Amazon Bedrock adds in-country inference in India for Kimi K3, keeping processing within the Mumbai and Hyderabad Regions
Moonshot AI's open-weight model gets a data-residency option on Bedrock alongside the existing global and US-based inference.
// Key points
- Kimi K3 is offered through cross-Region inference profiles: global.moonshotai.kimi-k3 is recommended for most use cases as the lowest-cost and most broadly available; in.moonshotai.kimi-k3 keeps processing within Mumbai and Hyderabad
- AWS recommends the OpenAI-compatible APIs for this model, and its example connects through the openai Python library
- The walkthrough reads a scanned Hindi document, extracts structured data and answers follow-up questions in Hinglish, with no separate OCR or translation service
- Customer Ultrahuman says its assistant handles more than 14,000 conversations a day on Kimi K3, and that prompt caching cut its LLM costs by 80% and made multi-turn chats 85% faster
Builder's takeThe pattern matters more than India: open-weight models are getting region-pinned profiles on the big clouds, which is the first thing regulated customers ask for. If you serve markets with residency rules, set the geographic profile explicitly in config instead of relying on the global default, and check that your SCPs allow both destination Regions, or calls will fail in ways that look like model errors.
// Background · from #Open models
Full timeline →- Nov 3 AWS distills a GLM-5.3 shopping agent into Qwen3.5-4B: held-out success rises from 0.297 to 0.541, level with the teacher
- Nov 3 NVIDIA extends the open Cosmos Framework to GR00T, Qwen and pi0.5 models and publishes Cosmos 3 Nano simulation checkpoints
- Nov 2 NVIDIA introduces NemoClaw open blueprints: OpenClaw, Hermes Agent or LangChain Deep Agents paired with Nemotron models and the OpenShell runtime