Amazon Bedrock Adds India-Based Inference for Kimi K3
Amazon Web Services announced that Amazon Bedrock now supports in-country inference for Kimi K3 through an India geographic profile, restricting processing to the Mumbai and Hyderabad Regions. The model remains available through global and US-based cross-Region inference profiles, with AWS saying requests can originate from a wide range of source Regions. AWS also described multimodal support for images, PDFs, tool calling, structured outputs, and prompt caching for Indic-language document workflows.
The India-specific profile gives Bedrock customers an option for deploying Kimi K3 while keeping inference within Indian Regions for data-residency-sensitive workloads.
Kimi K3 is a multi-modal, open-weight foundation model (FM) that provider Moonshot AI reported achieved frontier-level coding and general agentic intelligence at release.
In addition to global and US-based inference, Amazon Bedrock now supports in-country inference in India for Kimi K3: unblocking local workloads with strict data residency requirements. Customers like Ultrahuman are already seeing the benefits in production:
“Jade, an AI Health and Wellness assistant in the Ultrahuman app, answers questions in plain language using each person’s own Ring and glucose data, across more than 14,000 conversations a day. Kimi K3 on Amazon Bedrock let us add a leading open-weight model through the API we already use, with health data staying inside AWS and Mumbai as a fallback Region. With prompt caching, we’ve cut LLM costs by 80 percent and made multi-turn chats 85 percent faster.” — Aditya Patawari, VP Engineering, Ultrahuman
In this post, we explain the different global and geographic inference options available, and share code for an example use case: optical character recognition (OCR) and understanding of Indic-language documents, with follow-up question answering in code-mixed Hinglish.
#Kimi K3#Amazon Bedrock#Amazon Web Services#Moonshot AI#Ultrahuman#Jade