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Favicon de Moonshot AI

Moonshot AI

Explore los modelos ofrecidos por Moonshot AI (Términos del servicio)

4 modelos

Tókenes procesados en OpenRouter

  • Favicon de moonshotai
    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.

    por moonshotai23 oct 20261,05M de contexto2 US$/M entrada tokens10 US$/M salida tokens
  • Favicon de moonshotai
    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.

    por moonshotai16 jul 20261,05M de contexto3 US$/M entrada tokens15 US$/M salida tokens
  • Favicon de moonshotai
    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.

    por moonshotai12 jun 2026262K de contexto0,95 US$/M entrada tokens4 US$/M salida tokens
  • Favicon de moonshotai
    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.

    por moonshotai20 abr 2026262K de contexto0,95 US$/M entrada tokens4 US$/M salida tokens