A100 PCIe 80GB vs H200 NVL

The H200 demonstrates superior compute capabilities compared to the A100: its 1979 TFLOPS FP16 rate dwarfs the A100's 312 TFLOPS, accelerating half-precision training for large language models by over sixfold. Similarly, 67 TFLOPS FP32 outperforms the A100's 19.5 TFLOPS, benefiting single-precision scientific simulations and general compute tasks. The H200's FP8 at 3958 TFLOPS further optimizes low-precision inference workloads.

Memory specifications create significant real-world impacts: the H200's 141 GB HBM3e VRAM exceeds the A100's 80 GB HBM2e, enabling larger batch sizes and models without swapping. Its 4800 GB/s bandwidth, more than double the A100's 2039 GB/s, reduces data bottlenecks during training, allowing higher throughput for memory-intensive operations like transformer processing.

These differences translate to faster iteration times in AI pipelines: for LLM training, the H200 handles massive datasets efficiently, while inference benefits from FP8 and bandwidth for low-latency serving at scale.

The A100 PCIe 80GB suits cost-sensitive deployments: its pricing starts at $0.89 per hour across 28 offers, compared to the H200's $0.50 per hour but only 4 offers. Lower 400W TDP fits power-constrained environments, and 80 GB VRAM handles many mid-sized models adequately.

Legacy Ampere-optimized software or PCIe 4.0 clusters favor the A100: it delivers reliable 312 TFLOPS FP16 for fine-tuning and inference without Hopper-specific requirements.

The H200 NVL excels in memory-bound workloads: 141 GB HBM3e VRAM supports models exceeding 80 GB, unlike the A100. Its 4800 GB/s bandwidth sustains large batch sizes in training.

High-performance AI demands the H200: 1979 TFLOPS FP16 and 3958 TFLOPS FP8 provide unmatched speed for LLM inference and cutting-edge Hopper features via PCIe 5.0.