Kimi K2 0711
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Kimi K2 0711

kimi-k2-0711llms.txt
Moonshot AI
Kimi-K2 is a MoE architecture foundational model with extremely powerful coding and agent capabilities, featuring a total of 1 trillion parameters and activating 32 billion parameters. In benchmark performance tests across major categories such as general knowledge reasoning, programming, mathematics, and agents, the K2 model outperforms other mainstream open-source models. The Kimi-K2 model supports a context length of 128k tokens. It does not support visual capabilities.

Pricing

  • Input Tokens: $0.540 /M tokens
  • Output Tokens: $2.160 /M tokens

Input Modalities

  • Text

Output Modalities

  • Text

Capabilities

  • Tools
  • Tool calling
  • Structured outputs

Providers

Baidu kimi-k2-instruct
Pricing$0.540$2.160
Context128K
Max output32K
Latency0.8S
Throughput50.2TPS
Uptime
0.00% uptime 3 days ago
0.00% uptime 2 days ago
0.00% uptime yesterday
Moonshot kimi-k2-0711-preview
Pricing$0.620$2.480
Context131K
Max output131K
Latency2.5S
Throughput23.9TPS
Uptime
0.00% uptime 3 days ago
0.00% uptime 2 days ago
0.00% uptime yesterday

Performance for kimi-k2-0711

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-k2-0711",
    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 0711?

Kimi-K2 is a MoE architecture foundational model with extremely powerful coding and agent capabilities, featuring a total of 1 trillion parameters and activating 32 billion parameters. In benchmark performance tests across major categories such as general knowledge reasoning, programming, mathematics, and agents, the K2 model outperforms other mainstream open-source models. The Kimi-K2 model supports a context length of 128k tokens. It does not support visual capabilities.