AI Tools Review

MoonshotAI: Kimi K2 Thinking

By Moonshotai

Released: 2025-11-06

API
LLM
RAG
Moonshotai
Paid
New

Moonshotai Kimi K2 Thinking features MoE architecture and 262k-token context window. Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in Kimi K2, it activates 32 billion parameters per forward pass and supports 256 k-token context windows. The model is optimised for persistent step-by-step thought, dynamic tool invocation, and complex reasoning workflows that span hundreds of turns. It interleaves step-by-step reasoning with tool use, enabling autonomous research, coding, and writing that can persist for hundreds of sequential actions without drift. It sets new open-source benchmarks on HLE, BrowseComp, SWE-Multilingual, and LiveCodeBench, while maintaining stable multi-agent behaviour through 200–300 tool calls. Built on a large-scale MoE architecture with MuonClip optimization, it combines strong reasoning depth with high inference efficiency for demanding agentic and analytical tasks. Available at $0.4/1M tokens.

Visit MoonshotAI: Kimi K2 Thinking

AI-Powered

Leverages advanced AI technology to deliver cutting-edge capabilities and results.

Fast & Efficient

Optimized performance ensures quick results without compromising on quality.

Purpose-Built

Specifically designed for llms tasks and workflows.

Moonshotai Model Timeline

MoonshotAI: Kimi K2 ThinkingCurrent

262k tokens context

MoonshotAI: Kimi K2 0905

262k tokens context

MoonshotAI: Kimi K2 0905 (exacto)

262k tokens context

MoonshotAI: Kimi K2 0711 (free)

33k tokens context

MoonshotAI: Kimi K2 0711

131k tokens context

MoonshotAI: Kimi Dev 72B

131k tokens context

Specifications

pricing$0.40 / $1.75 (per 1M)
context Window262k tokens

AI Evaluation

4.8
Expert Rating
Text4.9/5
Coding3.5/5

Combines language understanding with search capabilities. Excels at finding and synthesizing information from various sources.

Pros

  • 262k token context window
  • Strong code generation and debugging
  • Advanced logical reasoning
  • Agent-ready with tool use

Cons

  • May lack creative flair
  • API integration required