Kimi K2 Thinking Turbo API

Experience the speed of Kimi K2 Thinking Turbo. A Moonshot AI model optimized for latency-sensitive applications requiring deep reasoning, 128K context, and live web search capabilities.

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Kimi K2 Thinking Turbo API — Faster reasoning, reduced costs

Scale your production agents with the Kimi K2 Thinking Turbo API. Achieve complex chain-of-thought capabilities and 128K context retention with significantly lower latency than standard reasoning models.

What can the Kimi K2 Thinking Turbo API do?

High-Speed RAG & Q&A

Process extensive datasets with the Kimi K2 Thinking Turbo API. It handles 128K tokens to deliver grounded answers from your documents with minimal wait time.

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Autonomous Agent Workflows

Power reliable agents using Kimi K2 Thinking Turbo API's deterministic function calling. Perfect for multi-step tasks requiring logic and external tool orchestration.

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Cost-Efficient Analytics

Run high-volume classification and logic tasks. The Kimi K2 Thinking Turbo API offers a budget-friendly alternative for batch processing large-scale logic jobs.

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Why developers choose Kimi K2 Thinking Turbo API

The Kimi K2 Thinking Turbo API bridges the gap between deep reasoning intelligence and production-grade speed, ensuring your users don't wait for answers.

Production-Grade Latency

Designed for real-time interactions, offering faster inference than the standard K2 Thinking model.

Advanced Tooling Ecosystem

Seamlessly integrates with search tools and custom APIs via robust JSON schema support.

Global Language Support

Excellent bilingual performance in English and Chinese, powered by Moonshot AI's MoE architecture.

How to integrate Kimi K2 Thinking Turbo API

Three simple steps to deploy fast, reasoning-capable AI agents.

Step 1 — Authenticate & Contextualize

Initialize the Kimi K2 Thinking Turbo API client and load up to 128K tokens of system prompts or documents.

Step 2 — Define Tools

Map your functions or enable the built-in web search capability to give the model real-time agency.

Step 3 — Execute & Scale

Send requests to the Turbo endpoint. Parse the JSON structured reasoning and tool calls for your application.

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Kimi K2 Thinking Turbo API Capabilities

Engineered for speed, built for reasoning

Capacity

128K Context Window

Ingest entire codebases or long reports effortlessly with the Kimi K2 Thinking Turbo API.

Performance

Turbo-Charged Speed

Optimized routing ensures rapid response generation for interactive apps.

Tools

Function Calling

Deterministic tool use allows the API to trigger external actions reliably.

Connectivity

Web Search Enabled

Optionally connect the model to the internet for fresh, real-time data retrieval.

Intelligence

Chain-of-Thought (CoT)

Deep reasoning capabilities with safety filters, now faster than ever.

Value

Economical Pricing

Lower cost-per-token compared to the standard K2 Thinking model.

Kimi K2 Thinking Turbo API vs. Alternatives

Compare performance, cost, and reasoning capabilities

Model	Duration	Resolution	Price	Strength
Kimi K2 Thinking Turbo API	N/A	Best for Speed/Reasoning Mix	Lowest (Turbo Rate)	Fast inference, 128K context, native tool use.
Kimi K2 Thinking (Standard)	N/A	Best for Deep Research	~$0.00056 in / $0.00224 out	Maximum reasoning depth; higher latency.
Competitor Flash Models	N/A	General Purpose	Varies (e.g., $0.0003 in)	Often cheaper but may lack specific CoT optimization.

Kimi K2 Thinking Turbo API - FAQ

Everything you need to know about the product and billing.

The Kimi K2 Thinking Turbo API is optimized for latency and cost. While the standard K2 Thinking focuses on maximum reasoning depth for the most complex problems, the Turbo variant delivers comparable reasoning quality much faster, making it better suited for user-facing applications.

Pricing is token-based and designed to be more affordable than the standard list price (approx. $0.00056/in), allowing for cost-effective scaling in production environments.

Yes, the API fully supports streaming responses, which is critical for maintaining a responsive user experience (low TTFT) in chat interfaces.

Absolutely. With its 128K context window and strong logic capabilities, it excels at analyzing code repositories and debugging complex scripts via tool definitions.

Yes, Moonshot AI typically ensures their APIs, including Kimi K2 Thinking Turbo, are compatible with common OpenAI-format SDKs for easy integration.

Web search is available as a built-in tool. You can enable it in your API request payload when you need the model to ground its reasoning in up-to-date internet data.