Moonshot AI

kimi-k3:cloud

Token-based pricing

Kimi K3 is an open-weight, native multimodal agentic model and Moonshot's most capable model to date. It is a 2.8T-parameter model built on Kimi Delta Attention (KDA) and Attention Residuals (AttnRes), with native vision capabilities and a 1-million-token context window. It is the world's first open 3T-class model.

visiontoolsthinkingcloudCommunity r/kimi

Context window1M

ModalitiesText, Image

Size2.81T

Pulls61.8K

Tags1

Updated1 month ago

ollama run kimi-k3:cloud

Key features

New architecture — Kimi Delta Attention (KDA) and Attention Residuals (AttnRes), with a Stable LatentMoE framework that activates 16 of 896 experts — roughly 2.5× better scaling efficiency than Kimi K2.
Long-horizon coding — sustains long engineering sessions, navigates massive repositories, and orchestrates terminal tools, from GPU kernel optimization and compiler development to vision-in-the-loop game dev, CAD, and chip design.
Agentic knowledge work — produces deep research with interactive visualizations, widgets and dashboards, plus motion design and video editing, powered by native multimodality.
Native multimodality & long context — understands text, images, and video within the same model, with a 1M-token context window.
Open frontier weights — full weights released under the Kimi K3 License.

Best practices

Long-horizon sessions — designed to operate with minimal human oversight across massive repositories and hundreds of tool calls.
Multimodal inputs — combine text, image, and video in one request; the same model handles all three natively.
Pricing — token-based billing on Ollama Cloud.

Specs sourced from ollama.com/library/kimi-k3 · Retrieved 2026-08-29