NVIDIA B200s: Unlocking Scalable AI Performance with the Corvex AI Cloud

The NVIDIA B200 represents a major step forward in GPU architecture, enabling faster, more efficient training and inference across the most demanding AI workloads—from large language models (LLMs) to diffusion models and multimodal systems. At Corvex, we’ve integrated these new GPUs into an infrastructure purpose-built to remove bottlenecks, maximize security, and support AI developers at scale.

How B200s Compare Against H200s and H100s

Blackwell-based B200s build on the Hopper generation with significant architectural gains:

• More HBM3e: 192GB of 1.8TB/s high-bandwidth memory per GPU (vs. 141GB for H200s and 100GB for H100s), supporting larger models and longer context windows.
  
  
• More Compute: Up to 20 petaFLOPs of 4-bit floating point (“FP4”) throughput per GPU—ideal for transformer-based inference and training.
  
  
• Smarter Precision: Native support for FP4, which allows for denser, faster inference workloads without loss of model quality.
  
  

These advances translate into practical improvements: faster training times, lowering TCO for both training and inference, and fewer compromises when running large models. The increase to 192GB of HBM3e memory—combined with dramatically higher memory bandwidth and FP4 throughput—means developers can fit larger models, or longer context windows, directly on a single GPU. 

This reduces the need for model parallelism, which often involves splitting a model across multiple GPUs and managing communication overhead between them. Avoiding this setup simplifies infrastructure, lowers interconnect latency, and minimizes synchronization errors. It also makes inference and fine-tuning more reproducible and easier to debug, since developers don’t have to implement or rely on fragile tensor-slicing or custom communication primitives. With B200s, more of your model lives on-chip, and more of your time goes into development—not infrastructure workarounds.

Where B200s Really Shine

B200s are especially well-suited for workloads involving:

• LLM inference at scale, particularly larger models and longer context windows
  
  
• Foundation model training and fine-tuning
  
  
• Image, video, and diffusion-based generation
  
  
• Multimodal AI systems requiring flexible tensor layouts and large memory footprints

For training foundation models, the B200 delivers sustained throughput thanks to its high PFLOP capacity and improved memory bandwidth—critical for large batch sizes and long training runs. And for diffusion or video models, the ability to keep high-dimensional tensors local to the GPU reduces pipeline fragmentation and allows for faster frame synthesis. In short, the B200 provides the kind of dense, fast, and flexible compute platform that these workloads demand.

Optimizing B200 Performance

At Corvex, the B200’s hardware capabilities are augmented by infrastructure design choices that eliminate common performance ceilings:

• Hot-rodded servers with proprietary, low-latency modifications to boost processing time across standard AI workloads. Corvex has implemented proprietary server modifications, accelerating common AI pipeline operations. Processing can be further accelerated with the addition of Corvex’s upcoming hosted inference engine, further reducing TCO.
  
  
• Liquid cooling to eliminate thermal throttling, increase reliability, and lower operating costs, even in rack densities exceeding 100kW. Fewer moving parts mean fewer maintenance interruptions and significantly better uptime. Liquid cooling also requires far less power than air cooling, netting operational cost savings that are passed on to customers. 
  
  
• Super fast networking: Corvex offers 3.2Tbps InfiniBand fabric that is never oversubscribed and 400Gbps RoCE storage networking mean GPUs are never starved for data, minimizing job length and optimizing the cost of deployments.
  
  
• Zero power caps or downclocking: Workloads run at sustained peak performance with optimized power and FLOP usage. 

In practice, this means Corvex customers get full-speed access to the B200’s capabilities—whether running short inference jobs or multi-day fine-tuning sessions.

Who Needs B200s

The B200 architecture, combined with Corvex’s infrastructure design, is ideal for model training, inference of large models and/or requests with long context windows, and instances where security and privacy are crucial. 

• Generative AI companies, early stage start-ups, and research labs developing frontier models or working with trillion-parameter or multi-agent systems
  
  
• AI infrastructure teams managing retrieval-augmented generation (RAG), fine-tuning pipelines, or running large-scale inference
  
  
• Healthcare, finance, government, and other organizations with strict security requirements
  
  
• Research labs and early-stage startups working with trillion-parameter or multi-agent systems
  
  

What these groups share is a need for faster model throughput, greater memory capacity, and security assurance—without sacrificing flexibility.

B200s on the Corvex AI Cloud: Fast, Secure, Cost-Effective

Corvex’s AI Cloud is purpose-built for running LLMs, foundation models, and diffusion models at scale—delivering top-tier performance, enterprise-grade security, and expert support, all with a lower total cost of ownership (TCO).

Corvex delivers:

• Efficient, High-Performance Computing: Hot-rodded servers, proprietary software accelerators, and 192GB of HBM3e per GPU enable notable improvements in throughput. Liquid-only cooling and zero thermal throttling support reliable, super efficient operation.
  
  
• Built-In Security: Confidential computing encrypts data during processing, with Trusted Execution Environments (TEEs), end-to-end SOC2 compliance (not just our data centers), and HIPAA readiness for regulated workloads (3Q 2025).
  
  
• Easily Accessible GPU infrastructure: Corvex’s team of seasoned AI and high-performance computing veterans offer hands-on guidance for model migration, system tuning, and runtime troubleshooting—24/7.

‍

• Lower TCO: Corvex’s accelerated stack—combined with efficient cooling and 3.2Tbps InfiniBand networking—increases processing efficiency, reduces energy use, and lowers customer TCO.

‍

The NVIDIA B200 marks a new era in scalable AI performance. But to realize its full potential, teams need infrastructure that’s purpose-built for next-gen compute. The Corvex AI Cloud delivers everything serious builders need to optimize their AI endeavors.  

‍