NVIDIA H100, H200, B200 PCIe vs. SXM5
The rise of generative AI and large language models has redefined what's possible in enterprise computing—and it all started with the NVIDIA H100. As the first GPU to power commercially successful foundation models, the H100 laid the groundwork for a new generation of AI infrastructure.
Now, NVIDIA's GPU ecosystem has expanded. The H200 offers a seamless upgrade path with more memory and bandwidth, while the B200, based on the cutting-edge Blackwell architecture, is just beginning to enter the market with unmatched performance for AGI-scale workloads.
But how do you choose the right GPU—and form factor—for your business? Let's break down the capabilities, pricing, and ideal use cases of each.
H100: The Foundational Workhorse of Modern AI
The NVIDIA H100 Tensor Core GPU remains one of the most versatile and widely deployed GPUs for AI training and Inference. Available in both PCIe and SXM (via HGX systems), it offers a solid balance of performance, compatibility, and cost.
- Memory: 80GB HBM2e
- Form Factors: PCIe and SXM
- Peak FP8 Performance: Up to 4.9 PFLOPs (SXM)
- Arc's Availability:
- HGX Systems (SXM): Starting at $215,000 USD – View Servers
- PCIe Systems: Contact Sales
- Reserved Cloud (HGX H100): Arc's Reserved Cloud
Why Choose H100?
- PCIe: Ideal for scalable Inference and modular deployments. Broad compatibility and lower entry costs make it great for startups and production-ready GenAI teams.
- SXM (HGX): Designed for multi-GPU training. With NVLink and NVSwitch, up to 8 GPUs can share memory at high bandwidth, and HGX nodes can be networked for large-scale training.
H200: More Memory, More Bandwidth, Same Hopper Ecosystem
The NVIDIA H200 builds directly on the H100's Hopper architecture but nearly doubles its memory and significantly boosts bandwidth, making it ideal for models with long context windows, larger batch sizes, and increased parameter counts.
- Memory: 141GB HBM3e
- Memory Bandwidth: 4.8 TB/s
- Form Factors: SXM and NVL (dual-GPU PCIe variant)
- Arc's Availability:
- HGX Systems (SXM): Starting at $255,000 USD – View Servers
- PCIe Systems: Contact Sales
Why Choose H200?
- An ideal upgrade path from H100, especially if you're already using HGX systems.
- Designed for large model training, fine-tuning, and Inference at scale.
- Same software stack and tools as H100—just with more horsepower.
B200: Peak Performance with Blackwell
Built on NVIDIA's latest Blackwell architecture, the B200 represents a full generational leap. With 192GB of ultra-fast HBM3e memory and staggering performance figures, it's designed for organizations training trillion-parameter models or operating real-time AI factories.
- Memory: 180GB HBM3e
- Peak Performance: Up to 72 PFLOPs (training), 144 PFLOPs (Inference)
- Form Factor: SXM, part of HGX B200 and GB200 NVL72 systems
- Arc's Availability:
- HGX Systems (SXM): Starting at $348,000 USD – View Servers
- GB200 NVL72 Systems: Contact Sales
Why Choose B200?
- Perfect for hyperscalers, cloud platforms, and advanced research labs.
- Only GPU that rivals full-node performance for trillion-parameter workloads.
- A future-proof investment for AGI-scale infrastructure.
PCIe vs. SXM: Which Form Factor Is Right for You?
Choosing between PCIe and SXM is just as important as selecting the right GPU. Each form factor offers different advantages depending on workload type and scalability requirements.
TL;DR:
- Use PCIe for inference tasks, experimentation, or when cost and compatibility are top priorities.
- Use SXM (HGX) when training massive models that need fast GPU-to-GPU communication and pooled memory.
Comparison Table
Conclusion
Whether you're training your first foundation model or scaling a global AI platform, NVIDIA's GPU ecosystem has a solution tailored to your goals:
- H100 offers the best entry point for real-world AI workloads, now available through both on-prem servers and Arc's Reserved H100 Cloud.
- H200 gives you more memory, bandwidth, and scalability—perfect for model growth and training performance.
- B200 is the GPU of the future, ready today for companies building at the bleeding edge of AI.
Need help deciding which GPU and form factor is right for you? Our team at Arc Compute is here to help. We'll walk you through hardware choices, cloud deployments, and colocation options—all tailored to your workload and budget. Email us at sales@arccompute.io or fill out our Contact Us form.
