AWS raises GPU instance prices 20% on July 1 amid surging AI computing demand

AWS raising GPU instance prices 20% on July 1 By Investing.com

Investing.com -- Amazon's (NASDAQ:AMZN) AWS will raise prices on its EC2 Capacity Block reservations for machine-learning GPU instances by approximately 20% effective July 1, 2026, citing supply and demand dynamics in a posting to its official documentation page. The new hourly rates per accelerator span AWS's most powerful Nvidia-powered instance families: the P6-B300 will be billed at $14.04, the P6-B200 at $12.355, the P5 (US regions) at $5.191, the P5 (non-US) at $4.72, the P5e at $5.97, the P5en (US) at $6.865, the P5en (non-US) at $6.241, and the P4de (US) at $2.214. All other EC2 prices remain unchanged, according to the AWS documentation. "Amazon EC2 Capacity Blocks for ML reservation prices are updated periodically based on supply and demand," the company said on its pricing page. The hike lands at a moment of sustained, surging enterprise appetite for GPU compute. AWS revenue climbed 28% year-over-year to $37.6 billion in the first quarter of 2026, the cloud unit's fastest growth rate in more than three years, a pace that gave AWS considerable pricing leverage with customers locked into AI training and inference workloads. Amazon has committed roughly $200 billion in capital expenditure in 2026 to AI infrastructure, and Reuters reported in March 2026 that Amazon is set to receive 1 million Nvidia GPU chips by end-2027 under a cloud supply agreement -- a deal that underscores just how supply-constrained the high-end GPU market remains. Capacity Blocks for ML are a reserved-capacity product that lets enterprises secure scarce GPU instances on a future date for time-bound workloads, typically large-scale model training. Because the product is reservation-based, customers have been willing to pay a premium over spot-market rates for the guarantee of availability; the new rates represent a significant step-up in that premium. For context, P6-B200 on-demand rates for an eight-GPU node were already running at roughly $14.24 per hour for the full node ahead of this change, per pricing analysis from Spheron Network published on June 20. For Nvidia, the pricing action is a dual-edged signal. The tight supply of P5 and P6 instances, which are built on Nvidia's Blackwell (B200, B300) and Hopper (H100) GPU architectures, confirms robust end-market demand for Nvidia silicon. Yet rising reservation costs could prompt some AWS customers to evaluate alternatives, including Nvidia-powered offerings on rival clouds or Google Cloud's TPU-based instances, which Alphabet has been actively marketing as a cost-competitive option. Whether Microsoft Azure or Google Cloud follow AWS with comparable GPU reservation price increases will be closely watched. Azure is AWS's nearest rival in enterprise cloud infrastructure, and a unilateral AWS hike could either spur competitive repricing or give Azure and Google Cloud an opening to attract cost-sensitive AI workloads. It also remains unclear whether existing Capacity Block reservations placed before July 1 will be honored at prior rates or billed at the new schedule from that date forward. With the increases taking effect in less than a week, enterprise buyers face an immediate decision: lock in any remaining capacity at current rates before July 1 or absorb the higher costs as a structural feature of the AI infrastructure landscape AWS has helped define.

Amazon Web Services to Raise Prices for Some EC2 AI Capacity Blocks

Amazon.com's Amazon Web Services said it would prices for certain Amazon EC2 Capacity Blocks for machine learning beginning July 1 as part of a periodic pricing update based on supply and demand. The company said hourly reservation rates would increase for several instance types powered by graphics-processing units, or GPUs, including P6-B300, P6-B200, P5, P5e, P5en and P4de Capacity Blocks. Other prices would remain unchanged. The updated rates apply across most AWS regions, with some regional differences. EC2 Capacity Blocks let customers reserve GPU-powered-computing capacity in advance for artificial-intelligence-model training and other machine-learning workloads, ensuring access to high-demand chips without long-term commitments. The service supports Nvidia Blackwell, H200, H100 and A100 GPUs, as well as AWS's Trainium chips, and allows reservations for up to six months. AWS's Capacity Blocks require customers to pay an upfront reservation fee, with operating-system charges billed separately while instances are running. Demand for AI-computing capacity has surged as companies race to build and deploy generative AI models. The Wall Street Journal previously reported that GPU-capacity shortages have pushed up rental prices for advanced Nvidia chips and forced some AI companies to ration computing resources amid strong demand.