Key Features

Provides a 2.8T-parameter multimodal model with native vision capabilities.
Supports a 1-million-token context window for long documents, repositories, and research traces.
Uses Kimi Delta Attention and Attention Residuals to improve long-context information flow.
Activates sparse Mixture-of-Experts capacity through Stable LatentMoE routing.
Targets long-horizon coding, GPU kernel optimization, compiler development, and visual software tasks.
Works through Kimi.com, Kimi Work, Kimi Code, and the Kimi API platform.
Supports agentic knowledge work such as interactive reports, dashboards, spreadsheets, and presentations.
Uses quantization-aware training and deployment guidance for large-scale inference efficiency.

The model combines Kimi Delta Attention, Attention Residuals, Stable LatentMoE sparsity, and quantization-aware training to improve scaling efficiency and inference practicality. Kimi reports that K3 can sustain long engineering sessions, optimize GPU kernels, build compiler components, reason over screenshots, generate interactive artifacts, and handle research workflows that require many tool calls and large context windows.


Kimi K3 is useful for developers and knowledge workers who want a high-capacity assistant across coding, research, slides, spreadsheets, dashboards, and video-oriented creative tasks. It is available through Kimi apps, Kimi Work, Kimi Code, and the Kimi API, with API pricing listed for input and output tokens while broader open-weight release details are staged separately.

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