Specifications: H100 NVL vs H100 PCIe
The H100 NVL and H100 PCIe have different architecture generations resulting in varying compute capabilities. Key spec differences include memory bandwidth, tensor core generation, supported precision formats, and inter-GPU connectivity options including NVLink, NVSwitch, and PCIe Gen5.
AI Inference Performance
For LLM inference, the H100 PCIe generally achieves 30-120% higher throughput than the H100 NVL depending on model size and batch configuration. For a 7B model at FP8 with continuous batching, the H100 NVL serves 1,800-2,400 tok/s while the H100 PCIe reaches 3,000-5,000 tok/s. For 70B models, tensor parallelism across 4 GPUs is needed on the H100 NVL while the H100 PCIe may serve the same model with 2 GPUs due to higher VRAM. Prefill latency for 4K tokens ranges from 35-55ms for the H100 NVL versus 18-35ms for the H100 PCIe.
Training Throughput Comparison
On training workloads, the H100 PCIe delivers 40-120% higher throughput for typical model sizes. For a 7B model at BF16 mixed precision, per-GPU throughput reaches 3,500-4,500 tok/s on the H100 NVL versus 5,000-8,000 tok/s on the H100 PCIe. Model FLOPS utilization (MFU) ranges from 38-48% on the H100 NVL and 42-55% on the H100 PCIe. Memory capacity constraints on the H100 NVL require activation checkpointing for models larger than 13B, while the H100 PCIe accommodates larger models without checkpointing.
VRAM and Model Capacity Analysis
Memory capacity is the most critical differentiator. The H100 NVL has limited VRAM, while the H100 PCIe has more VRAM. At FP16, a 7B model requires ~14 GB for weights, plus KV cache of ~1.5 GB per 128K context per request. INT4 quantization halves the weight memory requirement, enabling larger models or batch sizes. The VRAM gap is most impactful for long-context serving and large batch inference.
Cloud Pricing and TCO
On-demand cloud pricing for the H100 NVL averages $3.00/hr while the H100 PCIe averages $2.20/hr. However, cost-per-token analysis often favors the H100 PCIe by 15-40% for sustained production workloads due to higher throughput. Reserved 12-month contracts provide 30-50% discounts. For a 64-GPU, 3-year TCO, the H100 NVL cluster costs $895K-$948K while the H100 PCIe cluster costs $1101K-$1453K including hardware, power, cooling, and maintenance.
Which GPU Should You Choose?
Choose the H100 NVL for: budget-constrained deployments, models under 13B that fit in available VRAM, batch inference workloads where throughput per dollar is secondary to absolute cost, and development/staging environments. Choose the H100 PCIe for: production serving at scale, models larger than 13B parameters, workloads requiring FP8/FP4 precision, long-context inference beyond 128K tokens, and clusters above 128 GPUs where scaling efficiency matters.