NVIDIA A100 80GB SXM vs NVIDIA H100 SXM: specs, bandwidth and cost compared
The previous generation workhorse. No FP8, so modern quantised serving stacks give up a large fraction of their advantage here. The default training and high-throughput inference part for the 2023–2025 generation, and still the unit most capacity is quoted in.
Specifications
| Spec | NVIDIA A100 80GB SXM | NVIDIA H100 SXM |
|---|---|---|
| Architecture | Ampere | Hopper |
| Released | 2020 | 2022 |
| Memory | 80 GB HBM2e | 80 GB HBM3 |
| Memory bandwidth | 2,039 GB/s | 3,350 GB/s |
| Dense FP16 | 312 TFLOPS | 989 TFLOPS |
| FP8 tensor cores | No | Yes |
| Board power | 400 W | 700 W |
| Interconnect | NVLink 3.0 (600 GB/s) | NVLink 4.0 (900 GB/s) |
| Segment | datacenter | datacenter |
Which one to pick
Inference throughput on large models is bound by memory bandwidth far more than by peak FLOPS. NVIDIA H100 SXM has 3,350 GB/s against 2,039 GB/s, a 1.64× difference, which is the figure that most closely tracks tokens per second at batch size 1. Training and large-batch serving lean more on FP16 throughput, where the gap is 3.17×.
Rental cost
Indicative on-demand pricing runs roughly $0.80–$2.20 per GPU-hour depending on provider, region, and commitment. Spot and reserved capacity sit well below that band. These are ranges rather than quotes: street prices move week to week, so check live cloud price feed before budgeting.