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Kimi K2 Thinking Turbo

Kimi K2 Thinking Turbo is Moonshot AI's user-facing reasoning model. It delivers chain-of-thought thinking at turbo-speed latency for interactive products where deliberation quality and response time both shape the experience.

ReasoningTool UseImplicit Caching
index.ts
import { streamText } from 'ai'


const result = streamText({
  model: 'moonshotai/kimi-k2-thinking-turbo',
  prompt: 'Why is the sky blue?'
})
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Frequently Asked Questions

  • How does compressed thinking in Turbo differ from the full Thinking model?

    Thinking Turbo runs the same reasoning mechanism under a tighter budget. Standard Kimi K2 Thinking allocates a larger deliberation budget per request and produces longer traces. For hard tasks, use full Thinking; for many interactive cases, Thinking Turbo is enough.

  • Does Kimi K2 Thinking Turbo support tool use alongside reasoning?

    Yes. Tool calls and reasoning steps can interleave. The model can reason about a result, call a tool, reason about the response, and continue. This pipeline runs at turbo latency rather than full thinking-mode latency.

  • When should I use Thinking Turbo vs standard K2 Turbo?

    Use Thinking Turbo when the task benefits from deliberation and you have user-facing latency constraints. Use standard K2 Turbo when reasoning adds overhead without improving output quality for the specific task.

  • What context window does Kimi K2 Thinking Turbo support?

    262.1K tokens, consistent with the K2 family.

  • How does Kimi K2 Thinking Turbo handle very complex mathematical or logical problems?

    It fits moderate-complexity problems. For frontier reasoning difficulty, Kimi K2 Thinking with the full deliberation budget is the better fit.

  • How do I use Kimi K2 Thinking Turbo on AI Gateway?

    Use the identifier moonshotai/kimi-k2-thinking-turbo with any supported interface. AI Gateway handles provider routing automatically.