4. Deployment

[!Note]

You can access Kimi K2's API on https://platform.moonshot.ai , we provide OpenAI/Anthropic-compatible API for you.

The Anthropic-compatible API maps temperature by realtemperature = requesttemperature * 0.6 for better compatible with existing applications.

Our model checkpoints are stored in the block-fp8 format, you can find it on Huggingface.

Currently, Kimi-K2 is recommended to run on the following inference engines:

• vLLM
• SGLang
• KTransformers
• TensorRT-LLM

Deployment examples for vLLM and SGLang can be found in the Model Deployment Guide.

5. Model Usage

Chat Completion

Once the local inference service is up, you can interact with it through the chat endpoint:

def simplechat(client: OpenAI, modelname: str):
    messages = [
        {"role": "system", "content": "You are Kimi, an AI assistant created by Moonshot AI."},
        {"role": "user", "content": [{"type": "text", "text": "Please give a brief self-introduction."}]},
    ]
    response = client.chat.completions.create(
        model=model_name,
        messages=messages,
        stream=False,
        temperature=0.6,
        max_tokens=256
    )
    print(response.choices[0].message.content)

[!NOTE]

The recommended temperature for Kimi-K2-Instruct is temperature = 0.6.

If no special instructions are required, the system prompt above is a good default.

Tool Calling

Kimi-K2-Instruct has strong tool-calling capabilities.
To enable them, you need to pass the list of available tools in each request, then the model will autonomously decide when and how to invoke them.

The following example demonstrates calling a weather tool end-to-end:

# Your tool implementation
def get_weather(city: str) -> dict:
    return {"weather": "Sunny"}

Tool schema definition
tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Retrieve current weather information. Call this when the user asks about the weather.",
        "parameters": {
            "type": "object",
            "required": ["city"],
            "properties": {
                "city": {
                    "type": "string",
                    "description": "Name of the city"
                }
            }
        }
    }
}]

Map tool names to their implementations
tool_map = {
    "getweather": getweather
}

def toolcallwithclient(client: OpenAI, modelname: str):
    messages = [
        {"role": "system", "content": "You are Kimi, an AI assistant created by Moonshot AI."},
        {"role": "user", "content": "What's the weather like in Beijing today? Use the tool to check."}
    ]
    finish_reason = None
    while finishreason is None or finishreason == "tool_calls":
        completion = client.chat.completions.create(
            model=model_name,
            messages=messages,
            temperature=0.6,
            tools=tools,          # tool list defined above
            tool_choice="auto"
        )
        choice = completion.choices[0]
        finishreason = choice.finishreason
        if finishreason == "toolcalls":
            messages.append(choice.message)
            for toolcall in choice.message.toolcalls:
                toolcallname = tool_call.function.name
                toolcallarguments = json.loads(tool_call.function.arguments)
                toolfunction = toolmap[toolcallname]
                toolresult = toolfunction(toolcallarguments)
                print("toolresult:", toolresult)

messages.append({
                    "role": "tool",
                    "toolcallid": tool_call.id,
                    "name": toolcallname,
                    "content": json.dumps(tool_result)
                })
    print("-" * 100)
    print(choice.message.content)

The toolcallwith_client function implements the pipeline from user query to tool execution.
This pipeline requires the inference engine to support Kimi-K2’s native tool-parsing logic.
For streaming output and manual tool-parsing, see the Tool Calling Guide.

6. License

Both the code repository and the model weights are released under the Modified MIT License.

7. Third Party Notices

See THIRD PARTY NOTICES

7. Contact Us

If you have any questions, please reach out at [email protected].