Hugging Face Launches APAC Inference Endpoints in Singapore and Tokyo for Open-Source Model Deployment

Hugging Face has launched managed inference endpoints in Singapore and Tokyo data centres, enabling APAC enterprises to deploy open-source language models with in-region data residency and without managing GPU infrastructure. The service supports leading open-source models including Meta Llama, Mistral, Alibaba Qwen, and Google Gemma — giving APAC enterprises access to best-in-class open-weights models through a managed API similar in interface to proprietary model APIs like OpenAI or Anthropic.

The APAC regional launch is significant for two groups of enterprises. For organisations with data residency requirements — financial institutions in Singapore and Japan, healthcare providers, government agencies — in-region inference means sensitive data never leaves the jurisdiction. For enterprises with limited ML engineering capacity, the managed endpoint removes the need to manage GPU clusters, model serving infrastructure, and scaling — enabling adoption of open-source models without a dedicated MLOps team. APAC AI teams should evaluate Hugging Face Inference Endpoints as a path to open-source model deployment that combines the cost and customisation benefits of open weights with the operational simplicity of managed API access.