---
title: "Kimi K2 Thinking for OpenClaw: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using Kimi K2 Thinking with OpenClaw. Costs $0.47/M input, $2.00/M output. 131K context window. Here's when to use it and when to pick something else."
date: 2026-03-12
updatedDate: 2026-03-12
image: /images/models/provider-moonshotai-hero.jpg
keywords: "kimi k2 thinking openclaw, kimi k2 thinking pricing, kimi k2 thinking review, moonshot ai openclaw, kimi k2 thinking api"
category: model-guide
modelData:
  provider: "Moonshot AI"
  provider_slug: "moonshotai"
  full_id: "moonshotai/kimi-k2-thinking"
  input_cost_per_1m: 0.47
  output_cost_per_1m: 2
  max_input_tokens: 131072
  max_output_tokens: 65536
  features: ["function_calling", "reasoning"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What is the pricing for Kimi K2 Thinking?"
    answer: "It costs $0.47 per million input tokens and $2 per million output tokens."
  - question: "What is the context limit?"
    answer: "The model supports a 131K token context window, which is sufficient for most large-scale RAG or agent tasks."
---

Current as of March 2026. Kimi K2 Thinking is Moonshot AI's reasoning-heavy model that positions itself as a budget-friendly alternative to O1-preview for long-context tasks. At $0.47 per million input tokens, it offers a 131K window that holds up well during complex agentic workflows in OpenClaw.

## Specs

| | |
|---|---|
| **Provider** | Moonshot AI |
| **Input cost** | $0.47 / M tokens |
| **Output cost** | $2.00 / M tokens |
| **Context window** | 131K tokens |
| **Max output** | N/A tokens |
| **Parameters** | N/A |
| **Features** | function_calling, reasoning |

## What it's good at

#### Deep Logic

The reasoning feature allows it to tackle multi-step problems that usually trip up standard LLMs at this price point.

#### Context Stability

It manages the 131K token window effectively, showing less 'middle-of-the-prompt' forgetfulness than many competitors in the same tier.

## Where it falls short

#### Slow Inference

The thinking phase adds significant latency, making it unsuitable for applications requiring instant feedback.

#### Regional Latency

API calls to api.moonshot.cn can be inconsistent for users outside of mainland China or Southeast Asia.

## Best use cases with OpenClaw

- **Complex Debugging** — Use this when your OpenClaw agent needs to analyze a large stack trace against a wide context of source code within its 131K window.
- **Logic-Heavy Planning** — It's ideal for agents that must generate a detailed execution plan before calling external tools or functions.

## Not ideal for

- **Simple UI Text** — The $2 per million output cost is a waste on basic copy generation or greeting users that doesn't require reasoning.
- **Latency-Sensitive Tools** — Avoid this for any interactive tool where the user expects a response in under 500ms due to the model's 'thinking' overhead.

## OpenClaw setup

Configure a custom provider in OpenClaw using the base URL https://api.moonshot.cn/v1 and the model ID moonshotai/kimi-k2-thinking.

```json
{
  "models": {
    "mode": "merge",
    "providers": {
      "moonshotai": {
        "baseUrl": "https://api.moonshot.cn/v1",
        "apiKey": "YOUR-MOONSHOT-AI-API-KEY",
        "api": "openai-completions",
        "models": [
          {
            "id": "kimi-k2-thinking",
            "name": "Kimi K2 Thinking",
            "cost": {
              "input": 0.47,
              "output": 2
            },
            "contextWindow": 131072,
            "maxTokens": null
          }
        ]
      }
    }
  }
}
```

## How it compares

- **vs DeepSeek-V3** — DeepSeek is often cheaper on output, but Kimi's 131K context window feels more robust for long-form reasoning tasks.
- **vs GPT-4o-mini** — GPT-4o-mini is significantly faster for basic tasks, but it lacks the specialized reasoning architecture that Kimi K2 uses for hard problems.

## Bottom line

If you need O1-style reasoning with a large context window but only have a fraction of the budget, Kimi K2 Thinking is the best option for your OpenClaw agents.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=kimi-k2-thinking-openclaw" class="cta-button">TRY KIMI K2 THINKING ON HAIMAKER</a>

---

*For setup instructions, see our [API key guide](/blog/openclaw-api-key-setup). For all available models, see the [complete models guide](/blog/best-models-for-openclaw).*