Vultr VX1™ Cloud Compute: Affordable Cloud Computing for the Era of Agentic AI
The rise of agentic AI is catalyzing a surge in investment in cloud infrastructure and putting cloud cost optimization back in the spotlight. According to McKinsey research, data centers worldwide are projected to require $6.7 trillion by 2030 to keep pace with demand for compute power. The majority ($5.2 trillion) of this capital expenditure is related to AI processing loads, but core IT applications will still require a hefty $1.5 trillion in spending.
From an architectural perspective, agentic AI introduces new challenges. Notably, agentic AI workloads require significantly more CPU than GPUs. Rather than the previous 1:4-8 CPU-to-GPU ratio with chatbot AI, agentic AI is moving toward a 1:1 ratio and, in some cases, it’s higher on the CPU side.
However, this is a much deeper issue than simply adding more CPUs to GPU-heavy racks. As AMD argues: ‘agentic AI is driving demand for entirely new racks of CPU servers that sit alongside GPU infrastructure and run to power the work of all these agents.’
Beyond cloud cost optimization: server CPUs in the age of agentic AI
The reason CPUs are so important is that agentic AI requires a range of management processes, such as scheduling, data preparation, memory and I/O, and control flow, to keep GPU accelerators productive. Insufficient CPU performance can slow down GPU delivery and affect the entire system's performance.
In the light of Agentic AI, enterprises therefore need to think differently about server CPU architectures. The long-standing mission to reduce cloud costs remains in place, but alongside this sits a new focus on performance. CPUs need to be high-density, high-frequency, and memory optimized to deliver the performance, energy efficiency, and cost that agentic AI demands.
Vultr VX1™: A new foundation for agentic AI data centers
The key shift for Agentic AI architectures is that CPUs should not simply be bolted onto the GPU rack. Instead, businesses need to build a new high-performance, price-performance optimized CPU layer for agent orchestration and data processing.
This is the requirement that Vultr VX1™ meets. Based on the latest AMD EPYC™ processors, the solution is up to 33% more affordable per vCPU and offers up to an 82% performance-per-dollar advantage over efficiency-optimized (ARM-based) compute plans from the traditional hyperscalers.
Recent benchmarking tests highlight the value of Vultr VX1, demonstrating that it delivers the leading absolute price as well as price-to-performance ratio. The solution is also among the top three in terms of absolute performance:
Performance benchmarks were run using the Geekbench 6.5 benchmark, and no others, on comparable 2 vCPU / 8 GB RAM plans.
Performance and price-performance metrics are based on single-core performance.
Azure Cobalt used previous generation due to unavailability of the current generation.
DigitalOcean price and price-performance comparison was calculated using VX1 with Local NVMe, due to DigitalOcean not offering a boot from block storage option.
Vultr VX1 Cloud Compute therefore delivers the right economics and performance that enterprises need to optimize their agentic AI CPU racks. Plus, if businesses deploy Vultr VX1 Cloud Compute for their existing core enterprise workloads, they can dramatically reduce cloud costs, freeing up budget to invest in their new agentic AI infrastructure. It’s a virtuous circle: Greater efficiency today leads to greater innovation tomorrow. What’s more, as an open solution, businesses can escape hyperscaler lock-in and ensure that the next iteration of their cloud infrastructure is built entirely on their own terms.
To learn more about CPU modernization and the shift to agentic AI infrastructure, download our new whitepaper: Seize the Advantage: How Cloud Cost Optimization Can Fuel Agentic AI.
