NVIDIA’s GPU Price Surge May Push Indian Cloud Costs Up 20%

NVIDIA has raised the listed price of its RTX PRO 6000 Blackwell GPU to $16,000, up from $13,250 in June. Indian AI and GPU cloud platform CloudPe expects this to raise GPU cloud prices in India by 15–20% over 12–18 months.

The company made the assessment citing higher memory costs and tight supply. The GPU’s price has risen nearly 87% from its March 2025 launch price of $8,565. 

Memory makers also expect supply to remain tight through 2027 and beyond. The supply pressure is affecting cloud infrastructure providers globally, including Indian providers such as CloudPe.

CloudPe Founder and CEO Ishan Talathi said GPU pricing depends largely on demand and component costs. He said memory remains a key cost pressure for NVIDIA. “Blended across our existing fleet and volume purchase commitments, we anticipate GPU cloud pricing in India to rise,” he said in a statement.

He added that prices could stabilise if memory supply improves or alternative architectures gain traction. CloudPe also said it secured a significant share of its GPU fleet before the latest price increase.

The company said its existing inventory can help limit the impact of higher replacement costs. 

The changing cost structure could also affect decisions around direct GPU purchases. High-demand GPUs can have hardware lead times of 40 weeks or more, according to CloudPe.

Cloud provisioning, by comparison, can provide capacity within days. Direct GPU purchases generally suit workloads running continuously for 36 months or longer. However, faster GPU generation cycles could shorten the period available to recover hardware investments. Businesses buying GPUs at peak prices also retain those acquisition costs when newer architectures arrive.

Cloud services shift ownership and hardware replacement risks to providers. Providers can also distribute infrastructure across workloads such as VDI, rendering, video transcoding, and AI inference.

The company links the current shortage to a shift in global memory capacity towards AI. It expects broader supply relief only after new fabrication capacity arrives in late 2027. CloudPe said businesses that deploy earlier could secure available capacity and gain greater visibility into compute costs. 

Delayed deployments could face further changes in hardware availability and pricing. The company said GPU availability, procurement cycles, technology refresh rates, and cloud pricing will increasingly shape AI deployment economics.