Kimi K2 Thinking API

Deploy Moonshot's premier reasoning model. Kimi K2 Thinking combines a 128K context window with Chain of Thought (CoT) capabilities to solve complex problems, executing reliable tool calls and web searches at a fraction of the cost.

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Kimi K2 Thinking API — Depth, Stability, and Context

Build powerful AI agents with the Kimi K2 Thinking API. Handle 128K token inputs, orchestrate complex multi-step workflows, and leverage deep reasoning for data-heavy tasks.

What can you build with Kimi K2 Thinking?

Deep Research Agents

Synthesize vast datasets. The Kimi K2 Thinking API processes 128K tokens to generate cited, analytical reports from massive documents.

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Autonomous Workflows

Create agents that don't drift. Kimi K2 excels at sequential decision-making, utilizing JSON schemas and function calls reliably.

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Complex STEM Reasoning

Solve hard problems. Use the Kimi K2 Thinking API for advanced math derivation, code refactoring, and logic puzzles with safety checks.

Test reasoning

Why developers choose Kimi K2 Thinking API

Achieve the perfect balance of reasoning depth, massive context, and operational efficiency without breaking your budget.

Uncompromised Context

Process up to 128K tokens in a single pass, ideal for full codebase analysis or novel-length context.

Agentic Native

Designed for action. The model seamlessly connects reasoning with external tools and live web search.

Ultra-Low API Cost

Drastically cut expenses with rates ~ $0.00056/1K input. High intelligence doesn't have to be expensive.

How to integrate Kimi K2 Thinking API

Three steps to add deep reasoning capabilities to your application.

Step 1 — Ingest Data

Send up to 128K tokens of context. The Kimi K2 Thinking API handles heavy retrieval augmented generation (RAG) payloads with ease.

Step 2 — Configure Tools

Define your function schemas or enable the built-in web search tool to let the model fetch real-time information.

Step 3 — Execute & Reason

Receive structured, reasoned responses. Use the Chain of Thought output to audit the model's logic before showing the final result.

View API Docs

Kimi K2 Thinking Capabilities

Engineered for high-performance reasoning tasks

Capacity

128K Token Window

Analyze lengthy transcripts, legal contracts, or repositories.

Integration

Native Tool Use

Kimi K2 Thinking API reliably triggers functions and search.

Pricing

Budget Friendly

Access elite reasoning at ~$0.00056/1K input via EvoLink.

Language

Bilingual Mastery

Top-tier nuances in both English and Chinese contexts.

Safety

CoT Safety

Transparent reasoning steps with built-in safety filters.

Reliability

Agent Stability

Maintains logic over long, multi-turn conversations.

Kimi K2 Thinking vs. Competitors

Why Kimi K2 is the smart choice for cost-effective reasoning

Model	Duration	Resolution	Price	Strength
Kimi K2 Thinking	N/A	Reasoning	~$0.00056 in / $0.00224 out	128K context, web search, lowest cost for reasoning.
Gemini 2.5 Pro	N/A	Standard	$0.00125 in / $0.01 out (list)	High reasoning ceiling, larger context (1M).
Claude 3.5 Sonnet	N/A	Standard	Mid-tier	Excellent coding, smaller context effective window.

Frequently Asked Questions about Kimi K2 Thinking

Everything you need to know about the product and billing.

Pricing is highly competitive via EvoLink, listing at approximately $0.00056 per 1K input tokens and $0.00224 per 1K output tokens, making it affordable for high-volume tasks.

The Kimi K2 Thinking model uses a Chain of Thought (CoT) process to break down complex queries into logical steps before generating a final answer, ensuring higher accuracy for math and coding.

The model supports a massive context window of up to 128K tokens, allowing you to process large documents or extensive conversation histories in one API call.

Yes, it supports optional web search integration. You can configure the API to fetch live data from the internet when the model detects it needs current information.

Absolutely. With its 128K context and strong reasoning capabilities, Kimi K2 Thinking excels at understanding codebases, debugging, and refactoring via function calls.

You can access the model immediately through the EvoLink unified API platform, which provides optimized routing and simple key management.

Yes, typically the API provides options to view the 'thought' process, allowing developers to debug the agent's logic transparency.