung werden separat berechnet und reduzieren die effektiven Kosten bei langen, sich wiederholenden Workloads.
Kimi K2 unterstützt bis zu 131K Kontext-Tokens und bis zu 131K Output-Tokens pro Anfrage.
Ja. WaveSpeedAI stellt Kimi K2 über einen OpenAI-kompatiblen Endpunkt unter https://llm.wavespeed.ai/v1 bereit. Richten Sie das offizielle OpenAI SDK mit Ihrem WaveSpeedAI-API-Schlüssel auf diese Base-URL — keine weiteren Codeänderungen erforderlich.
Bei WaveSpeedAI anmelden, in Access Keys einen API-Schlüssel erstellen und eine Anfrage an https://llm.wavespeed.ai/v1/chat/completions mit der oben angezeigten Model-ID senden. Neue Konten erhalten kostenlose Credits, um Kimi K2 zu testen.