Evonova’s AI Compute Infrastructure for the Next Era of Intelligence

Over the last 12 months, demand for AI compute has skyrocketed. From OpenAI to Stability.ai, Meta to Microsoft, and across startups building vertical-specific agents or autonomous research loops, everyone is chasing the same bottleneck: GPU availability. 

Even with NVIDIA's record-breaking revenues, they can’t build enough chips fast enough. 

Leasing HGX B200s at $4.50 to $7+ per GPU/hour has quickly become a profitable income stream. 

In the race to power generative models, autonomous agents, and multimodal systems, infrastructure is everything. At the center of this new frontier lies the NVIDIA HGX B200—an ultra-powerful, 8-GPU server platform that is fast becoming the backbone of next-generation AI systems. 
 

What is the HGX B200? 

At its heart, the HGX B200 server is a high-density AI infrastructure unit built to handle the world’s most demanding machine learning, generative AI, and inference workloads. It’s typically packaged as a 4U or 5U chassis, with eight NVIDIA B200 GPUs, each connected via NVLink, and backed by terabytes of fast memory and high-throughput networking. 

With a single unit capable of over 40,000 TFLOPs (trillion floating point operations per second), the HGX B200 doesn’t just outperform its predecessors—it obliterates them. It was purpose-built for multimodal AI training, LLM inference, large-scale simulation, and even synthetic biology. 

While this may sound niche, the demand is anything but. 

Unlike prior cycles where software stole the spotlight, today it’s high-density compute that holds the keys to scale. The HGX B200, built with NVIDIA’s cutting-edge Blackwell architecture, delivers unmatched performance for training large language models, real-time inference, and massive parallel computation. With each unit offering tens of thousands of TFLOPs of compute, it sets a new standard for high-performance AI infrastructure. 

But beyond its capabilities, it’s the economics that are drawing serious attention. Leasing HGX B200 compute has emerged as one of the most compelling yield strategies in AI infrastructure. Each server, comprising 8 powerful GPUs, can command lease rates of $4.50 to $7+ per GPU/hour. That translates into daily revenue in excess of $850 per node—and over $300,000 per year per server. With minimal energy costs in low-cost hydro locations like Washington State, and hosting expenses under control, margins can rival or even surpass traditional crypto mining. 

This shift marks a new phase in digital infrastructure. Instead of speculative growth, these servers deliver daily, cash-generative returns from paying customers. For investors and treasury managers, this introduces a tangible, productive asset that supports portfolio diversification while riding the wave of AI expansion. 

Owning HGX B200 units is not just an operational advantage—it’s an income engine. With global demand outpacing supply, and unit availability limited to major integrators and partners, early access provides a rare and powerful edge. 

As enterprises, research groups, and startups race to develop proprietary AI tools, the market for high-performance GPUs will only deepen. And those who control the infrastructure will shape the next decade of innovation.