NVIDIA H100 SXM vs NVIDIA H200 SXM: specs, bandwidth and cost compared
The default training and high-throughput inference part for the 2023–2025 generation, and still the unit most capacity is quoted in. Same Hopper compute as H100 with 76% more memory and 43% more bandwidth. For inference, which is memory-bound, that bandwidth is the whole story.
Specifications
| Spec | NVIDIA H100 SXM | NVIDIA H200 SXM |
|---|---|---|
| Architecture | Hopper | Hopper |
| Released | 2022 | 2024 |
| Memory | 80 GB HBM3 | 141 GB HBM3e |
| Memory bandwidth | 3,350 GB/s | 4,800 GB/s |
| Dense FP16 | 989 TFLOPS | 989 TFLOPS |
| FP8 tensor cores | Yes | Yes |
| Board power | 700 W | 700 W |
| Interconnect | NVLink 4.0 (900 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 H200 SXM has 4,800 GB/s against 3,350 GB/s, a 1.43× 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 1.00×.
Rental cost
Indicative on-demand pricing runs roughly $1.90–$4.50 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.