Kimi K2 Thinking
Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model, extending the K2 series into agentic, long-horizon reasoning. Built on a trillion-parameter Mixture-of-Experts (MoE) architecture, it activates 32 billion parameters per forward pass and supports a 256k-token context window. Optimized for persistent step-by-step thought and dynamic tool use, it enables complex reasoning workflows and stable multi-agent behavior across 200–300 tool calls, setting new open-source records on HLE, BrowseComp, SWE-Multilingual, and LiveCodeBench. With MuonClip optimization and large-scale MoE architecture, it delivers strong reasoning depth and high inference efficiency for demanding agentic and analytical tasks.
Pricing
Pay-as-you-go rates for this model. More details can be found here.
Input Tokens (1M)
$0.30
Cached Input Tokens (1M)
$0.07
Output Tokens (1M)
$1.25
Capabilities
Input Modalities
Output Modalities
Supported Parameters
Available parameters for API requests
Usage Analytics
Token usage across the last 30 active days
Uptime
Reliability over the last 7 days
Throughput
Time-To-First-Token (TTFT)
Code Example
Example code for using this model through our API with Python (OpenAI SDK) or cURL. Replace placeholders with your API key and model ID.
Basic request example. Ensure API key permissions. For more details, see our documentation.
from openai import OpenAI
client = OpenAI(
base_url="https://api.naga.ac/v1",
api_key="YOUR_API_KEY",
)
resp = client.chat.completions.create(
model="kimi-k2-thinking",
messages=[
{{"role": "user", "content": "What's 2+2?"}}
],
temperature=0.2,
)
print(resp.choices[0].message.content)