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NVIDIA B300 GPUs are now available for reservation in India for February 2027 deployment, with local currency billing and data hosting.

Utho Cloud, an Indian cloud provider, has opened reservations for NVIDIA B300 GPUs, slated for deployment in February 2027. These GPUs, based on the Blackwell Ultra architecture, feature 288GB of HBM3e memory and are designed for demanding AI workloads like large language model training and inference. Utho Cloud is offering committed computing capacity with rupee-based billing and India-hosted infrastructure for one, two, or three-year reservation terms. This move aims to provide Indian AI companies and enterprises with reliable access to advanced computing, helping them plan infrastructure costs and meet data residency requirements. The company plans to invest in and deploy a total of 10,000 GPUs, though specific numbers for the B300s and deployment timelines beyond the initial February 2027 date for reservations remain undisclosed. Utho Cloud currently serves over 51,000 customers, including 3,500 B2B clients.

Utho Cloud's early reservation offering of NVIDIA B300 GPUs signifies a growing demand for cutting-edge AI hardware within India's rapidly expanding tech ecosystem. By providing rupee-based billing and local data hosting, the company directly addresses key concerns for Indian businesses regarding cost predictability and data sovereignty. This move aims to democratize access to high-performance computing, enabling local enterprises and startups to compete more effectively on a global scale without being hampered by foreign exchange volatility or complex cross-border data regulations.

The availability of these advanced GPUs, particularly the NVIDIA B300 with its substantial memory and processing power, suggests a significant uptick in large-scale AI model training and inference projects within India. Utho Cloud's strategy of offering long-term capacity commitments and engineering support positions them as a crucial enabler for businesses looking to build and deploy sophisticated AI applications. The company's significant investment in GPU infrastructure, totaling 10,000 GPUs, indicates a broader market trend toward dedicated, localized AI compute resources becoming essential for innovation and growth.