Kimi K2 Thinking
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Kimi K2 Thinking

kimi-k2-thinkingllms.txt
Moonshot AI
Kimi K2 Thinking is Moonshot AI's most advanced open-source inference model to date, extending the K2 series into intelligent agent and long-context inference domains. The model is built on the trillion-parameter mixture of experts (MoE) architecture introduced by Kimi K2, activating 32 billion parameters per forward pass and supporting a context window of 256,000 tokens.

Pricing

  • Input Tokens: $0.548 /M tokens
  • Output Tokens: $2.192 /M tokens
  • Cache Read: $0.137 /M tokens

Input Modalities

  • Text

Output Modalities

  • Text

Capabilities

  • Thinking
  • Tools
  • Tool calling
  • Structured outputs

Providers

Azure azure-kimi-k2-thinking
Pricing$0.600$2.500
Context256K
Max output256K
Latency0.5S
Throughput69.0TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today

Performance for kimi-k2-thinking

Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).

Uptime
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Latency
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Throughput
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Try this model

Python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"],
    base_url="https://aihubmix.com/v1",
)

response = client.chat.completions.create(
    model="kimi-k2-thinking",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

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

Frequently asked questions

What is Kimi K2 Thinking?

Kimi K2 Thinking is Moonshot AI's most advanced open-source inference model to date, extending the K2 series into intelligent agent and long-context inference domains. The model is built on the trillion-parameter mixture of experts (MoE) architecture introduced by Kimi K2, activating 32 billion parameters per forward pass and supporting a context window of 256,000 tokens.