Skip to main content
Moonshot’s Kimi family of models handles advanced reasoning and chat. It supports extended thinking with a visible reasoning trace before the final answer. A single endpoint serves three variants, each selected by setting the model field in the request body.

Try in playground

Test Moonshot Kimi in the Runpod Hub playground.
This endpoint is fully compatible with the OpenAI API. See the OpenAI compatibility examples below.

Model variants

Choose a variant by setting the model field in the request body (default kimi-k2.6). The endpoint slug stays moonshot-kimi for every variant. To target a variant other than the default, set the model field to its ID. For example, to use the flagship model, set "model": "kimi-k3" in the request body (or model="kimi-k3" with the OpenAI SDK).

Request

All parameters are passed within the input object in the request body.
array
required
Array of message objects with role and content.
string
required
The role of the message author. Use system, user, or assistant.
string
required
The content of the message.
string
default:"kimi-k2.6"
The Kimi variant to use. One of kimi-k2.6, kimi-k2.7-code, or kimi-k3.
integer
default:"2048"
Maximum number of tokens to generate. On the native route (/run and /runsync), this must be set at the top level of input. This cap counts reasoning tokens as well as visible output tokens.
string
default:"max"
Controls how much reasoning the model performs before answering. One of low, high, or max. Specific to the kimi-k3 variant.
float
default:"1"
Controls randomness in generation. Lower values make output more deterministic.
integer
Seed for reproducible results.
integer
Restricts sampling to the top K most probable tokens.
float
Nucleus sampling threshold. Range: 0.0-1.0.
Sampling parameters such as max_tokens must sit at the top level of the input object on the native route. Nesting them inside a sampling_params object has no effect: the values are ignored, and generation continues until the model stops on its own. Check finish_reason in the response ("length" means the max_tokens cap was reached, "stop" means the model finished on its own) to confirm the cap took effect.

Response

string
Unique identifier for the request.
string
Request status. Returns COMPLETED on success, FAILED on error.
integer
Time in milliseconds the request spent in queue before processing began.
integer
Time in milliseconds the model took to generate the response.
string
Identifier of the worker that processed the request.
array
Array of result objects. Each element contains the cost and the generated chat completion.
float
Cost of the generation in USD.
object
The chat completion. Contains choices, usage, and metadata (id, object, model, created).
array
Generated choices. Each has an index, a finish_reason ("stop" or "length"), and a message with role, content, and, for reasoning variants such as kimi-k3, reasoning_content.
object
Token usage: prompt_tokens, completion_tokens, total_tokens, completion_tokens_details (including reasoning_tokens), prompt_tokens_details (including cached_tokens), and a top-level cached_tokens count. The completion_tokens count includes reasoning tokens.

OpenAI API compatibility

Moonshot Kimi is fully compatible with the OpenAI API format. You can use the OpenAI Python client to interact with this endpoint. You can set model to any of the three variant IDs.
Python (OpenAI SDK)
For streaming responses, add stream=True:
Python (Streaming)
For more details, see Send vLLM requests and the OpenAI API compatibility guide.

Cost calculation

Moonshot Kimi charges separate rates for input and output tokens, and the rate depends on the variant. Kimi K2.6 and Kimi K2.7 Code charge $0.95 per 1M input tokens and $4.00 per 1M output tokens. Kimi K3 charges $3.00 per 1M input tokens and $15.00 per 1M output tokens. Example costs:
Last modified on September 16, 2026