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Moonshot AI의 파비콘

Moonshot AI

다음 제공업체의 모델 둘러보기: Moonshot AI (서비스 약관)

4 모델

OpenRouter에서 처리된 토큰

  • moonshotai의 파비콘
    MoonshotAI: Kimi K3.1 ProKimi K3.1 Pro

    Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model and a post-trained successor to Kimi K3, with a 1M-token context window. It is built for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, with native image and video understanding.

    제작: moonshotai2026년 10월 23일1.05M 컨텍스트US$2/M 입력 토큰US$10/M 출력 토큰
  • moonshotai의 파비콘
    MoonshotAI: Kimi K3Kimi K3

    Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at navigating large repositories, using tools, debugging, and iterating against images, logs, tests, and runtime feedback. Its architecture uses KDA and Attention Residuals for computational efficiency.

    제작: moonshotai2026년 7월 16일1.05M 컨텍스트US$3/M 입력 토큰US$15/M 출력 토큰
  • moonshotai의 파비콘
    MoonshotAI: Kimi K2.7 CodeKimi K2.7 Code

    MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts architecture that accepts text and image input, and it always operates in a thinking mode, preserving full reasoning content across multi-turn conversations. With a 256K-token context window, it targets long-horizon coding, agentic task decomposition, and multi-turn dialogue. The model activates 32B parameters out of roughly 1T total.

    제작: moonshotai2026년 6월 12일262K 컨텍스트US$0.95/M 입력 토큰US$4/M 출력 토큰
  • moonshotai의 파비콘
    MoonshotAI: Kimi K2.6Kimi K2.6

    Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture scales to hundreds of parallel sub-agents for autonomous task decomposition - delivering documents, websites, and spreadsheets in a single run without human oversight.

    제작: moonshotai2026년 4월 20일262K 컨텍스트US$0.95/M 입력 토큰US$4/M 출력 토큰