> ## Documentation Index
> Fetch the complete documentation index at: https://platform.kimi.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Generation Model Kimi K2 Pricing

export const DocTable = ({columns = [], rows = []}) => {
  return <div className="doc-table-wrap">
      <table className="doc-table">
        {columns.length > 0 ? <colgroup>
            {columns.map((column, index) => <col key={index} style={column.width ? {
    width: column.width
  } : undefined} />)}
          </colgroup> : null}
        <thead>
          <tr>
            {columns.map((column, index) => <th key={index}>{column.title}</th>)}
          </tr>
        </thead>
        <tbody>
          {rows.map((row, rowIndex) => <tr key={rowIndex}>
              {row.map((cell, cellIndex) => <td key={cellIndex}>{cell}</td>)}
            </tr>)}
        </tbody>
      </table>
    </div>;
};

## Product Pricing

**Explanation: Prices exclude applicable taxes. Specific tax obligations are subject to local tax regulations and will be calculated at checkout based on your jurisdiction.**

<DocTable
  columns={[
{ title: "Model", width: "24%" },
{ title: "Unit", width: "12%" },
{ title: "Input Price (Cache Hit)", width: "16%" },
{ title: "Input Price (Cache Miss)", width: "16%" },
{ title: "Output Price", width: "14%" },
{ title: "Context Window", width: "18%" },
]}
  rows={[
["kimi-k2-0905-preview", "1M tokens", <>{"$"}0.15</>, <>{"$"}0.60</>, <>{"$"}2.50</>, "262,144 tokens"],
["kimi-k2-0711-preview", "1M tokens", <>{"$"}0.15</>, <>{"$"}0.60</>, <>{"$"}2.50</>, "131,072 tokens"],
["kimi-k2-turbo-preview", "1M tokens", <>{"$"}0.15</>, <>{"$"}1.15</>, <>{"$"}8.00</>, "262,144 tokens"],
["kimi-k2-thinking", "1M tokens", <>{"$"}0.15</>, <>{"$"}0.60</>, <>{"$"}2.50</>, "262,144 tokens"],
["kimi-k2-thinking-turbo", "1M tokens", <>{"$"}0.15</>, <>{"$"}1.15</>, <>{"$"}8.00</>, "262,144 tokens"],
]}
/>

Here, 1M = 1,000,000. The prices in the table represent the cost per 1M tokens consumed.

> `kimi-k2` series models will be officially discontinued on **May 25, 2026** and will no longer be maintained or supported. Please use the latest Kimi model [kimi-k2.6](/guide/kimi-k2-6-quickstart) for continued support and enhanced reasoning capabilities.

## Model Description

* Kimi K2 is a Mixture-of-Experts (MoE) foundation model with exceptional coding and agent capabilities, featuring 1 trillion total parameters and 32 billion activated parameters. In benchmark evaluations covering general knowledge reasoning, programming, mathematics, and agent-related tasks, the K2 model outperforms other leading open-source models
* kimi-k2-0905-preview: Context length 256k. Based on kimi-k2-0711-preview, with enhanced agentic coding abilities, improved frontend code quality and practicality, and better context understanding
* kimi-k2-turbo-preview: Context length 256k. High-speed version of Kimi K2, always aligned with the Kimi K2 (kimi-k2-0905-preview). Same model parameters as Kimi K2, output speed up to 60 tokens/sec (max 100 tokens/sec)
* kimi-k2-0711-preview: Context length 128k
* kimi-k2-thinking: Context length 256k. A thinking model with general agentic and reasoning capabilities, specializing in deep reasoning tasks [Usage Notes](/guide/use-kimi-k2-thinking-model)
* kimi-k2-thinking-turbo: Context length 256k. High-speed version of kimi-k2-thinking, suitable for scenarios requiring both deep reasoning and extremely fast responses
* Supports ToolCalls, JSON Mode, Partial Mode, and internet search functionality
* Does not support vision functionality
* Supports automatic context caching functionality. Cached tokens are charged at the input price (cache hit) rate. You can view "context caching" type cost details in the [console](https://platform.kimi.ai/console)