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Moonshot AI's Kimi K3 Launches on Amazon Bedrock

Moonshot AI's open-weight Kimi K3 model is now available on Amazon Bedrock, featuring native vision and a 1-million-token context window for coding and knowledge tasks.

This article was AI-generated and published automatically. Context, labelling and all sources at the end of the article.

(KI-generiertes Symbolbild: Gemini / AI Connect)

Moonshot AI has made its Kimi K3 model available through Amazon Bedrock. The platform addition introduces an open-weight alternative tailored specifically for coding and knowledge work. This integration expands the selection of models accessible directly within the Bedrock service for developers handling complex digital tasks.

The newly introduced model features native vision capabilities alongside an extensive 1-million-token context window. In addition to processing large inputs, Kimi K3 supports explicit prompt caching. This technical feature is designed to reduce latency while cutting down input costs for end users.

What this means for you

The availability of Kimi K3 on Amazon Bedrock delivers an open-weight foundation for teams managing coding projects and knowledge work. Its 1-million-token context window and native vision accommodate substantial multimodal datasets. Furthermore, utilizing explicit prompt caching helps organizations systematically lower input costs and improve response latency.

Evidence

Solidly sourced
46/100

  • Moonshot AI has made Kimi K3 available on Amazon Bedrock.

    single source
    Quote

    „Kimi K3 from Moonshot AI is now available on Amazon Bedrock“

    AWS, Machine Learning

  • Kimi K3 is an open-weight model designed for coding and knowledge work.

    single source
    Quote

    „giving you a powerful new open-weight option for coding and knowledge work.“

    AWS, Machine Learning

  • The model features native vision capabilities and a 1-million-token context window.

    single source
    Quote

    „It offers native vision, a 1-million-token context window“

    AWS, Machine Learning

  • Kimi K3 provides explicit prompt caching to lower latency and input expenses.

    single source
    Quote

    „explicit prompt caching to reduce latency and input costs.“

    AWS, Machine Learning

Sources

The evidence score is computed, not hand-set: from confidence, the number of sources and the share of verified statements.

Source & transparency

As of: September 18, 2026

AI-generatedAI-generated: produced automatically from vetted sources with technical quality checks (source, quote and figure verification); no human sign-off of each item before publication

Sources
1
Verified statements
0 / 4
Evidence score
46Solidly sourced
Generative AIUse Cases

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